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Sample records for finland granger causality

  1. Granger causality for circular variables

    Energy Technology Data Exchange (ETDEWEB)

    Angelini, Leonardo; Pellicoro, Mario [Istituto Nazionale di Fisica Nucleare, Sezione di Bari (Italy); Dipartimento di Fisica, University of Bari (Italy); Stramaglia, Sebastiano, E-mail: sebastiano.stramaglia@ba.infn.i [Istituto Nazionale di Fisica Nucleare, Sezione di Bari (Italy); Dipartimento di Fisica, University of Bari (Italy)

    2009-06-29

    In this Letter we discuss the use of Granger causality to the analyze systems of coupled circular variables, by modifying a recently proposed method for multivariate analysis of causality. We show the application of the proposed approach on several Kuramoto systems, in particular one living on networks built by preferential attachment and a model for the transition from deeply to lightly anaesthetized states. Granger causalities describe the flow of information among variables.

  2. Granger Causality and Unit Roots

    DEFF Research Database (Denmark)

    Rodríguez-Caballero, Carlos Vladimir; Ventosa-Santaulària, Daniel

    2014-01-01

    The asymptotic behavior of the Granger-causality test under stochastic nonstationarity is studied. Our results confirm that the inference drawn from the test is not reliable when the series are integrated to the first order. In the presence of deterministic components, the test statistic diverges......, eventually rejecting the null hypothesis, even when the series are independent of each other. Moreover, controlling for these deterministic elements (in the auxiliary regressions of the test) does not preclude the possibility of drawing erroneous inferences. Granger-causality tests should not be used under...

  3. Granger Causality and Unit Roots

    DEFF Research Database (Denmark)

    Rodríguez-Caballero, Carlos Vladimir; Ventosa-Santaulària, Daniel

    2014-01-01

    The asymptotic behavior of the Granger-causality test under stochastic nonstationarity is studied. Our results confirm that the inference drawn from the test is not reliable when the series are integrated to the first order. In the presence of deterministic components, the test statistic diverges...

  4. Decomposing Granger Causality over the Spectrum

    NARCIS (Netherlands)

    A. Lemmens (Aurélie); C. Croux (Christophe); M.G. Dekimpe (Marnik)

    2004-01-01

    textabstractWe develop a bivariate spectral Granger-causality test that can be applied at each individual frequency of the spectrum. The spectral approach to Granger causality has the distinct advantage that it allows to disentangle (potentially) di®erent Granger- causality relationships over di®ere

  5. Granger causality for state-space models.

    Science.gov (United States)

    Barnett, Lionel; Seth, Anil K

    2015-04-01

    Granger causality has long been a prominent method for inferring causal interactions between stochastic variables for a broad range of complex physical systems. However, it has been recognized that a moving average (MA) component in the data presents a serious confound to Granger causal analysis, as routinely performed via autoregressive (AR) modeling. We solve this problem by demonstrating that Granger causality may be calculated simply and efficiently from the parameters of a state-space (SS) model. Since SS models are equivalent to autoregressive moving average models, Granger causality estimated in this fashion is not degraded by the presence of a MA component. This is of particular significance when the data has been filtered, downsampled, observed with noise, or is a subprocess of a higher dimensional process, since all of these operations-commonplace in application domains as diverse as climate science, econometrics, and the neurosciences-induce a MA component. We show how Granger causality, conditional and unconditional, in both time and frequency domains, may be calculated directly from SS model parameters via solution of a discrete algebraic Riccati equation. Numerical simulations demonstrate that Granger causality estimators thus derived have greater statistical power and smaller bias than AR estimators. We also discuss how the SS approach facilitates relaxation of the assumptions of linearity, stationarity, and homoscedasticity underlying current AR methods, thus opening up potentially significant new areas of research in Granger causal analysis.

  6. Granger causality and contiguity between stochastic processes

    Energy Technology Data Exchange (ETDEWEB)

    Triacca, Umberto [Universita di L' Aquila, Roio Poggio, I-67040 L' Aquila (Italy)]. E-mail: triacca@ec.univaq.it

    2007-03-05

    Although according to many econometricians the definition of causality proposed by Granger differs from other definitions of causation in the philosophy of science, in this Letter we argue that it is not completely lacking in philosophical legitimacy. We attempt to shed new light on the nexus between Granger causality and the concept of contiguity. In particular, we prove that the existence of a Granger causal link between two stochastic processes requires that these be 'contiguous' or that there exist a chain of processes, one contiguous to the next, which link the two processes.

  7. Synergy, redundancy and unnormalized Granger causality

    CERN Document Server

    Stramaglia, Sebastiano; Cortés, Jesus M; Marinazzo, Daniele

    2015-01-01

    We analyze by means of Granger causality the effect of synergy and redundancy in the inference (from time series data) of the information flow between subsystems of a complex network. Whilst fully conditioned Granger causality is not affected by synergy, the pairwise analysis fails to put in evidence synergetic effects. We show that maximization of the total Granger causality to a given target, over all the possible partitions of the set of driving variables, puts in evidence redundant multiplets of variables influencing the target, provided that an {\\it unnormalized} definition of Granger causality is adopted. Along the same lines we also introduce a pairwise index of synergy (w.r.t. to information flow to a third variable) which is zero when two independent sources additively influence a common target, differently from previous definitions of synergy.

  8. On the spectral formulation of Granger causality.

    Science.gov (United States)

    Chicharro, D

    2011-12-01

    Spectral measures of causality are used to explore the role of different rhythms in the causal connectivity between brain regions. We study several spectral measures related to Granger causality, comprising the bivariate and conditional Geweke measures, the directed transfer function, and the partial directed coherence. We derive the formulation of dependence and causality in the spectral domain from the more general formulation in the information-theory framework. We argue that the transfer entropy, the most general measure derived from the concept of Granger causality, lacks a spectral representation in terms of only the processes associated with the recorded signals. For all the spectral measures we show how they are related to mutual information rates when explicitly considering the parametric autoregressive representation of the processes. In this way we express the conditional Geweke spectral measure in terms of a multiple coherence involving innovation variables inherent to the autoregressive representation. We also link partial directed coherence with Sims' criterion of causality. Given our results, we discuss the causal interpretation of the spectral measures related to Granger causality and stress the necessity to explicitly consider their specific formulation based on modeling the signals as linear Gaussian stationary autoregressive processes.

  9. Localizing epileptic seizure onsets with Granger causality

    Science.gov (United States)

    Adhikari, Bhim M.; Epstein, Charles M.; Dhamala, Mukesh

    2013-09-01

    Accurate localization of the epileptic seizure onset zones (SOZs) is crucial for successful surgery, which usually depends on the information obtained from intracranial electroencephalography (IEEG) recordings. The visual criteria and univariate methods of analyzing IEEG recordings have not always produced clarity on the SOZs for resection and ultimate seizure freedom for patients. Here, to contribute to improving the localization of the SOZs and to understanding the mechanism of seizure propagation over the brain, we applied spectral interdependency methods to IEEG time series recorded from patients during seizures. We found that the high-frequency (>80 Hz) Granger causality (GC) occurs before the onset of any visible ictal activity and causal relationships involve the recording electrodes where clinically identifiable seizures later develop. These results suggest that high-frequency oscillatory network activities precede and underlie epileptic seizures, and that GC spectral measures derived from IEEG can assist in precise delineation of seizure onset times and SOZs.

  10. Granger Causality, Exogeneity, Cointegration, and Economic Policy Analysis

    OpenAIRE

    Davide Pettenuzzo; Halbert White

    2010-01-01

    Policy analysis has long been a main interest of Clive Granger's. Here, we present a framework for economic policy analysis that provides a novel integration of several fundamental concepts at the heart of Granger's contributions to time-series analysis. We work with a dynamic structural system analyzed by White and Lu (2010) with well-defined causal meaning; under suitable conditional exogeneity restrictions, Granger causality coincides with this structural notion. The system contains target...

  11. Manifest Variable Granger Causality Models for Developmental Research: A Taxonomy

    Science.gov (United States)

    von Eye, Alexander; Wiedermann, Wolfgang

    2015-01-01

    Granger models are popular when it comes to testing hypotheses that relate series of measures causally to each other. In this article, we propose a taxonomy of Granger causality models. The taxonomy results from crossing the four variables Order of Lag, Type of (Contemporaneous) Effect, Direction of Effect, and Segment of Dependent Series…

  12. Assessing thalamocortical functional connectivity with Granger causality.

    Science.gov (United States)

    Chen, Cheng; Maybhate, Anil; Israel, David; Thakor, Nitish V; Jia, Xiaofeng

    2013-09-01

    Assessment of network connectivity across multiple brain regions is critical to understanding the mechanisms underlying various neurological disorders. Conventional methods for assessing dynamic interactions include cross-correlation and coherence analysis. However, these methods do not reveal the direction of information flow, which is important for studying the highly directional neurological system. Granger causality (GC) analysis can characterize the directional influences between two systems. We tested GC analysis for its capability to capture directional interactions within both simulated and in vivo neural networks. The simulated networks consisted of Hindmarsh-Rose neurons; GC analysis was used to estimate the causal influences between two model networks. Our analysis successfully detected asymmetrical interactions between these networks ( , t -test). Next, we characterized the relationship between the "electrical synaptic strength" in the model networks and interactions estimated by GC analysis. We demonstrated the novel application of GC to monitor interactions between thalamic and cortical neurons following ischemia induced brain injury in a rat model of cardiac arrest (CA). We observed that during the post-CA acute period the GC interactions from the thalamus to the cortex were consistently higher than those from the cortex to the thalamus ( 1.983±0.278 times higher, p = 0.021). In addition, the dynamics of GC interactions between the thalamus and the cortex were frequency dependent. Our study demonstrated the feasibility of GC to monitor the dynamics of thalamocortical interactions after a global nervous system injury such as CA-induced ischemia, and offers preferred alternative applications in characterizing other inter-regional interactions in an injured brain.

  13. Granger causality and transfer entropy are equivalent for Gaussian variables.

    Science.gov (United States)

    Barnett, Lionel; Barrett, Adam B; Seth, Anil K

    2009-12-01

    Granger causality is a statistical notion of causal influence based on prediction via vector autoregression. Developed originally in the field of econometrics, it has since found application in a broader arena, particularly in neuroscience. More recently transfer entropy, an information-theoretic measure of time-directed information transfer between jointly dependent processes, has gained traction in a similarly wide field. While it has been recognized that the two concepts must be related, the exact relationship has until now not been formally described. Here we show that for Gaussian variables, Granger causality and transfer entropy are entirely equivalent, thus bridging autoregressive and information-theoretic approaches to data-driven causal inference.

  14. Granger causality and transfer entropy are equivalent for Gaussian variables

    CERN Document Server

    Barnett, Lionel; Seth, Anil

    2009-01-01

    Granger causality is a statistical notion of causal influence based on prediction via vector autoregression. Developed originally in the field of econometrics, it has since found application in a broader arena, particularly in neuroscience. More recently transfer entropy, an information-theoretic measure of time-directed information transfer between jointly dependent processes, has gained traction in a similarly wide field. It has always seemed plausible that the two concepts ought to be related. Here we show that for Gaussian variables, Granger causality and transfer entropy are entirely equivalent, thus bridging autoregressive and information-theoretic approaches to data-driven causal inference.

  15. Kernel canonical-correlation Granger causality for multiple time series

    Science.gov (United States)

    Wu, Guorong; Duan, Xujun; Liao, Wei; Gao, Qing; Chen, Huafu

    2011-04-01

    Canonical-correlation analysis as a multivariate statistical technique has been applied to multivariate Granger causality analysis to infer information flow in complex systems. It shows unique appeal and great superiority over the traditional vector autoregressive method, due to the simplified procedure that detects causal interaction between multiple time series, and the avoidance of potential model estimation problems. However, it is limited to the linear case. Here, we extend the framework of canonical correlation to include the estimation of multivariate nonlinear Granger causality for drawing inference about directed interaction. Its feasibility and effectiveness are verified on simulated data.

  16. Analyzing multiple spike trains with nonparametric Granger causality.

    Science.gov (United States)

    Nedungadi, Aatira G; Rangarajan, Govindan; Jain, Neeraj; Ding, Mingzhou

    2009-08-01

    Simultaneous recordings of spike trains from multiple single neurons are becoming commonplace. Understanding the interaction patterns among these spike trains remains a key research area. A question of interest is the evaluation of information flow between neurons through the analysis of whether one spike train exerts causal influence on another. For continuous-valued time series data, Granger causality has proven an effective method for this purpose. However, the basis for Granger causality estimation is autoregressive data modeling, which is not directly applicable to spike trains. Various filtering options distort the properties of spike trains as point processes. Here we propose a new nonparametric approach to estimate Granger causality directly from the Fourier transforms of spike train data. We validate the method on synthetic spike trains generated by model networks of neurons with known connectivity patterns and then apply it to neurons simultaneously recorded from the thalamus and the primary somatosensory cortex of a squirrel monkey undergoing tactile stimulation.

  17. Mitigating the effects of measurement noise on Granger causality

    CERN Document Server

    Nalatore, Hariharan; Ding, Mingzhou

    2007-01-01

    Computing Granger causal relations among bivariate experimentally observed time series has received increasing attention over the past few years. Such causal relations, if correctly estimated, can yield significant insights into the dynamical organization of the system being investigated. Since experimental measurements are inevitably contaminated by noise, it is thus important to understand the effects of such noise on Granger causality estimation. The first goal of this paper is to provide an analytical and numerical analysis of this problem. Specifically, we show that, due to noise contamination, (1) spurious causality between two measured variables can arise and (2) true causality can be suppressed. The second goal of the paper is to provide a denoising strategy to mitigate this problem. Specifically, we propose a denoising algorithm based on the combined use of the Kalman filter theory and the Expectation-Maximization (EM) algorithm. Numerical examples are used to demonstrate the effectiveness of the den...

  18. Granger causality vs. dynamic Bayesian network inference: a comparative study

    Directory of Open Access Journals (Sweden)

    Feng Jianfeng

    2009-04-01

    Full Text Available Abstract Background In computational biology, one often faces the problem of deriving the causal relationship among different elements such as genes, proteins, metabolites, neurons and so on, based upon multi-dimensional temporal data. Currently, there are two common approaches used to explore the network structure among elements. One is the Granger causality approach, and the other is the dynamic Bayesian network inference approach. Both have at least a few thousand publications reported in the literature. A key issue is to choose which approach is used to tackle the data, in particular when they give rise to contradictory results. Results In this paper, we provide an answer by focusing on a systematic and computationally intensive comparison between the two approaches on both synthesized and experimental data. For synthesized data, a critical point of the data length is found: the dynamic Bayesian network outperforms the Granger causality approach when the data length is short, and vice versa. We then test our results in experimental data of short length which is a common scenario in current biological experiments: it is again confirmed that the dynamic Bayesian network works better. Conclusion When the data size is short, the dynamic Bayesian network inference performs better than the Granger causality approach; otherwise the Granger causality approach is better.

  19. On directed information theory and Granger causality graphs.

    Science.gov (United States)

    Amblard, Pierre-Olivier; Michel, Olivier J J

    2011-02-01

    Directed information theory deals with communication channels with feedback. When applied to networks, a natural extension based on causal conditioning is needed. We show here that measures built from directed information theory in networks can be used to assess Granger causality graphs of stochastic processes. We show that directed information theory includes measures such as the transfer entropy, and that it is the adequate information theoretic framework needed for neuroscience applications, such as connectivity inference problems.

  20. Increasing fMRI sampling rate improves Granger causality estimates.

    Directory of Open Access Journals (Sweden)

    Fa-Hsuan Lin

    Full Text Available Estimation of causal interactions between brain areas is necessary for elucidating large-scale functional brain networks underlying behavior and cognition. Granger causality analysis of time series data can quantitatively estimate directional information flow between brain regions. Here, we show that such estimates are significantly improved when the temporal sampling rate of functional magnetic resonance imaging (fMRI is increased 20-fold. Specifically, healthy volunteers performed a simple visuomotor task during blood oxygenation level dependent (BOLD contrast based whole-head inverse imaging (InI. Granger causality analysis based on raw InI BOLD data sampled at 100-ms resolution detected the expected causal relations, whereas when the data were downsampled to the temporal resolution of 2 s typically used in echo-planar fMRI, the causality could not be detected. An additional control analysis, in which we SINC interpolated additional data points to the downsampled time series at 0.1-s intervals, confirmed that the improvements achieved with the real InI data were not explainable by the increased time-series length alone. We therefore conclude that the high-temporal resolution of InI improves the Granger causality connectivity analysis of the human brain.

  1. LEARNING GRANGER CAUSALITY GRAPHS FOR MULTIVARIATE NONLINEAR TIME SERIES

    Institute of Scientific and Technical Information of China (English)

    Wei GAO; Zheng TIAN

    2009-01-01

    An information theory method is proposed to test the. Granger causality and contemporaneous conditional independence in Granger causality graph models. In the graphs, the vertex set denotes the component series of the multivariate time series, and the directed edges denote causal dependence, while the undirected edges reflect the instantaneous dependence. The presence of the edges is measured by a statistics based on conditional mutual information and tested by a permutation procedure. Furthermore, for the existed relations, a statistics based on the difference between general conditional mutual information and linear conditional mutual information is proposed to test the nonlinearity. The significance of the nonlinear test statistics is determined by a bootstrap method based on surrogate data. We investigate the finite sample behavior of the procedure through simulation time series with different dependence structures, including linear and nonlinear relations.

  2. Inferring connectivity in networked dynamical systems: Challenges using Granger causality

    Science.gov (United States)

    Lusch, Bethany; Maia, Pedro D.; Kutz, J. Nathan

    2016-09-01

    Determining the interactions and causal relationships between nodes in an unknown networked dynamical system from measurement data alone is a challenging, contemporary task across the physical, biological, and engineering sciences. Statistical methods, such as the increasingly popular Granger causality, are being broadly applied for data-driven discovery of connectivity in fields from economics to neuroscience. A common version of the algorithm is called pairwise-conditional Granger causality, which we systematically test on data generated from a nonlinear model with known causal network structure. Specifically, we simulate networked systems of Kuramoto oscillators and use the Multivariate Granger Causality Toolbox to discover the underlying coupling structure of the system. We compare the inferred results to the original connectivity for a wide range of parameters such as initial conditions, connection strengths, community structures, and natural frequencies. Our results show a significant systematic disparity between the original and inferred network, unless the true structure is extremely sparse or dense. Specifically, the inferred networks have significant discrepancies in the number of edges and the eigenvalues of the connectivity matrix, demonstrating that they typically generate dynamics which are inconsistent with the ground truth. We provide a detailed account of the dynamics for the Erdős-Rényi network model due to its importance in random graph theory and network science. We conclude that Granger causal methods for inferring network structure are highly suspect and should always be checked against a ground truth model. The results also advocate the need to perform such comparisons with any network inference method since the inferred connectivity results appear to have very little to do with the ground truth system.

  3. Granger Causality Stock Market Networks: Temporal Proximity and Preferential Attachment

    OpenAIRE

    Tom\\'a\\v{s} V\\'yrost; \\v{S}tefan Ly\\'ocsa; Eduard Baum\\"ohl

    2014-01-01

    The structure of return spillovers is examined by constructing Granger causality networks using daily closing prices of 20 developed markets from 2nd January 2006 to 31st December 2013. The data is properly aligned to take into account non-synchronous trading effects. The study of the resulting networks of over 94 sub-samples revealed three significant findings. First, after the recent financial crisis the impact of the US stock market has declined. Second, spatial probit models confirmed the...

  4. On the Inference of Functional Circadian Networks Using Granger Causality.

    Science.gov (United States)

    Pourzanjani, Arya; Herzog, Erik D; Petzold, Linda R

    2015-01-01

    Being able to infer one way direct connections in an oscillatory network such as the suprachiastmatic nucleus (SCN) of the mammalian brain using time series data is difficult but crucial to understanding network dynamics. Although techniques have been developed for inferring networks from time series data, there have been no attempts to adapt these techniques to infer directional connections in oscillatory time series, while accurately distinguishing between direct and indirect connections. In this paper an adaptation of Granger Causality is proposed that allows for inference of circadian networks and oscillatory networks in general called Adaptive Frequency Granger Causality (AFGC). Additionally, an extension of this method is proposed to infer networks with large numbers of cells called LASSO AFGC. The method was validated using simulated data from several different networks. For the smaller networks the method was able to identify all one way direct connections without identifying connections that were not present. For larger networks of up to twenty cells the method shows excellent performance in identifying true and false connections; this is quantified by an area-under-the-curve (AUC) 96.88%. We note that this method like other Granger Causality-based methods, is based on the detection of high frequency signals propagating between cell traces. Thus it requires a relatively high sampling rate and a network that can propagate high frequency signals.

  5. A Multivariate Granger Causality Concept towards Full Brain Functional Connectivity.

    Science.gov (United States)

    Schmidt, Christoph; Pester, Britta; Schmid-Hertel, Nicole; Witte, Herbert; Wismüller, Axel; Leistritz, Lutz

    2016-01-01

    Detecting changes of spatially high-resolution functional connectivity patterns in the brain is crucial for improving the fundamental understanding of brain function in both health and disease, yet still poses one of the biggest challenges in computational neuroscience. Currently, classical multivariate Granger Causality analyses of directed interactions between single process components in coupled systems are commonly restricted to spatially low- dimensional data, which requires a pre-selection or aggregation of time series as a preprocessing step. In this paper we propose a new fully multivariate Granger Causality approach with embedded dimension reduction that makes it possible to obtain a representation of functional connectivity for spatially high-dimensional data. The resulting functional connectivity networks may consist of several thousand vertices and thus contain more detailed information compared to connectivity networks obtained from approaches based on particular regions of interest. Our large scale Granger Causality approach is applied to synthetic and resting state fMRI data with a focus on how well network community structure, which represents a functional segmentation of the network, is preserved. It is demonstrated that a number of different community detection algorithms, which utilize a variety of algorithmic strategies and exploit topological features differently, reveal meaningful information on the underlying network module structure.

  6. A Multivariate Granger Causality Concept towards Full Brain Functional Connectivity.

    Directory of Open Access Journals (Sweden)

    Christoph Schmidt

    Full Text Available Detecting changes of spatially high-resolution functional connectivity patterns in the brain is crucial for improving the fundamental understanding of brain function in both health and disease, yet still poses one of the biggest challenges in computational neuroscience. Currently, classical multivariate Granger Causality analyses of directed interactions between single process components in coupled systems are commonly restricted to spatially low- dimensional data, which requires a pre-selection or aggregation of time series as a preprocessing step. In this paper we propose a new fully multivariate Granger Causality approach with embedded dimension reduction that makes it possible to obtain a representation of functional connectivity for spatially high-dimensional data. The resulting functional connectivity networks may consist of several thousand vertices and thus contain more detailed information compared to connectivity networks obtained from approaches based on particular regions of interest. Our large scale Granger Causality approach is applied to synthetic and resting state fMRI data with a focus on how well network community structure, which represents a functional segmentation of the network, is preserved. It is demonstrated that a number of different community detection algorithms, which utilize a variety of algorithmic strategies and exploit topological features differently, reveal meaningful information on the underlying network module structure.

  7. On the Inference of Functional Circadian Networks Using Granger Causality

    Science.gov (United States)

    Pourzanjani, Arya; Herzog, Erik D.; Petzold, Linda R.

    2015-01-01

    Being able to infer one way direct connections in an oscillatory network such as the suprachiastmatic nucleus (SCN) of the mammalian brain using time series data is difficult but crucial to understanding network dynamics. Although techniques have been developed for inferring networks from time series data, there have been no attempts to adapt these techniques to infer directional connections in oscillatory time series, while accurately distinguishing between direct and indirect connections. In this paper an adaptation of Granger Causality is proposed that allows for inference of circadian networks and oscillatory networks in general called Adaptive Frequency Granger Causality (AFGC). Additionally, an extension of this method is proposed to infer networks with large numbers of cells called LASSO AFGC. The method was validated using simulated data from several different networks. For the smaller networks the method was able to identify all one way direct connections without identifying connections that were not present. For larger networks of up to twenty cells the method shows excellent performance in identifying true and false connections; this is quantified by an area-under-the-curve (AUC) 96.88%. We note that this method like other Granger Causality-based methods, is based on the detection of high frequency signals propagating between cell traces. Thus it requires a relatively high sampling rate and a network that can propagate high frequency signals. PMID:26413748

  8. Multivariate Granger Causality Analysis of Obesity Related Variables

    Science.gov (United States)

    Mukhopadhyay, Nitai D; Wheeler, David; Sabo, Roy; Sun, Shumei S

    2015-01-01

    Obesity is a complex health outcome that is a combination of multiple health indicators. Here we attempt to explore the dependence network among multiple aspects of obesity. Two longitudinal cohort studies across multiple decades have been used. The concept of causality is defined similar to Granger causality among multiple time series, however, modified to accommodate multivariate time series as the nodes of the network. Our analysis reveals relatively central position of physical measurements and blood chemistry measures in the overall network across both genders. Also there are some patterns specific to only male or female population. The geometry of the causality network is expected to help in our strategy to control the increasing trend of obesity rate. PMID:26855968

  9. Investigating Driver Fatigue versus Alertness Using the Granger Causality Network

    Science.gov (United States)

    Kong, Wanzeng; Lin, Weicheng; Babiloni, Fabio; Hu, Sanqing; Borghini, Gianluca

    2015-01-01

    Driving fatigue has been identified as one of the main factors affecting drivers’ safety. The aim of this study was to analyze drivers’ different mental states, such as alertness and drowsiness, and find out a neurometric indicator able to detect drivers’ fatigue level in terms of brain networks. Twelve young, healthy subjects were recruited to take part in a driver fatigue experiment under different simulated driving conditions. The Electroencephalogram (EEG) signals of the subjects were recorded during the whole experiment and analyzed by using Granger-Causality-based brain effective networks. It was that the topology of the brain networks and the brain’s ability to integrate information changed when subjects shifted from the alert to the drowsy stage. In particular, there was a significant difference in terms of strength of Granger causality (GC) in the frequency domain and the properties of the brain effective network i.e., causal flow, global efficiency and characteristic path length between such conditions. Also, some changes were more significant over the frontal brain lobes for the alpha frequency band. These findings might be used to detect drivers’ fatigue levels, and as reference work for future studies. PMID:26251909

  10. Investigating Driver Fatigue versus Alertness Using the Granger Causality Network

    Directory of Open Access Journals (Sweden)

    Wanzeng Kong

    2015-08-01

    Full Text Available Driving fatigue has been identified as one of the main factors affecting drivers’ safety. The aim of this study was to analyze drivers’ different mental states, such as alertness and drowsiness, and find out a neurometric indicator able to detect drivers’ fatigue level in terms of brain networks. Twelve young, healthy subjects were recruited to take part in a driver fatigue experiment under different simulated driving conditions. The Electroencephalogram (EEG signals of the subjects were recorded during the whole experiment and analyzed by using Granger-Causality-based brain effective networks. It was that the topology of the brain networks and the brain’s ability to integrate information changed when subjects shifted from the alert to the drowsy stage. In particular, there was a significant difference in terms of strength of Granger causality (GC in the frequency domain and the properties of the brain effective network i.e., causal flow, global efficiency and characteristic path length between such conditions. Also, some changes were more significant over the frontal brain lobes for the alpha frequency band. These findings might be used to detect drivers’ fatigue levels, and as reference work for future studies.

  11. On the methodology of energy-GDP Granger causality tests

    Energy Technology Data Exchange (ETDEWEB)

    Beaudreau, Bernard C. [Department of Economics, Universite Laval, Quebec (Canada)

    2010-09-15

    Despite their growing technical sophistication and empirical breadth, Granger energy-GDP causality tests remain inconclusive, leaving unresolved the increasingly relevant debate over the role of energy or energy growth in economic growth. While historians and growth theorists point to the development of the steam engine, the electromagnetic motor and the ensuing energy deepening as a key contributing factor in economic growth, the existing tests provide little support for this view. This paper examines this debate, focusing particular attention on the underlying methodology, specifically on the measures of energy used. It is argued that existing tests, by regressing GDP growth on current and lagged levels of energy consumption growth, do not capture the essence of the historical record and recent work on energy and development. A new energy metric in the form of energy availability is presented and discussed in detail. (author)

  12. Financial networks based on Granger causality: A case study

    Science.gov (United States)

    Papana, Angeliki; Kyrtsou, Catherine; Kugiumtzis, Dimitris; Diks, Cees

    2017-09-01

    Connectivity analysis is performed on a long financial record of 21 international stock indices employing a linear and a nonlinear causality measure, the conditional Granger causality index (CGCI) and the partial mutual information on mixed embedding (PMIME), respectively. Both measures aim to specify the direction of the interrelationships among the international stock indexes and portray the links of the resulting networks, by the presence of direct couplings between variables exploiting all available information. However, their differences are assessed due to the presence of nonlinearity. The weighted networks formed with respect to the causality measures are transformed to binary ones using a significance test. The financial networks are formed on sliding windows in order to examine the network characteristics and trace changes in the connectivity structure. Subsequently, two statistical network quantities are calculated; the average degree and the average shortest path length. The empirical findings reveal interesting time-varying properties of the constructed network, which are clearly dependent on the nature of the financial cycle.

  13. Immigration, unemployment and GDP in the host country: Bootstrap panel Granger causality analysis on OECD countries

    OpenAIRE

    Boubtane, Ekrame; Rault, C; Coulibaly, Dramane

    2013-01-01

    This paper examines the causality relationship between immigration, unemployment and economic growth of the host country. We employ the panel Granger causality testing approach of Konya (2006) that is based on SUR systems and Wald tests with country specific bootstrap critical values. This approach allows to test for Granger-causality on each individual panel member separately by taking into account the contemporaneous correlation across countries. Using annual data over the 1980-2005 period ...

  14. The opportune time to invest in residential properties - Engle-Granger cointegration test and Granger causality test approach

    Science.gov (United States)

    Chee-Yin, Yip; Hock-Eam, Lim

    2014-12-01

    This paper examines using housing supply as proxy to house prices, the causal relationship on house prices among 8 states in Malaysia by applying the Engle-Granger cointegration test and Granger causality test approach. The target states are Perak, Selangor, Penang, Federal Territory of Kuala Lumpur (WPKL or Kuala Lumpur), Kedah, Negeri Sembilan, Sabah and Sarawak. The primary aim of this study is to estimate how long (in months) house prices in Perak lag behind that of Selangor, Penang and WPKL. We classify the 8 states into two categories - developed and developing states. We use Engle-Granger cointegration test and Granger causality test to examine the long run and short run equilibrium relationship among the two categories.. It is found that the causal relationship is bidirectional in Perak and Sabah, Perak and Selangor while it is unidirectional for Perak and Sarawak, Perak and Penang, Perak and WPKL. The speed of deviation adjustment is about 273%, suggesting that the pricing dynamic of Perak has a 32- month or 2 3/4- year lag behind that of WPKL, Selangor and Penang. Such information will be useful to investors, house buyers and speculators.

  15. A Pitfall in Using the Characterization of Granger Non-Causality in Vector Autoregressive Models

    Directory of Open Access Journals (Sweden)

    Umberto Triacca

    2015-04-01

    Full Text Available It is well known that in a vector autoregressive (VAR model Granger non-causality is characterized by a set of restrictions on the VAR coefficients. This characterization has been derived under the assumption of non-singularity of the covariance matrix of the innovations. This note shows that if this assumption is violated, then the characterization of Granger non-causality in a VAR model fails to hold. In these situations Granger non-causality test results must be interpreted with caution.

  16. The Relation between Granger Causality and Directed Information Theory: A Review

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    Pierre-Olivier Amblard

    2012-12-01

    Full Text Available This report reviews the conceptual and theoretical links between Granger causality and directed information theory. We begin with a short historical tour of Granger causality, concentrating on its closeness to information theory. The definitions of Granger causality based on prediction are recalled, and the importance of the observation set is discussed. We present the definitions based on conditional independence. The notion of instantaneous coupling is included in the definitions. The concept of Granger causality graphs is discussed. We present directed information theory from the perspective of studies of causal influences between stochastic processes. Causal conditioning appears to be the cornerstone for the relation between information theory and Granger causality. In the bivariate case, the fundamental measure is the directed information, which decomposes as the sum of the transfer entropies and a term quantifying instantaneous coupling. We show the decomposition of the mutual information into the sums of the transfer entropies and the instantaneous coupling measure, a relation known for the linear Gaussian case. We study the multivariate case, showing that the useful decomposition is blurred by instantaneous coupling. The links are further developed by studying how measures based on directed information theory naturally emerge from Granger causality inference frameworks as hypothesis testing.

  17. Neural Connectivity in Epilepsy as Measured by Granger Causality

    Science.gov (United States)

    Coben, Robert; Mohammad-Rezazadeh, Iman

    2015-01-01

    Epilepsy is a chronic neurological disorder characterized by repeated seizures or excessive electrical discharges in a group of brain cells. Prevalence rates include about 50 million people worldwide and 10% of all people have at least one seizure at one time in their lives. Connectivity models of epilepsy serve to provide a deeper understanding of the processes that control and regulate seizure activity. These models have received initial support and have included measures of EEG, MEG, and MRI connectivity. Preliminary findings have shown regions of increased connectivity in the immediate regions surrounding the seizure foci and associated low connectivity in nearby regions and pathways. There is also early evidence to suggest that these patterns change during ictal events and that these changes may even by related to the occurrence or triggering of seizure events. We present data showing how Granger causality can be used with EEG data to measure connectivity across brain regions involved in ictal events and their resolution. We have provided two case examples as a demonstration of how to obtain and interpret such data. EEG data of ictal events are processed, converted to independent components and their dipole localizations, and these are used to measure causality and connectivity between these locations. Both examples have shown hypercoupling near the seizure foci and low causality across nearby and associated neuronal pathways. This technique also allows us to track how these measures change over time and during the ictal and post-ictal periods. Areas for further research into this technique, its application to epilepsy, and the formation of more effective therapeutic interventions are recommended. PMID:26236211

  18. A study of industrial electricity consumption based on partial Granger causality network

    Science.gov (United States)

    Yao, Can-Zhong; Lin, Qing-Wen; Lin, Ji-Nan

    2016-11-01

    The paper studies the industrial energy transferring paths among the industries of China by distinguishing direct causality from the indirect. With complementary graphs, we propose that industrial causal relationship can be heterogeneous, and provide insights for refining robust industrial causality framework. First, by analyzing the in-weight and out-weight of the industries in Granger causality networks we find that public utilities have significant causality with other industries, and the industries with higher degree value tend to have stronger causality with others. Further, we eliminate the exogenous links by partial Granger causality model and find both Granger and partial Granger networks have consistent hub industries while some outliers emerge in partial Granger causality networks. Besides, compared with GX, GZ, HN and YN, the correlation between the volume of electricity consumption and the weight of each industry is more significant in the networks of GD and NF. By studying the characteristics of complementary graphs, we show that the industrial energy transferring paths in GD are more multidimensional, and the corresponding interdependent relationship among industries is more robust. Finally, using bootstrap method we verify the reliability of each industrial relationship network. Results exhibit that GD, GX and NF have more reliable causal relationship networks than other provinces, revealing their industrial structure to be more stable.

  19. Economic Growth, Foreign Direct Investment and CO2 Emissions in China: A Panel Granger Causality Analysis

    Directory of Open Access Journals (Sweden)

    Hongfeng Peng

    2016-03-01

    Full Text Available Using a sample of province-level panel data, this paper investigates the Granger causality associations among economic growth (GDP, foreign direct investment (FDI and CO2 emissions in China. By applying the bootstrap Granger panel causality approach (Kónya, 2006, we consider both cross-sectional dependence and homogeneity of different regions in China. The empirical results support that the causality direction not only works in a single direction either from GDP to FDI (in Yunnan or from FDI to GDP (in Beijing, Neimenggu, Jilin, Shanxi and Gansu, but it also works in both directions (in Henan. Moreover, we document that GDP is Granger-causing CO2 emissions in Neimenggu, Hubei, Guangxi and Gansu while there is bidirectional causality between these two variables in Shanxi. In the end, we identify the unidirectional causality from FDI to CO2 emissions in Beijing, Henan, Guizhou and Shanxi, and the bidirectional causality between FDI and CO2 emissions in Neimenggu.

  20. Exploring Granger causality between global average observed time series of carbon dioxide and temperature

    Energy Technology Data Exchange (ETDEWEB)

    Kodra, Evan A [ORNL; Chatterjee, Snigdhansu [University of Minnesota; Ganguly, Auroop R [ORNL

    2010-01-01

    Detection and attribution methodologies have been developed over the years to delineate anthropogenic from natural drivers of climate change and impacts. A majority of prior attribution studies, which have used climate model simulations and observations or reanalysis datasets, have found evidence for humaninduced climate change. This papers tests the hypothesis that Granger causality can be extracted from the bivariate series of globally averaged land surface temperature (GT) observations and observed CO2 in the atmosphere using a reverse cumulative Granger causality test. This proposed extension of the classic Granger causality test is better suited to handle the multisource nature of the data and provides further statistical rigor. The results from this modified test show evidence for Granger causality from a proxy of total radiative forcing (RC), which in this case is a transformation of atmospheric CO2, to GT. Prior literature failed to extract these results via the standard Granger causality test. A forecasting test shows that a holdout set of GT can be better predicted with the addition of lagged RC as a predictor, lending further credibility to the Granger test results. However, since second-order-differenced RC is neither normally distributed nor variance stationary, caution should be exercised in the interpretation of our results.

  1. Detectability of Granger causality for subsampled continuous-time neurophysiological processes.

    Science.gov (United States)

    Barnett, Lionel; Seth, Anil K

    2017-01-01

    Granger causality is well established within the neurosciences for inference of directed functional connectivity from neurophysiological data. These data usually consist of time series which subsample a continuous-time biophysiological process. While it is well known that subsampling can lead to imputation of spurious causal connections where none exist, less is known about the effects of subsampling on the ability to reliably detect causal connections which do exist. We present a theoretical analysis of the effects of subsampling on Granger-causal inference. Neurophysiological processes typically feature signal propagation delays on multiple time scales; accordingly, we base our analysis on a distributed-lag, continuous-time stochastic model, and consider Granger causality in continuous time at finite prediction horizons. Via exact analytical solutions, we identify relationships among sampling frequency, underlying causal time scales and detectability of causalities. We reveal complex interactions between the time scale(s) of neural signal propagation and sampling frequency. We demonstrate that detectability decays exponentially as the sample time interval increases beyond causal delay times, identify detectability "black spots" and "sweet spots", and show that downsampling may potentially improve detectability. We also demonstrate that the invariance of Granger causality under causal, invertible filtering fails at finite prediction horizons, with particular implications for inference of Granger causality from fMRI data. Our analysis emphasises that sampling rates for causal analysis of neurophysiological time series should be informed by domain-specific time scales, and that state-space modelling should be preferred to purely autoregressive modelling. On the basis of a very general model that captures the structure of neurophysiological processes, we are able to help identify confounds, and offer practical insights, for successful detection of causal connectivity

  2. Functional clustering of time series gene expression data by Granger causality

    Science.gov (United States)

    2012-01-01

    Background A common approach for time series gene expression data analysis includes the clustering of genes with similar expression patterns throughout time. Clustered gene expression profiles point to the joint contribution of groups of genes to a particular cellular process. However, since genes belong to intricate networks, other features, besides comparable expression patterns, should provide additional information for the identification of functionally similar genes. Results In this study we perform gene clustering through the identification of Granger causality between and within sets of time series gene expression data. Granger causality is based on the idea that the cause of an event cannot come after its consequence. Conclusions This kind of analysis can be used as a complementary approach for functional clustering, wherein genes would be clustered not solely based on their expression similarity but on their topological proximity built according to the intensity of Granger causality among them. PMID:23107425

  3. Functional clustering of time series gene expression data by Granger causality

    Directory of Open Access Journals (Sweden)

    Fujita André

    2012-10-01

    Full Text Available Abstract Background A common approach for time series gene expression data analysis includes the clustering of genes with similar expression patterns throughout time. Clustered gene expression profiles point to the joint contribution of groups of genes to a particular cellular process. However, since genes belong to intricate networks, other features, besides comparable expression patterns, should provide additional information for the identification of functionally similar genes. Results In this study we perform gene clustering through the identification of Granger causality between and within sets of time series gene expression data. Granger causality is based on the idea that the cause of an event cannot come after its consequence. Conclusions This kind of analysis can be used as a complementary approach for functional clustering, wherein genes would be clustered not solely based on their expression similarity but on their topological proximity built according to the intensity of Granger causality among them.

  4. Granger Causality between Stock Market and Macroeconomic Indicators: Evidence from Germany

    Directory of Open Access Journals (Sweden)

    Tomáš Plíhal

    2016-01-01

    Full Text Available The aim of this paper is to investigate informational efficiency of the stock market in Germany. Granger causality between the stock market and the selected macroeconomic variables is investigated by bivariate analysis using Toda-Yamamoto (1995 approach. This study focuses on monthly data from January 1999 to September 2015, and the stock market is represented by blue chip stock market index DAX. Investigated macroeconomic indicators include industrial production, inflation, money supply, interest rate, trade balance and exchange rate. Stock market Granger-causes industrial production and interest rate, and is therefore leading indicator of these variables. Between money supply and stock prices is Granger causality in both directions. Other variables seem to be independent on development of the stock market. We do not find any violation of Efficient market hypothesis which indicates that the stock market in Germany is informational efficient.

  5. Research on power grid loss prediction model based on Granger causality property of time series

    Energy Technology Data Exchange (ETDEWEB)

    Wang, J. [North China Electric Power Univ., Beijing (China); State Grid Corp., Beijing (China); Yan, W.P.; Yuan, J. [North China Electric Power Univ., Beijing (China); Xu, H.M.; Wang, X.L. [State Grid Information and Telecommunications Corp., Beijing (China)

    2009-03-11

    This paper described a method of predicting power transmission line losses using the Granger causality property of time series. The stable property of the time series was investigated using unit root tests. The Granger causality relationship between line losses and other variables was then determined. Granger-caused time series were then used to create the following 3 prediction models: (1) a model based on line loss binomials that used electricity sales to predict variables, (2) a model that considered both power sales and grid capacity, and (3) a model based on autoregressive distributed lag (ARDL) approaches that incorporated both power sales and the square of power sales as variables. A case study of data from China's electric power grid between 1980 and 2008 was used to evaluate model performance. Results of the study showed that the model error rates ranged between 2.7 and 3.9 percent. 6 refs., 3 tabs., 1 fig.

  6. Granger causality analysis of steady-state electroencephalographic signals during propofol-induced anaesthesia.

    Directory of Open Access Journals (Sweden)

    Adam B Barrett

    Full Text Available Changes in conscious level have been associated with changes in dynamical integration and segregation among distributed brain regions. Recent theoretical developments emphasize changes in directed functional (i.e., causal connectivity as reflected in quantities such as 'integrated information' and 'causal density'. Here we develop and illustrate a rigorous methodology for assessing causal connectivity from electroencephalographic (EEG signals using Granger causality (GC. Our method addresses the challenges of non-stationarity and bias by dividing data into short segments and applying permutation analysis. We apply the method to EEG data obtained from subjects undergoing propofol-induced anaesthesia, with signals source-localized to the anterior and posterior cingulate cortices. We found significant increases in bidirectional GC in most subjects during loss-of-consciousness, especially in the beta and gamma frequency ranges. Corroborating a previous analysis we also found increases in synchrony in these ranges; importantly, the Granger causality analysis showed higher inter-subject consistency than the synchrony analysis. Finally, we validate our method using simulated data generated from a model for which GC values can be analytically derived. In summary, our findings advance the methodology of Granger causality analysis of EEG data and carry implications for integrated information and causal density theories of consciousness.

  7. Inference of biological networks using Bi-directional Random Forest Granger causality.

    Science.gov (United States)

    Furqan, Mohammad Shaheryar; Siyal, Mohammad Yakoob

    2016-01-01

    The standard ordinary least squares based Granger causality is one of the widely used methods for detecting causal interactions between time series data. However, recent developments in technology limit the utilization of some existing implementations due to the availability of high dimensional data. In this paper, we are proposing a technique called Bi-directional Random Forest Granger causality. This technique uses the random forest regularization together with the idea of reusing the time series data by reversing the time stamp to extract more causal information. We have demonstrated the effectiveness of our proposed method by applying it to simulated data and then applied it to two real biological datasets, i.e., fMRI and HeLa cell. fMRI data was used to map brain network involved in deductive reasoning while HeLa cell dataset was used to map gene network involved in cancer.

  8. A study of causality structure and dynamics in industrial electricity consumption based on Granger network

    Science.gov (United States)

    Yao, Can-Zhong; Lin, Ji-Nan; Lin, Qing-Wen; Zheng, Xu-Zhou; Liu, Xiao-Feng

    2016-11-01

    Based on industrial electricity consumption, we model industrial networks by Granger causality method and MST (minimum spanning tree), and then further stick onto an industrial coupling mechanism from energy-consumption perspective. First, we construct Granger causality networks of five provinces in South China of GD, GX, GZ, HN and YN based on their industrial electricity consumption data, and we demonstrate from a network-topology perspective: the distribution of weight of links of all industrial electricity-consumption Granger causality networks approximately follows power-law distribution, revealing a phenomenon that few industries may bring a tremendous influence on the rest. Moreover, correlation analysis between weight and degree of a node shows that in most Granger causality networks, both span and strength of influence of a given industry will significantly increase. Further, we analyze the relationship between the thresholds of Granger causality significance and density of corresponding networks. Results show GD and HN could be classified into a group with relatively greater global differentiation in industries and unbalanced industrial development, however, GX, GZ and YN are grouped as second cluster with relatively balanced industrial development. Furthermore, using Chu-Liu-EdmondsMST algorithm, we extract graphs of MSTs or maximal cliques from industrial electricity-consumption Granger causality networks, and research on energy transmission structure, feedback loop, and bootstrap reliability. By analyzing MSTs, we find that only GD, GX and YN can be extracted with MST graphs, and capture the probable transmission routes of key nodes. Besides we illustrate all three MST graphs are involved with feedback loops structures with various characteristics: GX has complete feed-forward section, feed-back section and feedback loop section; YN has only feed-forward section and feedback loop section; GD has multiple feedback loops section. Finally, we conduct

  9. Attribution of precipitation changes on ground-air temperature offset: Granger causality analysis

    Science.gov (United States)

    Cermak, Vladimir; Bodri, Louise

    2016-06-01

    This work examines the causal relationship between the value of the ground-air temperature offset and the precipitation changes for monitored 5-min data series together with their hourly and daily averages obtained at the Sporilov Geophysical Observatory (Prague). Shallow subsurface soil temperatures were monitored under four different land cover types (bare soil, sand, short-cut grass and asphalt). The ground surface temperature (GST) and surface air temperature (SAT) offset, ΔT(GST-SAT), is defined as the difference between the temperature measured at the depth of 2 cm below the surface and the air temperature measured at 5 cm above the surface. The results of the Granger causality test did not reveal any evidence of Granger causality for precipitation to ground-air temperature offsets on the daily scale of aggregation except for the asphalt pavement. On the contrary, a strong evidence of Granger causality for precipitation to the ground-air temperature offsets was found on the hourly scale of aggregation for all land cover types except for the sand surface cover. All results are sensitive to the lag choice of the autoregressive model. On the whole, obtained results contain valuable information on the delay time of ΔT(GST-SAT) caused by the rainfall events and confirmed the importance of using autoregressive models to understand the ground-air temperature relationship.

  10. The Global Drivers of Photosynthesis and Light Use Efficiency Seasonality: A Granger Frequency Causality Analysis

    Science.gov (United States)

    Nemani, Ramakrishna R.

    2016-01-01

    Photosynthesis and light use efficiency (LUE) are major factors in the evolution of the continental carbon cycle due to their contribution to gross primary production (GPP). However, while the drivers of photosynthesis and LUE on a plant or canopy scale can often be identified, significant uncertainties exist when modeling these on a global scale. This is due to sparse observations in regions such as the tropics and the lack of a direct global observation dataset. Although others have attempted to address this issue using correlations (Beer, 2010) or calculating GPP from vegetation indices (Running, 2004), in this study we take a new approach. We combine the statistical method of Granger frequency causality and partial Granger frequency causality with remote sensing data products (including sun-induced fluorescence used as a proxy for GPP) to determine the main environmental drivers of GPP across the globe.

  11. Inference of Granger causal time-dependent influences in noisy multivariate time series.

    Science.gov (United States)

    Sommerlade, Linda; Thiel, Marco; Platt, Bettina; Plano, Andrea; Riedel, Gernot; Grebogi, Celso; Timmer, Jens; Schelter, Björn

    2012-01-15

    Inferring Granger-causal interactions between processes promises deeper insights into mechanisms underlying network phenomena, e.g. in the neurosciences where the level of connectivity in neural networks is of particular interest. Renormalized partial directed coherence has been introduced as a means to investigate Granger causality in such multivariate systems. A major challenge in estimating respective coherences is a reliable parameter estimation of vector autoregressive processes. We discuss two shortcomings typical in relevant applications, i.e. non-stationarity of the processes generating the time series and contamination with observational noise. To overcome both, we present a new approach by combining renormalized partial directed coherence with state space modeling. A numerical efficient way to perform both the estimation as well as the statistical inference will be presented.

  12. Granger Causality between Stock Market and Macroeconomic Indicators: Evidence from Germany

    OpenAIRE

    Tomáš Plíhal

    2016-01-01

    The aim of this paper is to investigate informational efficiency of the stock market in Germany. Granger causality between the stock market and the selected macroeconomic variables is investigated by bivariate analysis using Toda-Yamamoto (1995) approach. This study focuses on monthly data from January 1999 to September 2015, and the stock market is represented by blue chip stock market index DAX. Investigated macroeconomic indicators include industrial production, inflation, money supply, in...

  13. Granger Causality and National Procurement Spending: Applications to the CC130 Hercules Fleet Performance

    Science.gov (United States)

    2011-09-01

    do not correlate with subsequent CC130 Hercules aircraft performance changes and vice versa. Granger causality tests rep- resent a powerful tool ...confirms the results in [2] and provides the CF with a new tool to help search for relationships in time series data. In our analysis, we found that (R...failures recorded against uninstalled equipment. An Off-A/C form is defined as a CF 349 formwithout an Aircraft number or a CF 543 form. A failure will

  14. Granger causal time-dependent source connectivity in the somatosensory network.

    Science.gov (United States)

    Gao, Lin; Sommerlade, Linda; Coffman, Brian; Zhang, Tongsheng; Stephen, Julia M; Li, Dichen; Wang, Jue; Grebogi, Celso; Schelter, Bjoern

    2015-05-21

    Exploration of transient Granger causal interactions in neural sources of electrophysiological activities provides deeper insights into brain information processing mechanisms. However, the underlying neural patterns are confounded by time-dependent dynamics, non-stationarity and observational noise contamination. Here we investigate transient Granger causal interactions using source time-series of somatosensory evoked magnetoencephalographic (MEG) elicited by air puff stimulation of right index finger and recorded using 306-channel MEG from 21 healthy subjects. A new time-varying connectivity approach, combining renormalised partial directed coherence with state space modelling, is employed to estimate fast changing information flow among the sources. Source analysis confirmed that somatosensory evoked MEG was mainly generated from the contralateral primary somatosensory cortex (SI) and bilateral secondary somatosensory cortices (SII). Transient Granger causality shows a serial processing of somatosensory information, 1) from contralateral SI to contralateral SII, 2) from contralateral SI to ipsilateral SII, 3) from contralateral SII to contralateral SI, and 4) from contralateral SII to ipsilateral SII. These results are consistent with established anatomical connectivity between somatosensory regions and previous source modeling results, thereby providing empirical validation of the time-varying connectivity analysis. We argue that the suggested approach provides novel information regarding transient cortical dynamic connectivity, which previous approaches could not assess.

  15. Granger causal time-dependent source connectivity in the somatosensory network

    Science.gov (United States)

    Gao, Lin; Sommerlade, Linda; Coffman, Brian; Zhang, Tongsheng; Stephen, Julia M.; Li, Dichen; Wang, Jue; Grebogi, Celso; Schelter, Bjoern

    2015-05-01

    Exploration of transient Granger causal interactions in neural sources of electrophysiological activities provides deeper insights into brain information processing mechanisms. However, the underlying neural patterns are confounded by time-dependent dynamics, non-stationarity and observational noise contamination. Here we investigate transient Granger causal interactions using source time-series of somatosensory evoked magnetoencephalographic (MEG) elicited by air puff stimulation of right index finger and recorded using 306-channel MEG from 21 healthy subjects. A new time-varying connectivity approach, combining renormalised partial directed coherence with state space modelling, is employed to estimate fast changing information flow among the sources. Source analysis confirmed that somatosensory evoked MEG was mainly generated from the contralateral primary somatosensory cortex (SI) and bilateral secondary somatosensory cortices (SII). Transient Granger causality shows a serial processing of somatosensory information, 1) from contralateral SI to contralateral SII, 2) from contralateral SI to ipsilateral SII, 3) from contralateral SII to contralateral SI, and 4) from contralateral SII to ipsilateral SII. These results are consistent with established anatomical connectivity between somatosensory regions and previous source modeling results, thereby providing empirical validation of the time-varying connectivity analysis. We argue that the suggested approach provides novel information regarding transient cortical dynamic connectivity, which previous approaches could not assess.

  16. A novel extended Granger Causal Model approach demonstrates brain hemispheric differences during face recognition learning.

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    Tian Ge

    2009-11-01

    Full Text Available Two main approaches in exploring causal relationships in biological systems using time-series data are the application of Dynamic Causal model (DCM and Granger Causal model (GCM. These have been extensively applied to brain imaging data and are also readily applicable to a wide range of temporal changes involving genes, proteins or metabolic pathways. However, these two approaches have always been considered to be radically different from each other and therefore used independently. Here we present a novel approach which is an extension of Granger Causal model and also shares the features of the bilinear approximation of Dynamic Causal model. We have first tested the efficacy of the extended GCM by applying it extensively in toy models in both time and frequency domains and then applied it to local field potential recording data collected from in vivo multi-electrode array experiments. We demonstrate face discrimination learning-induced changes in inter- and intra-hemispheric connectivity and in the hemispheric predominance of theta and gamma frequency oscillations in sheep inferotemporal cortex. The results provide the first evidence for connectivity changes between and within left and right inferotemporal cortexes as a result of face recognition learning.

  17. Granger Causality in Multivariate Time Series Using a Time-Ordered Restricted Vector Autoregressive Model

    Science.gov (United States)

    Siggiridou, Elsa; Kugiumtzis, Dimitris

    2016-04-01

    Granger causality has been used for the investigation of the inter-dependence structure of the underlying systems of multi-variate time series. In particular, the direct causal effects are commonly estimated by the conditional Granger causality index (CGCI). In the presence of many observed variables and relatively short time series, CGCI may fail because it is based on vector autoregressive models (VAR) involving a large number of coefficients to be estimated. In this work, the VAR is restricted by a scheme that modifies the recently developed method of backward-in-time selection (BTS) of the lagged variables and the CGCI is combined with BTS. Further, the proposed approach is compared favorably to other restricted VAR representations, such as the top-down strategy, the bottom-up strategy, and the least absolute shrinkage and selection operator (LASSO), in terms of sensitivity and specificity of CGCI. This is shown by using simulations of linear and nonlinear, low and high-dimensional systems and different time series lengths. For nonlinear systems, CGCI from the restricted VAR representations are compared with analogous nonlinear causality indices. Further, CGCI in conjunction with BTS and other restricted VAR representations is applied to multi-channel scalp electroencephalogram (EEG) recordings of epileptic patients containing epileptiform discharges. CGCI on the restricted VAR, and BTS in particular, could track the changes in brain connectivity before, during and after epileptiform discharges, which was not possible using the full VAR representation.

  18. Understanding climate impacts on vegetation using a spatiotemporal non-linear Granger causality framework

    Science.gov (United States)

    Papagiannopoulou, Christina; Decubber, Stijn; Miralles, Diego; Demuzere, Matthias; Dorigo, Wouter; Verhoest, Niko; Waegeman, Willem

    2017-04-01

    Satellite data provide an abundance of information about crucial climatic and environmental variables. These data - consisting of global records, spanning up to 35 years and having the form of multivariate time series with different spatial and temporal resolutions - enable the study of key climate-vegetation interactions. Although methods which are based on correlations and linear models are typically used for this purpose, their assumptions for linearity about the climate-vegetation relationships are too simplistic. Therefore, we adopt a recently proposed non-linear Granger causality analysis [1], in which we incorporate spatial information, concatenating data from neighboring pixels and training a joint model on the combined data. Experimental results based on global data sets show that considering non-linear relationships leads to a higher explained variance of past vegetation dynamics, compared to simple linear models. Our approach consists of several steps. First, we compile an extensive database [1], which includes multiple data sets for land surface temperature, near-surface air temperature, surface radiation, precipitation, snow water equivalents and surface soil moisture. Based on this database, high-level features are constructed and considered as predictors in our machine-learning framework. These high-level features include (de-trended) seasonal anomalies, lagged variables, past cumulative variables, and extreme indices, all calculated based on the raw climatic data. Second, we apply a spatiotemporal non-linear Granger causality framework - in which the linear predictive model is substituted for a non-linear machine learning algorithm - in order to assess which of these predictor variables Granger-cause vegetation dynamics at each 1° pixel. We use the de-trended anomalies of Normalized Difference Vegetation Index (NDVI) to characterize vegetation, being the target variable of our framework. Experimental results indicate that climate strongly (Granger

  19. Multivariate Granger causality between electricity generation, exports, prices and GDP in Malaysia

    Energy Technology Data Exchange (ETDEWEB)

    Lean, Hooi Hooi [Economics Program, School of Social Sciences, Universiti Sains Malaysia (Malaysia); Smyth, Russell [Department of Economics, Monash University (Australia)

    2010-09-15

    This paper employs annual data for Malaysia from 1970 to 2008 to examine the causal relationship between economic growth, electricity generation, exports and prices in a multivariate model. We find that there is unidirectional Granger causality running from economic growth to electricity generation. However, neither the export-led nor handmaiden theories of trade are supported and there is no causal relationship between prices and economic growth. The policy implication of this result is that electricity conservation policies, including efficiency improvement measures and demand management policies, which are designed to reduce the wastage of electricity and curtail generation can be implemented without having an adverse effect on Malaysia's economic growth. (author)

  20. Economic growth and energy consumption revisited. Evidence from linear and nonlinear Granger causality

    Energy Technology Data Exchange (ETDEWEB)

    Chiou-Wei, Song Zan [Department of Managerial Economics, Nan-Hua University, Chia-Yi (China); Chen, Ching-Fu [Department of Transportation and Communication Management Science, National Cheng Kung University, 1, Ta-Hsueh Road, Tainan, 701 (China); Zhu, Zhen [Department of Economics, College of Business, University of Central Oklahoma, Edmon, OK, 43034 (United States)

    2008-11-15

    The relationship between energy consumption and economic growth is considered as an imperative issue in energy economics. Previous studies have ignored the nonlinear behavior which could be caused by structural breaks. In this study, both linear and nonlinear Granger causality tests are applied to examine the causal relationship between energy consumption and economic growth for a sample of Asian newly industrialized countries as well as the U.S. This study finds evidence supporting a neutrality hypothesis for the United States, Thailand, and South Korea. However, empirical evidence on Philippines and Singapore reveals a unidirectional causality running from economic growth to energy consumption while energy consumption may have affected economic growth for Taiwan, Hong Kong, Malaysia and Indonesia. Policy implications are also discussed. (author)

  1. Saving-Economic Growth Nexus In Nigeria, 1970-2007: Granger Causality And Co-Integration Analyses

    Directory of Open Access Journals (Sweden)

    Nurudeen ABU

    2010-05-01

    Full Text Available The controversy surrounding the direction of causality between saving and economic growth motivated this study. The author employed the Granger-causality and co-integration techniques to analyze the relationship between saving and economic growth in Nigeria during the period 1970-2007. The Johansen co-integration test indicates that the variables (economic growth and saving are co-integrated, and that a long-run equilibrium exists between them. In addition, the granger causality test reveals that causality runs from economic growth to saving, implying that economic growth precedes and granger causes saving. Thus, we reject the Solow’s hypothesis that saving precedes economic growth, and accept the Keynesian theory that t is economic growth that leads to higher saving. The author recommends that government and policy makers should employ policies that would accelerate economic growth so as to increase saving.

  2. Granger Causalities Between Interest Rate, Price Level, Money Supply and Real Gdp in the Czech Republic

    Directory of Open Access Journals (Sweden)

    Tomáš Urbanovský

    2017-01-01

    Full Text Available The main aim of this paper is to investigate relationships between selected macroeconomic variables – interest rate, price level, money supply and real GDP – in the Czech Republic in order to find out definite implications of its interactions and give recommendations to macroeconomic policy authorities. Two implemented vector autoregression models with different lag length reached slightly different conclusions. VAR(1 suggests that three pairs of Granger causality exist, in particular between price level and interest rate, between real GDP and interest rate and between real GDP and price level. VAR(2 uncovered two more pairs of Granger causality between money supply and interest rate and between money supply and price level. Despite better prediction power of VAR(2 in case of money supply, low correlation coefficient comprising variable money supply raises doubts about the factual existence of causality between money supply and other variables. However, both models allow forecasting the direction of change in case of variables interest rate and real GDP with the same success rate nearly 82 %. Both VARs also agreed that interest rate could be changed by change of price level and that interest rate could be changed by change of real GDP. These conclusions represent potential recommendations to macroeconomic policy authorities. For the purpose of further research, exchange rate variable will be included in the model instead of interest rate, because effect of interest rate turned out to be limited in times of weakened state of Czech economy.

  3. Granger Causality in Multi-variate Time Series using a Time Ordered Restricted Vector Autoregressive Model

    CERN Document Server

    Siggiridou, Elsa

    2015-01-01

    Granger causality has been used for the investigation of the inter-dependence structure of the underlying systems of multi-variate time series. In particular, the direct causal effects are commonly estimated by the conditional Granger causality index (CGCI). In the presence of many observed variables and relatively short time series, CGCI may fail because it is based on vector autoregressive models (VAR) involving a large number of coefficients to be estimated. In this work, the VAR is restricted by a scheme that modifies the recently developed method of backward-in-time selection (BTS) of the lagged variables and the CGCI is combined with BTS. Further, the proposed approach is compared favorably to other restricted VAR representations, such as the top-down strategy, the bottom-up strategy, and the least absolute shrinkage and selection operator (LASSO), in terms of sensitivity and specificity of CGCI. This is shown by using simulations of linear and nonlinear, low and high-dimensional systems and different t...

  4. Analysis of sampling artifacts on the Granger causality analysis for topology extraction of neuronal dynamics.

    Science.gov (United States)

    Zhou, Douglas; Zhang, Yaoyu; Xiao, Yanyang; Cai, David

    2014-01-01

    Granger causality (GC) is a powerful method for causal inference for time series. In general, the GC value is computed using discrete time series sampled from continuous-time processes with a certain sampling interval length τ, i.e., the GC value is a function of τ. Using the GC analysis for the topology extraction of the simplest integrate-and-fire neuronal network of two neurons, we discuss behaviors of the GC value as a function of τ, which exhibits (i) oscillations, often vanishing at certain finite sampling interval lengths, (ii) the GC vanishes linearly as one uses finer and finer sampling. We show that these sampling effects can occur in both linear and non-linear dynamics: the GC value may vanish in the presence of true causal influence or become non-zero in the absence of causal influence. Without properly taking this issue into account, GC analysis may produce unreliable conclusions about causal influence when applied to empirical data. These sampling artifacts on the GC value greatly complicate the reliability of causal inference using the GC analysis, in general, and the validity of topology reconstruction for networks, in particular. We use idealized linear models to illustrate possible mechanisms underlying these phenomena and to gain insight into the general spectral structures that give rise to these sampling effects. Finally, we present an approach to circumvent these sampling artifacts to obtain reliable GC values.

  5. Analysis of Sampling Artifacts on the Granger Causality Analysis for Topology Extraction of Neuronal Dynamics

    Directory of Open Access Journals (Sweden)

    Douglas eZhou

    2014-07-01

    Full Text Available Granger causality (GC is a powerful method for causal inference for time series. In general, the GC value is computed using discrete time series sampled from continuous-time processes with a certain sampling interval length $tau$, emph{i.e.}, the GC value is a function of $tau$. Using the GC analysis for the topology extraction of the simplest integrate-and-fire neuronal network of two neurons, we discuss behaviors of the GC value as a function of $tau$, which exhibits (i oscillations, often vanishing at certain finite sampling interval lengths, (ii the GC vanishes linearly as one uses finer and finer sampling. We show that these sampling effects can occur in both linear and nonlinear dynamics: the GC value may vanish in the presence of true causal influence or become nonzero in the absence of causal influence. Without properly taking this issue into account, GC analysis may produce unreliable conclusions about causal influence when applied to empirical data. These sampling artifacts on the GC value greatly complicate the reliability of causal inference using the GC analysis, in general, and the validity of topology reconstruction for networks, in particular. We use idealized linear models to illustrate possible mechanisms underlying these phenomena and to gain insight into the general spectral structures that give rise to these sampling effects. Finally, we present an approach to circumvent these sampling artifacts to obtain reliable GC values.

  6. Rural Financial Development and Rural Economic Efficiency Improvement Based on Granger Causality Test

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Based on the co-integration test theory,Financial Interrelation Ratio(FIR),level of financial efficiency(LFE),level of financial development(LFD) and other indices evaluating the rural financial development are selected by Granger Causality Test.The rural loan balance(RLB),rural deposit balance(RDB),total rural output(TRO),fixed assets investment(FAI),Financial Interrelation Ratio(FIR),economic efficiency(EE),level of financial efficiency(LFE),and level of financial development(LFD) in the years 1979-2007 are collected.Graphical method intuitively reflects the development trend and historical track of relevant indices;and Granger Causality Test verifies the relationship between rural financial development level and rural economic efficiency in the years 1979-2007.Result shows that rural financial development level has significant impact on rural economic growth,but rural economic growth has no significant impact on rural financial development;and rural financial development also has insignificant promotion impact on rural economic efficiency.Thus,conclusions are obtained.Although rural financial development has made certain contribution to the development of rural economy,this kind of contribution is only reflected in total quantity,but not efficiency.Therefore,government should further strengthen the promotion function of financial development for economic efficiency,and gradually establish a virtuous circle system for rural finance and economic development.

  7. The Global Drivers of Photosynthesis and Light Use Efficiency Seasonality: A Granger Frequency Causality Analysis

    Science.gov (United States)

    Green, J.; Lee, J. E.; Gentine, P.; Berry, J. A.; Konings, A. G.

    2015-12-01

    hotosynthesis and light use efficiency (LUE) are major factors in the evolution of the continental carbon cycle due to their contribution to gross primary production (GPP). However, while the drivers of photosynthesis and LUE on a plant or canopy scale can often be identified, significant uncertainties exist when modeling these on a global scale. This is due to sparse observations in regions such as the tropics and the lack of a direct global observation dataset. Although others have attempted to address this issue using correlations (Beer, 2010) or calculating GPP from vegetation indices (Running, 2004), in this study we take a new approach. We combine the statistical method of Granger frequency causality and partial Granger frequency causality with remote sensing data products (including sun-induced fluorescence used as a proxy for GPP) to determine the main environmental drivers of GPP across the globe. References:Beer, C., M. Reichstein, E. Tomelleri, P. Ciais, M. Jung, N. Carvalhais, C. Ro¨denbeck, M. Altaf Arain, D. Baldocchi, G. B. Bonan, A. Bondeau, A. Cescatti, G. Lasslop, A. Lindroth, M. Lomas, S. Luyssaert, H. Margolis, K. W. Oleson, O. Roupsard, E. Veenendaal, N. Viovy, C. Williams, I. Woodward, and D. Papale, 2010: Terrestrial Gross Carbon Dioxide Uptake: Global Distribution and Covariation with Climate. doi: 10.1126/science.1184984. Running, S.W., Nemani, R. R., Heinsch, F. A., Zhao, M., Reeves, M., Hashimoto, H., 2004. A Continuous Satellite Derived Measure of Global Terrestrial Primary Production. BioScience 54(6), 547-560.

  8. Electricity supply, employment and real GDP in India: evidence from cointegration and Granger-causality tests

    Energy Technology Data Exchange (ETDEWEB)

    Ghosh, Sajal [Management Development Institute (MDI), Gurgaon, Room No. C - 10, MDI, P.O. Box No. 60, Mehrauli Road, Sukhrali, Gurgaon 122001 (India)], E-mail: sajalg@yahoo.com

    2009-08-15

    This study probes nexus between electricity supply, employment and real GDP for India within a multivariate framework using autoregressive distributed lag (ARDL) bounds testing approach of cointegration. Long-run equilibrium relationship has been established among these variables for the time span 1970-71 to 2005-06. The study further establishes long- and short-run Granger causality running from real GDP and electricity supply to employment without any feedback effect. Thus, growth in real GDP and electricity supply are responsible for the high level of employment in India. The absence of causality running from electricity supply to real GDP implies that electricity demand and supply side measures can be adopted to reduce the wastage of electricity, which would not affect future economic growth of India.

  9. Electricity supply, employment and real GDP in India. Evidence from cointegration and Granger-causality tests

    Energy Technology Data Exchange (ETDEWEB)

    Ghosh, Sajal [Management Development Institute (MDI), Gurgaon, Room No. C - 10, MDI, P.O. Box No. 60, Mehrauli Road, Sukhrali, Gurgaon 122001 (India)

    2009-08-15

    This study probes nexus between electricity supply, employment and real GDP for India within a multivariate framework using autoregressive distributed lag (ARDL) bounds testing approach of cointegration. Long-run equilibrium relationship has been established among these variables for the time span 1970-71 to 2005-06. The study further establishes long- and short-run Granger causality running from real GDP and electricity supply to employment without any feedback effect. Thus, growth in real GDP and electricity supply are responsible for the high level of employment in India. The absence of causality running from electricity supply to real GDP implies that electricity demand and supply side measures can be adopted to reduce the wastage of electricity, which would not affect future economic growth of India. (author)

  10. Identifying interactions in the time and frequency domains in local and global networks - A Granger Causality Approach

    Directory of Open Access Journals (Sweden)

    Guo Shuixia

    2010-06-01

    Full Text Available Abstract Background Reverse-engineering approaches such as Bayesian network inference, ordinary differential equations (ODEs and information theory are widely applied to deriving causal relationships among different elements such as genes, proteins, metabolites, neurons, brain areas and so on, based upon multi-dimensional spatial and temporal data. There are several well-established reverse-engineering approaches to explore causal relationships in a dynamic network, such as ordinary differential equations (ODE, Bayesian networks, information theory and Granger Causality. Results Here we focused on Granger causality both in the time and frequency domain and in local and global networks, and applied our approach to experimental data (genes and proteins. For a small gene network, Granger causality outperformed all the other three approaches mentioned above. A global protein network of 812 proteins was reconstructed, using a novel approach. The obtained results fitted well with known experimental findings and predicted many experimentally testable results. In addition to interactions in the time domain, interactions in the frequency domain were also recovered. Conclusions The results on the proteomic data and gene data confirm that Granger causality is a simple and accurate approach to recover the network structure. Our approach is general and can be easily applied to other types of temporal data.

  11. Credible Granger-Causality Inference with Modest Sample Lengths: A Cross-Sample Validation Approach

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    Richard A. Ashley

    2014-03-01

    Full Text Available Credible Granger-causality analysis appears to require post-sample inference, as it is well-known that in-sample fit can be a poor guide to actual forecasting effectiveness. However, post-sample model testing requires an often-consequential a priori partitioning of the data into an “in-sample” period – purportedly utilized only for model specification/estimation – and a “post-sample” period, purportedly utilized (only at the end of the analysis for model validation/testing purposes. This partitioning is usually infeasible, however, with samples of modest length – e.g., T ≤ 150 – as is common in both quarterly data sets and/or in monthly data sets where institutional arrangements vary over time, simply because there is in such cases insufficient data available to credibly accomplish both purposes separately. A cross-sample validation (CSV testing procedure is proposed below which both eliminates the aforementioned a priori partitioning and which also substantially ameliorates this power versus credibility predicament – preserving most of the power of in-sample testing (by utilizing all of the sample data in the test, while also retaining most of the credibility of post-sample testing (by always basing model forecasts on data not utilized in estimating that particular model’s coefficients. Simulations show that the price paid, in terms of power relative to the in-sample Granger-causality F test, is manageable. An illustrative application is given, to a re-analysis of the Engel andWest [1] study of the causal relationship between macroeconomic fundamentals and the exchange rate; several of their conclusions are changed by our analysis.

  12. Multivariate Autoregressive Modeling and Granger Causality Analysis of Multiple Spike Trains

    Directory of Open Access Journals (Sweden)

    Michael Krumin

    2010-01-01

    Full Text Available Recent years have seen the emergence of microelectrode arrays and optical methods allowing simultaneous recording of spiking activity from populations of neurons in various parts of the nervous system. The analysis of multiple neural spike train data could benefit significantly from existing methods for multivariate time-series analysis which have proven to be very powerful in the modeling and analysis of continuous neural signals like EEG signals. However, those methods have not generally been well adapted to point processes. Here, we use our recent results on correlation distortions in multivariate Linear-Nonlinear-Poisson spiking neuron models to derive generalized Yule-Walker-type equations for fitting ‘‘hidden’’ Multivariate Autoregressive models. We use this new framework to perform Granger causality analysis in order to extract the directed information flow pattern in networks of simulated spiking neurons. We discuss the relative merits and limitations of the new method.

  13. Random forest Granger causality for detection of effective brain connectivity using high-dimensional data.

    Science.gov (United States)

    Furqan, Mohammad Shaheryar; Siyal, Mohammad Yakoob

    2016-03-01

    Studies have shown that the brain functions are not localized to isolated areas and connections but rather depend on the intricate network of connections and regions inside the brain. These networks are commonly analyzed using Granger causality (GC) that utilizes the ordinary least squares (OLS) method for its standard implementation. In the past, several approaches have shown to solve the limitations of OLS by using diverse regularization systems. However, there are still some shortcomings in terms of accuracy, precision, and false discovery rate (FDR). In this paper, we are proposing a new strategy to use Random Forest as a regularization technique for computing GC that will improve these shortcomings. We have demonstrated the effectiveness of our proposed methodology by comparing the results with existing Least absolute shrinkage and selection operator (LASSO), and Elastic-Net regularized implementations of GC using simulated dataset. Later, we have used our proposed approach to map the network involved during deductive reasoning using real StarPlus dataset.

  14. Is Granger causality a viable technique for analyzing fMRI data?

    Directory of Open Access Journals (Sweden)

    Xiaotong Wen

    Full Text Available Multivariate neural data provide the basis for assessing interactions in brain networks. Among myriad connectivity measures, Granger causality (GC has proven to be statistically intuitive, easy to implement, and generate meaningful results. Although its application to functional MRI (fMRI data is increasing, several factors have been identified that appear to hinder its neural interpretability: (a latency differences in hemodynamic response function (HRF across different brain regions, (b low-sampling rates, and (c noise. Recognizing that in basic and clinical neuroscience, it is often the change of a dependent variable (e.g., GC between experimental conditions and between normal and pathology that is of interest, we address the question of whether there exist systematic relationships between GC at the fMRI level and that at the neural level. Simulated neural signals were convolved with a canonical HRF, down-sampled, and noise-added to generate simulated fMRI data. As the coupling parameters in the model were varied, fMRI GC and neural GC were calculated, and their relationship examined. Three main results were found: (1 GC following HRF convolution is a monotonically increasing function of neural GC; (2 this monotonicity can be reliably detected as a positive correlation when realistic fMRI temporal resolution and noise level were used; and (3 although the detectability of monotonicity declined due to the presence of HRF latency differences, substantial recovery of detectability occurred after correcting for latency differences. These results suggest that Granger causality is a viable technique for analyzing fMRI data when the questions are appropriately formulated.

  15. Predicting depression based on dynamic regional connectivity: a windowed Granger causality analysis of MEG recordings.

    Science.gov (United States)

    Lu, Qing; Bi, Kun; Liu, Chu; Luo, Guoping; Tang, Hao; Yao, Zhijian

    2013-10-16

    Abnormal inter-regional causalities can be mapped for the objective diagnosis of various diseases. These inter-regional connectivities are usually calculated over an entire scan and used to characterize the stationary strength of the connections. However, the connectivity within networks may undergo substantial changes during a scan. In this study, we developed an objective depression recognition approach using the dynamic regional interactions that occur in response to sad facial stimuli. The whole time-period magnetoencephalography (MEG) signals from the visual cortex, amygdala, anterior cingulate cortex (ACC) and inferior frontal gyrus (IFG) were separated into sequential time intervals. The Granger causality mapping method was used to identify the pairwise interaction pattern within each time interval. Feature selection was then undertaken within a minimum redundancy-maximum relevance (mRMR) framework. Typical classifiers were utilized to predict those patients who had depression. The overall performances of these classifiers were similar, and the highest classification accuracy rate was 87.5%. The best discriminative performance was obtained when the number of features was within a robust range. The discriminative network pattern obtained through support vector machine (SVM) analyses displayed abnormal causal connectivities that involved the amygdala during the early and late stages. These early and late connections in the amygdala appear to reveal a negative bias to coarse expression information processing and abnormal negative modulation in patients with depression, which may critically affect depression discrimination.

  16. Large-scale Granger causality analysis on resting-state functional MRI

    Science.gov (United States)

    D'Souza, Adora M.; Abidin, Anas Zainul; Leistritz, Lutz; Wismüller, Axel

    2016-03-01

    We demonstrate an approach to measure the information flow between each pair of time series in resting-state functional MRI (fMRI) data of the human brain and subsequently recover its underlying network structure. By integrating dimensionality reduction into predictive time series modeling, large-scale Granger Causality (lsGC) analysis method can reveal directed information flow suggestive of causal influence at an individual voxel level, unlike other multivariate approaches. This method quantifies the influence each voxel time series has on every other voxel time series in a multivariate sense and hence contains information about the underlying dynamics of the whole system, which can be used to reveal functionally connected networks within the brain. To identify such networks, we perform non-metric network clustering, such as accomplished by the Louvain method. We demonstrate the effectiveness of our approach to recover the motor and visual cortex from resting state human brain fMRI data and compare it with the network recovered from a visuomotor stimulation experiment, where the similarity is measured by the Dice Coefficient (DC). The best DC obtained was 0.59 implying a strong agreement between the two networks. In addition, we thoroughly study the effect of dimensionality reduction in lsGC analysis on network recovery. We conclude that our approach is capable of detecting causal influence between time series in a multivariate sense, which can be used to segment functionally connected networks in the resting-state fMRI.

  17. Directed neural connectivity changes in robot-assisted gait training: a partial Granger causality analysis.

    Science.gov (United States)

    Youssofzadeh, Vahab; Zanotto, Damiano; Stegall, Paul; Naeem, Muhammad; Wong-Lin, KongFatt; Agrawal, Sunil K; Prasad, Girijesh

    2014-01-01

    Now-a-days robotic exoskeletons are often used to help in gait training of stroke patients. However, such robotic systems have so far yielded only mixed results in benefiting the clinical population. Therefore, there is a need to investigate how gait learning and de-learning get characterised in brain signals and thus determine neural substrate to focus attention on, possibly, through an appropriate brain-computer interface (BCI). To this end, this paper reports the analysis of EEG data acquired from six healthy individuals undergoing robot-assisted gait training of a new gait pattern. Time-domain partial Granger causality (PGC) method was applied to estimate directed neural connectivity among relevant brain regions. To validate the results, a power spectral density (PSD) analysis was also performed. Results showed a strong causal interaction between lateral motor cortical areas. A frontoparietal connection was found in all robot-assisted training sessions. Following training, a causal "top-down" cognitive control was evidenced, which may indicate plasticity in the connectivity in the respective brain regions.

  18. Environmental responsibility and financial performance nexus in South Africa: panel Granger causality analysis

    Directory of Open Access Journals (Sweden)

    Thomas Adomah Worae

    2017-08-01

    Full Text Available The authors examined environmental responsibility and financial performance nexus of Johannesburg Stock Exchange’s socially responsible investing manufacturing and mining firms during the period of 2008-2014. The study employs annual panel dataset of fourteen manufacturing and mining companies on the index, and Granger causality analysis using Gcause2 Baum’s version. The paper found unidirectional causal relationship between environmental responsibility, measured by emissions intensity and equity returns, and bidirectional causal relationship between emissions intensity and market value of equity deflated by sales at 1% significant levels. Impliedly, improvements in ‘energy efficient technologies’ to reduce fossil energy consumption (prevention activities seem to exhibit value destroying tendencies, while improvements in ‘end-of-pipe’ activities seem to estimate a drive market value of equity deflated by sales and equity returns. The Pesaran CD and Breusch-Pagan LM tests confirmed existence of cross-sectional dependence amongst panel members. The authors tend to support institutional and stakeholder theories.

  19. Granger causality-based synaptic weights estimation for analyzing neuronal networks.

    Science.gov (United States)

    Shao, Pei-Chiang; Huang, Jian-Jia; Shann, Wei-Chang; Yen, Chen-Tung; Tsai, Meng-Li; Yen, Chien-Chang

    2015-06-01

    Granger causality (GC) analysis has emerged as a powerful analytical method for estimating the causal relationship among various types of neural activity data. However, two problems remain not very clear and further researches are needed: (1) The GC measure is designed to be nonnegative in its original form, lacking of the trait for differentiating the effects of excitations and inhibitions between neurons. (2) How is the estimated causality related to the underlying synaptic weights? Based on the GC, we propose a computational algorithm under a best linear predictor assumption for analyzing neuronal networks by estimating the synaptic weights among them. Under this assumption, the GC analysis can be extended to measure both excitatory and inhibitory effects between neurons. The method was examined by three sorts of simulated networks: those with linear, almost linear, and nonlinear network structures. The method was also illustrated to analyze real spike train data from the anterior cingulate cortex (ACC) and the striatum (STR). The results showed, under the quinpirole administration, the significant existence of excitatory effects inside the ACC, excitatory effects from the ACC to the STR, and inhibitory effects inside the STR.

  20. On the dynamics of aggregate output, electricity consumption and exports in Malaysia: Evidence from multivariate Granger causality tests

    Energy Technology Data Exchange (ETDEWEB)

    Lean, Hooi Hooi [Economics Program, School of Social Sciences, Universiti Sains Malaysia (Malaysia); Smyth, Russell [Department of Economics, Monash University, Clayton 3800 (Australia)

    2010-06-15

    This paper employs annual data from 1971 to 2006 to examine the causal relationship between aggregate output, electricity consumption, exports, labor and capital in a multivariate model for Malaysia. We find that there is bidirectional Granger causality running between aggregate output and electricity consumption. The policy implication of this result is that Malaysia should adopt the dual strategy of increasing investment in electricity infrastructure and stepping up electricity conservation policies to reduce unnecessary wastage of electricity, in order to avoid the negative effect of reducing electricity consumption on aggregate output. We also find support for the export-led hypothesis which states Granger causality runs from exports to aggregate output. This result is consistent with Malaysia pursuing a successful export-orientated strategy. (author)

  1. 多维时间序列Granger因果图Markov性%Markov Properties of Multivariate Time Series Granger Causality Graphs

    Institute of Scientific and Technical Information of China (English)

    魏岳嵩

    2014-01-01

    文章利用Granger因果图表示多维时间变量序列间的因果关系,图中的顶点集由序列的各个分量组成,顶点间的有向边表示分量序列间的Granger因果关系,无向边表示分量间的同期因果关系。建立Granger因果图的p-分离准则,研究Granger因果图的Markov性。%In this paper,we use Granger causality graphs to present the causal relationships of sequence of variables of multivariate time series. In the graphs,the component series constitute the vertex set,while the di-rected edges denote the Granger causality relationships and undirected edges correspond to contemporaneous causality relationships. We construct the p-separated criterion and discuss the Markov properties of Grang-er causality graphs.

  2. Development of effective connectivity during own- and other-race face processing: A Granger causality analysis

    Directory of Open Access Journals (Sweden)

    Guifei Zhou

    2016-09-01

    Full Text Available Numerous developmental studies have suggested that other-race effect (ORE in face recognition emerges as early as in infancy and develops steadily throughout childhood. However, there is very limited research on the neural mechanisms underlying this developmental ORE. The present study used Granger causality analysis (GCA to examine the development of children’s cortical networks in processing own- and other-race faces. Children were between 3 to 13 years. An old-new paradigm was used to assess their own- and other-race face recognition with ETG-4000 (Hitachi Medical Co., Japan acquiring functional near infrared spectroscopy (fNIRS data. After preprocessing, for each participant and under each face condition, we obtained the causal map by calculating the weights of causal relations between the time courses of oxy-Hb of each pair of channels using GCA. To investigate further the differential causal connectivity for own-race faces and other-race faces at the group level, a repeated measure analysis of variance (ANOVA was performed on the GCA weights for each pair of channels with the face race task (own-race face vs. other-race face as the within-subject variable and the age as a between-subject factor (continuous variable. We found an age-related increase in functional connectivity, paralleling a similar age-related improvement in behavioral face processing ability. More importantly, we found that the significant differences in neural functional connectivity between the recognition of own-race faces and that of other-race faces were moderated by age. Thus, like the behavioral ORE, the neural ORE emerges early and undergoes a protracted developmental course.

  3. Former Soviet Union oil production and GDP decline: Granger causality and the multi-cycle Hubbert curve

    Energy Technology Data Exchange (ETDEWEB)

    Reynolds, Douglas B. [Oil and Energy Economics, School of Management, University of Alaska Fairbanks (United States); Kolodziej, Marek [Center for Energy and Environmental Studies, Boston University (United States)

    2008-03-15

    This paper discusses the transition of the Former Soviet Union (FSU) within the context of a 1987-1996 Soviet and FSU oil production decline. The conventional explanation of the break-up is that economic inefficiencies and the Cold War defense build-up caused it. Another possible explanation, one that is examined at length here, is that declining oil production was a contributing factor. The econometric analysis suggests that the fall in Soviet and former Soviet GDP in the 1980s and 1990s did not Granger cause the decline in oil production, but the decline in oil production did Granger cause the fall in GDP. Coal and natural gas to GDP relationships show alternative Granger causalities that we would expect to see with oil, but do not. A multi-cycle Hubbert trend that may be used to forecast future FSU oil production is also shown. (author)

  4. Estimation of Relationship between Inflation and Relative Price Variability: Granger Causality and ARDL Modelling Approach

    Directory of Open Access Journals (Sweden)

    Saghir Pervaiz Ghauri

    2017-02-01

    Full Text Available The objective of this research paper is to examine the relationship between relative price variability and inflation by using consumer price index (CPI of Pakistan. The outcomes of the research further divided into food and non-food groups too. The monthly data of CPI was taken from the Pakistan Bureau of Statistics, from August 2001 to July 2011 (with 2000-01 base for 92 composite commodities with 12 sub-groups. We employed the Granger causality testing approach for the evaluation of any possible influence of one indicator to another. In this scenario, it is viable to state that there is a presence of causality and bidirectional feedback between the variables or the two variables are independent. The major issue is to identify a suitable statistical method that enables us to analyze the association among the variables. The findings of this study demonstrated that there is a probable relationship between inflation (DPt and both un-weighted measures of price variability (VPt and SPt for the whole items that have been considered for the analysis. Apart from that, this association also exists between food and non-food categories of CPI basket.

  5. Investigation of acupoint specificity by multivariate granger causality analysis from functional MRI data.

    Science.gov (United States)

    Feng, Yuanyuan; Bai, Lijun; Zhang, Wensheng; Xue, Ting; Ren, Yanshuang; Zhong, Chongguang; Wang, Hu; You, Youbo; Liu, Zhenyu; Dai, Jianping; Liu, Yijun; Tian, Jie

    2011-07-01

    To investigate the acupoint specificity by exploring the effective connectivity patterns of the poststimulus resting brain networks modulated by acupuncture at the PC6, with the same meridian acupoint PC7 and different meridian acupoint GB37. The functional MRI (fMRI) study was performed in 36 healthy right-handed subjects receiving acupuncture at three acupoints, respectively. Due to the sustained effects of acupuncture, a novel experimental paradigm using the nonrepeated event-related (NRER) design was adopted. Psychophysical responses (deqi sensations) were also assessed. Finally, a newly multivariate Granger causality analysis (mGCA) was used to analyze effective connectivity patterns of the resting fMRI data taken following acupuncture at three acupoints. Following acupuncture at PC6, the red nucleus and substantia nigra emerged as central hubs, in comparison with the fusiform gyrus following acupuncture at GB37. Red nucleus was also a target following acupuncture at PC7, but with fewer inputs than those of PC6. In addition, the most important target following acupuncture at PC7 was located at the parahippocampus. Our findings demonstrated that acupuncture at different acupoints may exert heterogeneous modulatory effects on the causal interactions of brain areas during the poststimulus resting state. These preliminary findings provided a clue to elucidate the relatively function-oriented specificity of acupuncture effects. Copyright © 2011 Wiley-Liss, Inc.

  6. Correntropy-based partial directed coherence for testing multivariate Granger causality in nonlinear processes

    Science.gov (United States)

    Kannan, Rohit; Tangirala, Arun K.

    2014-06-01

    Identification of directional influences in multivariate systems is of prime importance in several applications of engineering and sciences such as plant topology reconstruction, fault detection and diagnosis, and neurosciences. A spectrum of related directionality measures, ranging from linear measures such as partial directed coherence (PDC) to nonlinear measures such as transfer entropy, have emerged over the past two decades. The PDC-based technique is simple and effective, but being a linear directionality measure has limited applicability. On the other hand, transfer entropy, despite being a robust nonlinear measure, is computationally intensive and practically implementable only for bivariate processes. The objective of this work is to develop a nonlinear directionality measure, termed as KPDC, that possesses the simplicity of PDC but is still applicable to nonlinear processes. The technique is founded on a nonlinear measure called correntropy, a recently proposed generalized correlation measure. The proposed method is equivalent to constructing PDC in a kernel space where the PDC is estimated using a vector autoregressive model built on correntropy. A consistent estimator of the KPDC is developed and important theoretical results are established. A permutation scheme combined with the sequential Bonferroni procedure is proposed for testing hypothesis on absence of causality. It is demonstrated through several case studies that the proposed methodology effectively detects Granger causality in nonlinear processes.

  7. Attention-dependent modulation of cortical taste circuits revealed by Granger causality with signal-dependent noise.

    Directory of Open Access Journals (Sweden)

    Qiang Luo

    2013-10-01

    Full Text Available We show, for the first time, that in cortical areas, for example the insular, orbitofrontal, and lateral prefrontal cortex, there is signal-dependent noise in the fMRI blood-oxygen level dependent (BOLD time series, with the variance of the noise increasing approximately linearly with the square of the signal. Classical Granger causal models are based on autoregressive models with time invariant covariance structure, and thus do not take this signal-dependent noise into account. To address this limitation, here we describe a Granger causal model with signal-dependent noise, and a novel, likelihood ratio test for causal inferences. We apply this approach to the data from an fMRI study to investigate the source of the top-down attentional control of taste intensity and taste pleasantness processing. The Granger causality with signal-dependent noise analysis reveals effects not identified by classical Granger causal analysis. In particular, there is a top-down effect from the posterior lateral prefrontal cortex to the insular taste cortex during attention to intensity but not to pleasantness, and there is a top-down effect from the anterior and posterior lateral prefrontal cortex to the orbitofrontal cortex during attention to pleasantness but not to intensity. In addition, there is stronger forward effective connectivity from the insular taste cortex to the orbitofrontal cortex during attention to pleasantness than during attention to intensity. These findings indicate the importance of explicitly modeling signal-dependent noise in functional neuroimaging, and reveal some of the processes involved in a biased activation theory of selective attention.

  8. IMPLEMENTING FISCAL OR MONETARY POLICY IN TIME OF CRISIS? RUNNING GRANGER CAUSALITY TO TEST THE PHILLIPS CURVE IN SOME EURO ZONE COUNTRIES

    Directory of Open Access Journals (Sweden)

    Nico Gianluigi

    2014-12-01

    Full Text Available This paper aims to provide empirical evidence about the theoretical relationship between inflation and unemployment in 9 European countries. Based on two major goals for economic policymakers namely, to keep both inflation and unemployment low, we use the ingredients of the Phillips curve to orient fiscal and monetary policies. These policies are prerogative for the achievement of a desirable combination of unemployment and inflation. More in detail, we attempt to address two basic issues. One strand of the study examines the size and sign of the impact of unemployment rate on percentage changes in inflation. In our preferred econometric model, we have made explicit the evidence according to which one unit increase (% in unemployment reduces inflation of roughly 0.73 percent, on average. Next, we turn to the question concerning the causal link between inflation and unemployment and we derive a political framework enables to orient European policymakers in the implementation of either fiscal or monetary policy. In this context, by means of the Granger causality test, we mainly find evidence of a directional causality which runs from inflation to unemployment in 4 out of 9 European countries under analysis. This result implies that political authorities of Austria, Belgium, Germany and Italy should implement monetary policy in order to achieve pre-established targets of unemployment and inflation. In the same context, a directional causality running from unemployment to inflation has been found in France and Cyprus suggesting that a reduction in the unemployment level can be achieved through controlling fiscal policy. However, succeeding in this goal may lead to an increasing demand for goods and services which, in turn, might cause a higher inflation than expected. Finally, while there is no statistical evidence of a causal link between unemployment and inflation in Finland and Greece, a bidirectional causality has been found in Estonia. This

  9. Conditional Granger Causality Analysis of Effective Connectivity during Motor Imagery and Motor Execution in Stroke Patients

    Directory of Open Access Journals (Sweden)

    Li Wang

    2016-01-01

    Full Text Available Aims. Motor imagery has emerged as a promising technique for the improvement of motor function following stroke, but the mechanism of functional network reorganization in patients during this process remains unclear. The aim of this study is to evaluate the cortical motor network patterns of effective connectivity in stroke patients. Methods. Ten stroke patients with right hand hemiplegia and ten normal control subjects were recruited. We applied conditional Granger causality analysis (CGCA to explore and compare the functional connectivity between motor execution and motor imagery. Results. Compared with the normal controls, the patient group showed lower effective connectivity to the primary motor cortex (M1, the premotor cortex (PMC, and the supplementary motor area (SMA in the damaged hemisphere but stronger effective connectivity to the ipsilesional PMC and M1 in the intact hemisphere during motor execution. There were tighter connections in the cortical motor network in the patients than in the controls during motor imagery, and the patients showed more effective connectivity in the intact hemisphere. Conclusions. The increase in effective connectivity suggests that motor imagery enhances core corticocortical interactions, promotes internal interaction in damaged hemispheres in stroke patients, and may facilitate recovery of motor function.

  10. Lexical influences on speech perception: A Granger causality analysis of MEG and EEG source estimates

    Science.gov (United States)

    Gow, David W.; Segawa, Jennifer A.; Ahlfors, Seppo P.; Lin, Fa-Hsuan

    2008-01-01

    Behavioural and functional imaging studies have demonstrated that lexical knowledge influences the categorization of perceptually ambiguous speech sounds. However, methodological and inferential constraints have so far been unable to resolve the question of whether this interaction takes the form of direct top-down influences on perceptual processing, or feedforward convergence during a decision process. We examined top-down lexical influences on the categorization of segments in a /s/−/∫/ continuum presented in different lexical contexts to produce a robust Ganong effect. Using integrated MEG/EEG and MRI data we found that, within a network identified by 40Hz gamma phase locking, activation in the supramarginal gyrus associated with wordform representation influences phonetic processing in the posterior superior temporal gyrus during a period of time associated with lexical processing. This result provides direct evidence that lexical processes influence lower level phonetic perception, and demonstrates the potential value of combining Granger causality analyses and high spatiotemporal resolution multimodal imaging data to explore the functional architecture of cognition. PMID:18703146

  11. Assessing Granger Causality in Electrophysiological Data: Removing the Adverse Effects of Common Signals via Bipolar Derivations.

    Science.gov (United States)

    Trongnetrpunya, Amy; Nandi, Bijurika; Kang, Daesung; Kocsis, Bernat; Schroeder, Charles E; Ding, Mingzhou

    2015-01-01

    Multielectrode voltage data are usually recorded against a common reference. Such data are frequently used without further treatment to assess patterns of functional connectivity between neuronal populations and between brain areas. It is important to note from the outset that such an approach is valid only when the reference electrode is nearly electrically silent. In practice, however, the reference electrode is generally not electrically silent, thereby adding a common signal to the recorded data. Volume conduction further complicates the problem. In this study we demonstrate the adverse effects of common signals on the estimation of Granger causality, which is a statistical measure used to infer synaptic transmission and information flow in neural circuits from multielectrode data. We further test the hypothesis that the problem can be overcome by utilizing bipolar derivations where the difference between two nearby electrodes is taken and treated as a representation of local neural activity. Simulated data generated by a neuronal network model where the connectivity pattern is known were considered first. This was followed by analyzing data from three experimental preparations where a priori predictions regarding the patterns of causal interactions can be made: (1) laminar recordings from the hippocampus of an anesthetized rat during theta rhythm, (2) laminar recordings from V4 of an awake-behaving macaque monkey during alpha rhythm, and (3) ECoG recordings from electrode arrays implanted in the middle temporal lobe and prefrontal cortex of an epilepsy patient during fixation. For both simulation and experimental analysis the results show that bipolar derivations yield the expected connectivity patterns whereas the untreated data (referred to as unipolar signals) do not. In addition, current source density signals, where applicable, yield results that are close to the expected connectivity patterns, whereas the commonly practiced average re-reference method

  12. Assessing Granger causality in electrophysiological data: the importance of bipolar derivations

    Directory of Open Access Journals (Sweden)

    Amy eTrongnetrpunya

    2016-01-01

    Full Text Available Multielectrode voltage data are usually recorded against a common reference. Such data are frequently used without further treatment to assess patterns of functional connectivity between neuronal populations and between brain areas. It is important to note from the outset that such an approach is valid only when the reference electrode is nearly electrically silent. In practice, however, the reference electrode is generally not electrically silent, thereby adding a common signal to the recorded data. Volume conduction further complicates the problem. In this study we demonstrate the adverse effects of common signals on the estimation of Granger causality, which is a statistical measure used to infer synaptic transmission and information flow in neural circuits from multielectrode data. We further test the hypothesis that the problem can be overcome by utilizing bipolar derivations where the difference between two nearby electrodes is taken and treated as a representation of local neural activity. Simulated data generated by a neuronal network model where the connectivity pattern is known were considered first. This was followed by analyzing data from three experimental preparations where a priori predictions regarding the patterns of causal interactions can be made: (1 laminar recordings from the hippocampus of an anesthetized rat during theta rhythm, (2 laminar recordings from V4 of an awake-behaving macaque monkey during alpha rhythm, and (3 ECoG recordings from electrode arrays implanted in the middle temporal lobe and prefrontal cortex of an epilepsy patient during fixation. For both simulation and experimental analysis the results show that bipolar derivations yield the expected connectivity patterns whereas the untreated data (referred to as unipolar signals do not. In addition, current source density signals, where applicable, yield results that are close to the expected connectivity patterns, whereas the commonly practiced average re

  13. Granger因果检验的文献回顾%The Literature Review of Granger Causality Test

    Institute of Scientific and Technical Information of China (English)

    潘慧峰; 袁军

    2016-01-01

    本文首先介绍了Granger因果关系的概念,探讨了其内涵,并将其与哲学意义上的因果关系、经济学意义上的因果关系进行了比较。进一步从统计学数字特征的角度,对均值Granger因果检验、方差Granger因果检验、分位数Granger因果检验;从序列的平稳性角度,对平稳序列和非平稳序列的Granger因果检验;从函数形式的角度,对线性Granger因果检验与非线性Granger因果检验;从数据类型的角度,对时间序列的Granger因果检验和面板数据的Granger 因果检验进行了综述。在每种分类下,给出了定义、常用的检验模型,及其在经济、金融领域的实证研究。文章最后对滞后阶数的选取、信息准则的选取、Granger因果关系与观测频率、Granger因果检验的实施步骤等关键问题进行了深入的探讨。%This article firstly introduces the conception of Granger causality and differences be-tween it and philosophical causality.Then, we review the definitions, testing methods and empiri-cal study in finance and economics fields of Granger causality from four perspectives:the numeri-cal characters of statistics, stationarity of data, Linearity of functions and the structure of da-ta.The numerical characters of statistics include mean, variance, quantile;the stationarity of da-ta include the stationary data and non-stationary data;the linearity of functions include the linear function and non-linear function; the structure of data includes time series and panel data.Final y, we do further studies on the selections of the number of lags, Information criterion, the relationship between the Granger causality and observing frequencies and the procedures of implementing Granger causality test.

  14. Identifying HIV associated neurocognitive disorder using large-scale Granger causality analysis on resting-state functional MRI

    Science.gov (United States)

    DSouza, Adora M.; Abidin, Anas Z.; Leistritz, Lutz; Wismüller, Axel

    2017-02-01

    We investigate the applicability of large-scale Granger Causality (lsGC) for extracting a measure of multivariate information flow between pairs of regional brain activities from resting-state functional MRI (fMRI) and test the effectiveness of these measures for predicting a disease state. Such pairwise multivariate measures of interaction provide high-dimensional representations of connectivity profiles for each subject and are used in a machine learning task to distinguish between healthy controls and individuals presenting with symptoms of HIV Associated Neurocognitive Disorder (HAND). Cognitive impairment in several domains can occur as a result of HIV infection of the central nervous system. The current paradigm for assessing such impairment is through neuropsychological testing. With fMRI data analysis, we aim at non-invasively capturing differences in brain connectivity patterns between healthy subjects and subjects presenting with symptoms of HAND. To classify the extracted interaction patterns among brain regions, we use a prototype-based learning algorithm called Generalized Matrix Learning Vector Quantization (GMLVQ). Our approach to characterize connectivity using lsGC followed by GMLVQ for subsequent classification yields good prediction results with an accuracy of 87% and an area under the ROC curve (AUC) of up to 0.90. We obtain a statistically significant improvement (p<0.01) over a conventional Granger causality approach (accuracy = 0.76, AUC = 0.74). High accuracy and AUC values using our multivariate method to connectivity analysis suggests that our approach is able to better capture changes in interaction patterns between different brain regions when compared to conventional Granger causality analysis known from the literature.

  15. Synergetic and redundant information flow detected by unnormalized Granger causality: application to resting state fMRI.

    Science.gov (United States)

    Stramaglia, Sebastiano; Angelini, Leonardo; Wu, Guorong; Cortes, Jesus M; Faes, Luca; Marinazzo, Daniele

    2016-04-28

    We develop a framework for the analysis of synergy and redundancy in the pattern of information flow between subsystems of a complex network. The presence of redundancy and/or synergy in multivariate time series data renders difficult to estimate the neat flow of information from each driver variable to a given target. We show that adopting an unnormalized definition of Granger causality one may put in evidence redundant multiplets of variables influencing the target by maximizing the total Granger causality to a given target, over all the possible partitions of the set of driving variables. Consequently we introduce a pairwise index of synergy which is zero when two independent sources additively influence the future state of the system, differently from previous definitions of synergy. We report the application of the proposed approach to resting state fMRI data from the Human Connectome Project, showing that redundant pairs of regions arise mainly due to space contiguity and interhemispheric symmetry, whilst synergy occurs mainly between non-homologous pairs of regions in opposite hemispheres. Redundancy and synergy, in healthy resting brains, display characteristic patterns, revealed by the proposed approach. The pairwise synergy index, here introduced, maps the informational character of the system at hand into a weighted complex network: the same approach can be applied to other complex systems whose normal state corresponds to a balance between redundant and synergetic circuits.

  16. Altered connectivity pattern of hubs in default-mode network with Alzheimer's disease: an Granger causality modeling approach.

    Directory of Open Access Journals (Sweden)

    Xiaoyan Miao

    Full Text Available BACKGROUND: Evidences from normal subjects suggest that the default-mode network (DMN has posterior cingulate cortex (PCC, medial prefrontal cortex (MPFC and inferior parietal cortex (IPC as its hubs; meanwhile, these DMN nodes are often found to be abnormally recruited in Alzheimer's disease (AD patients. The issues on how these hubs interact to each other, with the rest nodes of the DMN and the altered pattern of hubs with respect to AD, are still on going discussion for eventual final clarification. PRINCIPAL FINDINGS: To address these issues, we investigated the causal influences between any pair of nodes within the DMN using Granger causality analysis and graph-theoretic methods on resting-state fMRI data of 12 young subjects, 16 old normal controls and 15 AD patients respectively. We found that: (1 PCC/MPFC/IPC, especially the PCC, showed the widest and distinctive causal effects on the DMN dynamics in young group; (2 the pattern of DMN hubs was abnormal in AD patients compared to old control: MPFC and IPC had obvious causal interaction disruption with other nodes; the PCC showed outstanding performance for it was the only region having causal relation with all other nodes significantly; (3 the altered relation between hubs and other DMN nodes held potential as a noninvasive biomarker of AD. CONCLUSIONS: Our study, to the best of our knowledge, is the first to support the hub configuration of the DMN from the perspective of causal relationship, and reveal abnormal pattern of the DMN hubs in AD. Findings from young subjects provide additional evidence for the role of PCC/MPFC/IPC acting as hubs in the DMN. Compared to old control, MPFC and IPC lost their roles as hubs owing to the obvious causal interaction disruption, and PCC was preserved as the only hub showing significant causal relations with all other nodes.

  17. THE GRANGER CAUSALITY TESTS FOR THE FIVE ASEAN COUNTRIES STOCK MARKETS AND MACROECONOMIC VARIABLES DURING AND POST THE 1997 ASIAN FINANCIAL CRISIS

    Directory of Open Access Journals (Sweden)

    Adwin Surja Atmadja

    2005-01-01

    Full Text Available This study seeks to examine the existence of Granger-causality among stock prices indices and macroeconomic variables in five ASEAN countries, Indonesia; Malaysia; the Philippines; Singapore; and Thailand with particular attention to the 1997 Asian financial crisis and period onwards. Using monthly time series data of the countries, a Granger-causality test based on the vector autoregressive (VAR analytical framework was employed to empirically reveal the causality among the variables. This research finds that there were few Granger causalities found between the country's wtock price index and macroeconomic variables. This indicates that the linkages between domestic stock price movements and macroeconomic factors were very. Due to that, the ASEAN stock markets were crelatively unable to efficiently capture changes in economic fundamentals during the observation period in most of the countries in accordance to the literature in emerging stock markets, and that the influence of specific macroeconomic factors on the domestic economies differ across countries. This also implies that the stock markets do not seem to have played a significant role in most countries' economies, and macroeconomic variables are unlikely to be appropriate indicators to predict not only the future behaviour of other macroeconomic variables, but also that of the stock market price indices. Abstract in Bahasa Indonesia : Makalah ini mencoba untuk menganalisis keberadaan Granger-causality antara indeks harga saham dan variabel-variabel ekonomi makro di lima negara ASEAN, yaitu Indonesia; Malaysia; Filipina; Singapore; dan Thailand yang berfokus pada periode terjadinya krisis keuangan Asia pada tahun 1997 dan sesudahnya. Dengan mempergunakan data time series bulanan dari setiap negara tersebut, tes Granger-causality yang didasarkan pada kerangka analisa VAR (vector autoregressive diaplikasikan untuk mengungkap secara empiris hubungan kausal antar variabel. Dari hasil tes

  18. 基于图模型方法的Granger因果性检验∗%Granger Causality Detecting Based on Graphical Modelling

    Institute of Scientific and Technical Information of China (English)

    魏岳嵩

    2016-01-01

    The Granger causality is an important criterion for measuring the dynamic relation-ship among system variables. In this paper, we apply the graphical model method to explore the Granger causal relations among variables. The Granger causality graph is established and its structural identification is investigated based on the conditional mutual information and permutation test. The test statistics is estimated using the correlation integral of chaos theory and its limiting distribution is proved. Finally, the Granger causality among main international stock markets is investigated using the proposed method.%Granger因果性是衡量系统变量间动态关系的重要依据。本文利用图模型方法研究变量间的Granger因果性,建立了Granger因果图。基于条件互信息和置换检验法建立了Granger因果图结构的辨识方法,利用混沌理论中的关联积分估计相应的检验统计量,给出了统计量的渐进分布,并用所给方法研究国际主要股市间的Granger因果关系。

  19. Application of Bootstrap Methods in Investigation of Size of the Granger Causality Test for Integrated VAR Systems

    Directory of Open Access Journals (Sweden)

    Łukasz Lach

    2010-06-01

    Full Text Available This paper examines the size performance of the Toda-Yamamoto testfor Granger causality in the case of trivariate integrated and cointegratedVAR systems. The standard asymptotic distribution theory andthe residual-based bootstrap approach are applied. A variety of typesof distribution of error term is considered. The impact of misspecificationof initial parameters as well as the influence of an increase in samplesize and number of bootstrap replications on size performance ofToda-Yamamoto test statistics is also examined. The results of the conductedsimulation study confirm that standard asymptotic distributiontheory may often cause significant over-rejection. Application of bootstrapmethods usually leads to improvement of size performance of theToda-Yamamoto test. However, in some cases the considered bootstrapmethod also leads to serious size distortion and performs worse thanthe traditional approach based on χ2 distribution.

  20. Disorganization of Equilibrium Directional Interactions in the Brain Motor Network of Parkinson's disease: New Insight of Resting State Analysis Using Granger Causality and Graphical Approach

    OpenAIRE

    Ghasemi, Mahdieh; Mahloojifar, Ali

    2013-01-01

    Parkinson's disease (PD) is a progressive neurological disorder characterized by tremor, rigidity, and slowness of movements. Particular changes related to various pathological attacks in PD could result in causal interactions of the brain network from resting state functional magnetic resonance imaging (rs-fMRI) data. In this paper, we aimed to disclose the network structure of the directed influences over the brain using multivariate Granger causality analysis and graph theory in patients w...

  1. The Linear and Nonlinear Granger Causality between Stock Index Futures and Spot-Based on an Empirical Study of One -minute High Frequency Data%股指期货和现货的线性、非线性Granger 因果关系分析--基于1分钟高频数据的实证研究

    Institute of Scientific and Technical Information of China (English)

    周伟杰; 顾荣宝

    2015-01-01

    By the traditional linear Granger causality test and the nonlinear Granger causality developed by non -parametric test method,the interaction between stock index futures and spot under different periods is studied.The results show that there are linear and nonlinear Granger causality in the entire period of the study.At the beginning period when futures are listed on the stock market,there exists double -way linear Granger causality between stock index futures and spot,and futures show one -way nonlinear Granger causality on spot.In the next different sta-ges,the linear and nonlinear Granger relationship between futures and spot is still significant,but the linear and nonlinear Granger effects of spot on futures are gradually weakened.It shows,as the market continues to deepen, futures play the leading role of price discovery both from linear and nonlinear perspectives.Furthermore,if there is the Granger causality of spot on futures,the linear Granger relationship will be more obvious.%利用传统线性 Granger 因果检验以及最近发展的非线性 Granger 因果非参数 Tn 检验法,对股指期货和现货的互动关系展开研究。结果表明,从研究的整个阶段来看,股指现货和期货之间存在线性和非线性的 Granger 因果关系;在期货上市之初,股指期货与现货互为线性 Granger 因果关系,且只存在期货对现货的非线性 Granger 因果关系;在随后的几个不同阶段内,期货对现货的线性和非线性关系仍然显著,而现货对期货的线性和非线性 Granger 作用逐渐减弱。说明随着市场运行的不断深入,无论从线性还是非线性角度,期货对价格发现起主导作用。进一步发现,若存在股指现货对期货的 Granger 因果关系,现货对期货的线性作用更明显。

  2. Parametric and nonparametric Granger causality testing: Linkages between international stock markets

    NARCIS (Netherlands)

    de Gooijer, J.G.; Sivarajasingham, S.

    2008-01-01

    This study investigates long-term linear and nonlinear causal linkages among eleven stock markets, six industrialized markets and five emerging markets of South-East Asia. We cover the period 1987-2006, taking into account the on-set of the Asian financial crisis of 1997. We first apply a test for t

  3. Hierarchy of neural organization in the embryonic spinal cord: Granger-causality graph analysis of in vivo calcium imaging data.

    Science.gov (United States)

    Fallani, Fabrizio De Vico; Corazzol, Martina; Sternberg, Jenna R; Wyart, Claire; Chavez, Mario

    2015-05-01

    The recent development of genetically encoded calcium indicators enables monitoring in vivo the activity of neuronal populations. Most analysis of these calcium transients relies on linear regression analysis based on the sensory stimulus applied or the behavior observed. To estimate the basic properties of the functional neural circuitry, we propose a network approach to calcium imaging recorded at single cell resolution. Differently from previous analysis based on cross-correlation, we used Granger-causality estimates to infer information propagation between the activities of different neurons. The resulting functional network was then modeled as a directed graph and characterized in terms of connectivity and node centralities. We applied our approach to calcium transients recorded at low frequency (4 Hz) in ventral neurons of the zebrafish spinal cord at the embryonic stage when spontaneous coiling of the tail occurs. Our analysis on population calcium imaging data revealed a strong ipsilateral connectivity and a characteristic hierarchical organization of the network hubs that supported established propagation of activity from rostral to caudal spinal cord. Our method could be used for detecting functional defects in neuronal circuitry during development and pathological conditions.

  4. Granger causality mapping during joint actions reveals evidence for forward models that could overcome sensory-motor delays.

    Directory of Open Access Journals (Sweden)

    Idil Kokal

    Full Text Available Studies investigating joint actions have suggested a central role for the putative mirror neuron system (pMNS because of the close link between perception and action provided by these brain regions [1], [2], [3]. In contrast, our previous functional magnetic resonance imaging (fMRI experiment demonstrated that the BOLD response of the pMNS does not suggest that it directly integrates observed and executed actions during joint actions [4]. To test whether the pMNS might contribute indirectly to the integration process by sending information to brain areas responsible for this integration (integration network, here we used Granger causality mapping (GCM [5]. We explored the directional information flow between the anterior sites of the pMNS and previously identified integrative brain regions. We found that the left BA44 sent more information than it received to both the integration network (left thalamus, right middle occipital gyrus and cerebellum and more posterior nodes of the pMNS (BA2. Thus, during joint actions, two anatomically separate networks therefore seem effectively connected and the information flow is predominantly from anterior to posterior areas of the brain. These findings suggest that the pMNS is involved indirectly in joint actions by transforming observed and executed actions into a common code and is part of a generative model that could predict the future somatosensory and visual consequences of observed and executed actions in order to overcome otherwise inevitable neural delays.

  5. Modelling the rand and commodity prices: A Granger causality and cointegration analysis

    Directory of Open Access Journals (Sweden)

    Xolani Ndlovu

    2014-11-01

    Full Text Available This paper examines the ‘commodity currency’ hypothesis of the Rand, that is, the postulate that the currency moves in line with commodity prices, and analyses the associated causality using nominal data between 1996 and 2010. We address both the short run and long run relationship between commodity prices and exchange rates. We find that while the levels of the series of both assets are difference stationary, they are not cointegrated. Further, we find the two variables are negatively related, with strong and significant causality running from commodity prices to the exchange rate and not vice versa, implying exogeneity in the determination of commodity prices with respect to the nominal exchange rate. The strength of the relationship is significantly weaker than other OECD commodity currencies. We surmise that the relationship is dynamic over time owing to the portfolio-rebalance argument and the Commodity Terms of Trade (CTT effect and, in the absence of an error correction mechanism, this disconnect may be prolonged. For commodity and currency market participants, this implies that while futures and forward commodity prices may be useful leading indicators of future currency movements, the price risk management strategies may need to be recalibrated over time.

  6. La inversión extranjera directa y las exportaciones en Tailandia. Pruebas de causalidad de Granger y equilibrio general Foreign direct inverstment and exports in Thailand. granger's causality tests and general equilibrium

    Directory of Open Access Journals (Sweden)

    De Lombaerde Philippe

    1996-12-01

    Full Text Available Los autores investigan la causalidad entre inversión directa y las exportaciones en el caso de Tailandia, un país caracterizado por un rapido crecimiento económico y de exportaciones, y por sus entradas de capital extranjero relativamente importantes. Sus resultados en prueba de causalidad de Granger contradicen los resultados de un estudio de equilibrio general, utilizando datos sobre la inversión japonesa en Tailandia. Los autores apuntan al riesgo de utilizar una sola metodología y sugieren razones por ambigüedad de los resultados.The authors investigate the FDI -export causality in the case of
    Thailand, a country characterized by rapid economic and exports growth, and relatively important incoming FDI flows , Their results from Granger causality tests contradict with those from a general-equilibrium study using data on Japanese FDI in Thailand. The authors indicate the risk of using single methodologies and suggest reasons for the ambiguous
    results.

  7. LEARNING OF MULTIVARIATE TIME SERIES GRANGER CAUSALITY BASED ON GRAPHICAL MODEL METHODS%多维时间序列Granger因果性的一种图模型学习方法

    Institute of Scientific and Technical Information of China (English)

    魏岳嵩; 田铮

    2011-01-01

    传统的两变量Granger因果分析法容易产生伪因果关系,且不能刻画变量间的同期因果性.利用图模型方法研究多维时间序列变量间Granger因果关系,通过Granger因果图的建立将问题转化为Granger因果图结构的辨识问题,利用局部密度估计法构造相应的辨识统计量,采用bootstrap方法来确定检验统计量的原分布.模拟分析以及对于中国股市间Granger因果关系的研究说明了该方法的有效性.%Traditional two-variable Granger causality analysis method is prone to inducing spurious causal relationship and cannot portray the immediate causal relationship. This paper explores how to use graphical model methods to analyze the Granger causality graphs among components of multivariate time series. Granger causality graphs of time series is presented and the structural identification problem of Granger causality graph is investigated. A statistic based on local density estimator is proposed, and a bootstrap methods is considered for determining the null distribution of the test statistic. The validity of the proposed method is confirmed by simulations analysis and investigating the Granger causal relationships of the China's stock market.

  8. Theta-rhythmic drive between medial septum and hippocampus in slow-wave sleep and microarousal: a Granger causality analysis

    Science.gov (United States)

    Kang, D.; Ding, M.; Topchiy, I.; Shifflett, L.

    2015-01-01

    Medial septum (MS) plays a critical role in controlling the electrical activity of the hippocampus (HIPP). In particular, theta-rhythmic burst firing of MS neurons is thought to drive lasting HIPP theta oscillations in rats during waking motor activity and REM sleep. Less is known about MS-HIPP interactions in nontheta states such as non-REM sleep, in which HIPP theta oscillations are absent but theta-rhythmic burst firing in subsets of MS neurons is preserved. The present study used Granger causality (GC) to examine the interaction patterns between MS and HIPP in slow-wave sleep (SWS, a nontheta state) and during its short interruptions called microarousals (a transient theta state). We found that during SWS, while GC revealed a unidirectional MS→HIPP influence over a wide frequency band (2–12 Hz, maximum: ∼8 Hz), there was no theta peak in the hippocampal power spectra, indicating a lack of theta activity in HIPP. In contrast, during microarousals, theta peaks were seen in both MS and HIPP power spectra and were accompanied by bidirectional GC with MS→HIPP and HIPP→MS theta drives being of equal magnitude. Thus GC in a nontheta state (SWS) vs. a theta state (microarousal) primarily differed in the level of HIPP→MS. The present findings suggest a modification of our understanding of the role of MS as the theta generator in two regards. First, a MS→HIPP theta drive does not necessarily induce theta field oscillations in the hippocampus, as found in SWS. Second, HIPP theta oscillations entail bidirectional theta-rhythmic interactions between MS and HIPP. PMID:26354315

  9. Vector Autoregressive Models and Granger Causality in Time Series Analysis in Nursing Research: Dynamic Changes Among Vital Signs Prior to Cardiorespiratory Instability Events as an Example.

    Science.gov (United States)

    Bose, Eliezer; Hravnak, Marilyn; Sereika, Susan M

    Patients undergoing continuous vital sign monitoring (heart rate [HR], respiratory rate [RR], pulse oximetry [SpO2]) in real time display interrelated vital sign changes during situations of physiological stress. Patterns in this physiological cross-talk could portend impending cardiorespiratory instability (CRI). Vector autoregressive (VAR) modeling with Granger causality tests is one of the most flexible ways to elucidate underlying causal mechanisms in time series data. The purpose of this article is to illustrate the development of patient-specific VAR models using vital sign time series data in a sample of acutely ill, monitored, step-down unit patients and determine their Granger causal dynamics prior to onset of an incident CRI. CRI was defined as vital signs beyond stipulated normality thresholds (HR = 40-140/minute, RR = 8-36/minute, SpO2 time segment prior to onset of first CRI was chosen for time series modeling in 20 patients using a six-step procedure: (a) the uniform time series for each vital sign was assessed for stationarity, (b) appropriate lag was determined using a lag-length selection criteria, (c) the VAR model was constructed, (d) residual autocorrelation was assessed with the Lagrange Multiplier test, (e) stability of the VAR system was checked, and (f) Granger causality was evaluated in the final stable model. The primary cause of incident CRI was low SpO2 (60% of cases), followed by out-of-range RR (30%) and HR (10%). Granger causality testing revealed that change in RR caused change in HR (21%; i.e., RR changed before HR changed) more often than change in HR causing change in RR (15%). Similarly, changes in RR caused changes in SpO2 (15%) more often than changes in SpO2 caused changes in RR (9%). For HR and SpO2, changes in HR causing changes in SpO2 and changes in SpO2 causing changes in HR occurred with equal frequency (18%). Within this sample of acutely ill patients who experienced a CRI event, VAR modeling indicated that RR changes

  10. 向量白回归模型Granger因果图的条件互信息辨识与应用%Identification and application about Granger causality graph of vector autoregressive model using conditional mutual information

    Institute of Scientific and Technical Information of China (English)

    魏岳嵩; 田铮; 陈占寿

    2011-01-01

    Grangerl因果性是衡量系统变量间动态关系的重要依据.传统的两变量Grangerl因果分析法容易产生伪因果关系,且不能刻画变量间的即时因果性.本文利用图模型方法研究时间序列变量间的Grangerl因果关系,建立了时间序列Granger因果图,提出Grangerl因果图的条件互信息辨识方法,利用混沌理论中的关联积分估计条件互信息,统计量的显著性由置换检验确定.仿真结果证实了方法的有效性,并利用该方法研究了空气污染指标以及中国股市间的Grangerl因果关系.%The Granger Causality is an important basis for measuring the dynamic relationships among system vari- ables. Traditional two-variable Granger causality analysis method is prone to inducing spurious causal relationship and can not portray the immediate causal relationship. This paper explores how to use graphical models method to analyze the Granger causal relations among components of multivariate time series. Granger causality graph of time series is presented. The structural identification of Granger causality graph is investigated based on the conditional mutual information. The conditional mutual information is estimated using the correlation integral from chaos theory. The significance of the tested statistics is determined with a permutation test. The validity of the proposed method is confirmed by simulations analysis. The Granger causal relationships of the air pollution index and the China's stock market are investigated using the proposed method.

  11. Granger Causality Test of Urban-rural Income Gap and Employment of Rural Labor Forces——A Case Study of Shouguang City

    Institute of Scientific and Technical Information of China (English)

    2012-01-01

    Taking Shouguang City in Shandong Province as an example, this article researches the mutual relationship between urban-rural income and employment of rural labor forces, and conducting cointegration test and Granger causality test on the variable sequences using statistical data. The results show that the average annual income of rural labor forces influences the income per capita of rural residents, and there is a Granger causality relationship between the income per capita of rural residents and urban employees’ average wage. Engaging in production concerning agriculture, forestry, animal husbandry and fishery makes the total income per capita in rural areas of Shouguang City higher than the average wage of urban residents in Shouguang City, even in Weifang City. The comparative advantage in terms of income causes the city to loose attraction to rural residents in Shouguang City. The comparative advantage drives more rural labor forces in Shouguang City to engage in primary industry, thereby greatly reducing the pressure of employment and transfer of rural labor forces. Finally important following measures are put forward to promote employment and on-the-spot transfer of rural labor forces: vigorously propel agricultural industrialization; increase rural residents’ income; improve the living conditions for rural residents.

  12. Granger causality in integrated GC-MS and LC-MS metabolomics data reveals the interface of primary and secondary metabolism.

    Science.gov (United States)

    Doerfler, Hannes; Lyon, David; Nägele, Thomas; Sun, Xiaoliang; Fragner, Lena; Hadacek, Franz; Egelhofer, Volker; Weckwerth, Wolfram

    2013-06-01

    Metabolomics has emerged as a key technique of modern life sciences in recent years. Two major techniques for metabolomics in the last 10 years are gas chromatography coupled to mass spectrometry (GC-MS) and liquid chromatography coupled to mass spectrometry (LC-MS). Each platform has a specific performance detecting subsets of metabolites. GC-MS in combination with derivatisation has a preference for small polar metabolites covering primary metabolism. In contrast, reversed phase LC-MS covers large hydrophobic metabolites predominant in secondary metabolism. Here, we present an integrative metabolomics platform providing a mean to reveal the interaction of primary and secondary metabolism in plants and other organisms. The strategy combines GC-MS and LC-MS analysis of the same sample, a novel alignment tool MetMAX and a statistical toolbox COVAIN for data integration and linkage of Granger Causality with metabolic modelling. For metabolic modelling we have implemented the combined GC-LC-MS metabolomics data covariance matrix and a stoichiometric matrix of the underlying biochemical reaction network. The changes in biochemical regulation are expressed as differential Jacobian matrices. Applying the Granger causality, a subset of secondary metabolites was detected with significant correlations to primary metabolites such as sugars and amino acids. These metabolic subsets were compiled into a stoichiometric matrix N. Using N the inverse calculation of a differential Jacobian J from metabolomics data was possible. Key points of regulation at the interface of primary and secondary metabolism were identified.

  13. Disorganization of Equilibrium Directional Interactions in the Brain Motor Network of Parkinson's disease: New Insight of Resting State Analysis Using Granger Causality and Graphical Approach.

    Science.gov (United States)

    Ghasemi, Mahdieh; Mahloojifar, Ali

    2013-04-01

    Parkinson's disease (PD) is a progressive neurological disorder characterized by tremor, rigidity, and slowness of movements. Particular changes related to various pathological attacks in PD could result in causal interactions of the brain network from resting state functional magnetic resonance imaging (rs-fMRI) data. In this paper, we aimed to disclose the network structure of the directed influences over the brain using multivariate Granger causality analysis and graph theory in patients with PD as compared with control group. rs-fMRI at rest from 10 PD patients and 10 controls were analyzed. Topological properties of the networks showed that information flow in PD is smaller than that in healthy individuals. We found that there is a balanced local network in healthy control group, including positive pair-wise cross connections between caudate and cerebellum and reciprocal connections between motor cortex and caudate in the left and right hemispheres. The results showed that this local network is disrupted in PD due to disturbance of the interactions in the motor networks. These findings suggested alteration of the functional organization of the brain in the resting state that affects the information transmission from and to other brain regions related to both primary dysfunctions and higher-level cognition impairments in PD. Furthermore, we showed that regions with high degree values could be detected as betweenness centrality nodes. Our results demonstrate that properties of small-world connectivity could also recognize and quantify the characteristics of directed influence brain networks in PD.

  14. A nonlinear Granger causality test between stock returns and investor sentiment for Chinese stock market: a wavelet-based approach

    NARCIS (Netherlands)

    Chu, X.; Wu, C.; Qiu, J.

    2016-01-01

    In this article, we re-examine the causality between the stock returns and investor sentiment in China. The number of net added accounts is used as a proxy for investor sentiment. To mimic the different investment horizons of market participants, we use the wavelet method to decompose stock returns

  15. Automatic search for fMRI connectivity mapping: an alternative to Granger causality testing using formal equivalences among SEM path modeling, VAR, and unified SEM.

    Science.gov (United States)

    Gates, Kathleen M; Molenaar, Peter C M; Hillary, Frank G; Ram, Nilam; Rovine, Michael J

    2010-04-15

    Modeling the relationships among brain regions of interest (ROIs) carries unique potential to explicate how the brain orchestrates information processing. However, hurdles arise when using functional MRI data. Variation in ROI activity contains sequential dependencies and shared influences on synchronized activation. Consequently, both lagged and contemporaneous relationships must be considered for unbiased statistical parameter estimation. Identifying these relationships using a data-driven approach could guide theory-building regarding integrated processing. The present paper demonstrates how the unified SEM attends to both lagged and contemporaneous influences on ROI activity. Additionally, this paper offers an approach akin to Granger causality testing, Lagrange multiplier testing, for statistically identifying directional influence among ROIs and employs this approach using an automatic search procedure to arrive at the optimal model. Rationale for this equivalence is offered by explicating the formal relationships among path modeling, vector autoregression, and unified SEM. When applied to simulated data, biases in estimates which do not consider both lagged and contemporaneous paths become apparent. Finally, the use of unified SEM with the automatic search procedure is applied to an empirical data example.

  16. Using large-scale Granger causality to study changes in brain network properties in the Clinically Isolated Syndrome (CIS) stage of multiple sclerosis

    Science.gov (United States)

    Abidin, Anas Z.; Chockanathan, Udaysankar; DSouza, Adora M.; Inglese, Matilde; Wismüller, Axel

    2017-03-01

    Clinically Isolated Syndrome (CIS) is often considered to be the first neurological episode associated with Multiple sclerosis (MS). At an early stage the inflammatory demyelination occurring in the CNS can manifest as a change in neuronal metabolism, with multiple asymptomatic white matter lesions detected in clinical MRI. Such damage may induce topological changes of brain networks, which can be captured by advanced functional MRI (fMRI) analysis techniques. We test this hypothesis by capturing the effective relationships of 90 brain regions, defined in the Automated Anatomic Labeling (AAL) atlas, using a large-scale Granger Causality (lsGC) framework. The resulting networks are then characterized using graph-theoretic measures that quantify various network topology properties at a global as well as at a local level. We study for differences in these properties in network graphs obtained for 18 subjects (10 male and 8 female, 9 with CIS and 9 healthy controls). Global network properties captured trending differences with modularity and clustering coefficient (pparietal lobe. We conclude that multivariate analysis of fMRI time-series can reveal interesting information about changes occurring in the brain in early stages of MS.

  17. Multivariate Granger causality between electricity consumption, exports and GDP. Evidence from a panel of Middle Eastern countries

    Energy Technology Data Exchange (ETDEWEB)

    Narayan, Paresh Kumar; Smyth, Russell [School of Accounting, Finance and Economics, Deakin University (Australia); Department of Economics, Monash University, 900 Dandenong Road, Caulfield East, Vic. 3145 (Australia)

    2009-01-15

    This paper examines the causal relationship between electricity consumption, exports and gross domestic product (GDP) for a panel of Middle Eastern countries. We find that for the panel as a whole there are statistically significant feedback effects between these variables. A 1 per cent increase in electricity consumption increases GDP by 0.04 per cent, a 1 per cent increase in exports increases GDP by 0.17 per cent and a 1 per cent increase in GDP generates a 0.95 per cent increase in electricity consumption. The policy implications are that for the panel as a whole these countries should invest in electricity infrastructure and step up electricity conservation policies to avoid a reduction in electricity consumption adversely affecting economic growth. Further policy implications are that for the panel as a whole promoting exports, particularly non-oil exports, is a means to promote economic growth and that expansion of exports can be realized without having adverse effects on energy conservation policies. (author)

  18. Multivariate granger causality between electricity consumption, exports and GDP: Evidence from a panel of Middle Eastern countries

    Energy Technology Data Exchange (ETDEWEB)

    Narayan, Paresh Kumar; Smyth, Russell, E-mail: Russell.Smyth@BusEco.monash.edu.au

    2009-01-15

    This paper examines the causal relationship between electricity consumption, exports and gross domestic product (GDP) for a panel of Middle Eastern countries. We find that for the panel as a whole there are statistically significant feedback effects between these variables. A 1 per cent increase in electricity consumption increases GDP by 0.04 per cent, a 1 per cent increase in exports increases GDP by 0.17 per cent and a 1 per cent increase in GDP generates a 0.95 per cent increase in electricity consumption. The policy implications are that for the panel as a whole these countries should invest in electricity infrastructure and step up electricity conservation policies to avoid a reduction in electricity consumption adversely affecting economic growth. Further policy implications are that for the panel as a whole promoting exports, particularly non-oil exports, is a means to promote economic growth and that expansion of exports can be realized without having adverse effects on energy conservation policies.

  19. Altered effective connectivity network of the basal ganglia in low-grade hepatic encephalopathy: a resting-state fMRI study with Granger causality analysis.

    Directory of Open Access Journals (Sweden)

    Rongfeng Qi

    Full Text Available BACKGROUND: The basal ganglia often show abnormal metabolism and intracranial hemodynamics in cirrhotic patients with hepatic encephalopathy (HE. Little is known about how the basal ganglia affect other brain system and is affected by other brain regions in HE. The purpose of this study was to investigate whether the effective connectivity network associated with the basal ganglia is disturbed in HE patients by using resting-state functional magnetic resonance imaging (rs-fMRI. METHODOLOGY/PRINCIPAL FINDINGS: Thirty five low-grade HE patients and thirty five age- and gender- matched healthy controls participated in the rs-fMRI scans. The effective connectivity networks associated with the globus pallidus, the primarily affected region within basal ganglia in HE, were characterized by using the Granger causality analysis and compared between HE patients and healthy controls. Pearson correlation analysis was performed between the abnormal effective connectivity and venous blood ammonia levels and neuropsychological performances of all HE patients. Compared with the healthy controls, patients with low-grade HE demonstrated mutually decreased influence between the globus pallidus and the anterior cingulate cortex (ACC, cuneus, bi-directionally increased influence between the globus pallidus and the precuneus, and either decreased or increased influence from and to the globus pallidus in many other frontal, temporal, parietal gyri, and cerebellum. Pearson correlation analyses revealed that the blood ammonia levels in HE patients negatively correlated with effective connectivity from the globus pallidus to ACC, and positively correlated with that from the globus pallidus to precuneus; and the number connectivity test scores in patients negatively correlated with the effective connectivity from the globus pallidus to ACC, and from superior frontal gyrus to globus pallidus. CONCLUSIONS/SIGNIFICANCE: Low-grade HE patients had disrupted effective

  20. Control over the strength of connections between modules: a double dissociation between stimulus format and task revealed by Granger causality mapping in fMRI

    Science.gov (United States)

    Anderson, Britt; Soliman, Sherif; O’Malley, Shannon; Danckert, James; Besner, Derek

    2015-01-01

    Drawing on theoretical and computational work with the localist dual route reading model and results from behavioral studies, Besner et al. (2011) proposed that the ability to perform tasks that require overriding stimulus-specific defaults (e.g., semantics when naming Arabic numerals, and phonology when evaluating the parity of number words) necessitate the ability to modulate the strength of connections between cognitive modules for lexical representation, semantics, and phonology on a task- and stimulus-specific basis. We used functional magnetic resonance imaging to evaluate this account by assessing changes in functional connectivity while participants performed tasks that did and did not require such stimulus-task default overrides. The occipital region showing the greatest modulation of BOLD signal strength for the two stimulus types was used as the seed region for Granger causality mapping (GCM). Our GCM analysis revealed a region of rostromedial frontal cortex with a crossover interaction. When participants performed tasks that required overriding stimulus type defaults (i.e., parity judgments of number words and naming Arabic numerals) functional connectivity between the occipital region and rostromedial frontal cortex was present. Statistically significant functional connectivity was absent when the tasks were the default for the stimulus type (i.e., parity judgments of Arabic numerals and reading number words). This frontal region (BA 10) has previously been shown to be involved in goal-directed behavior and maintenance of a specific task set. We conclude that overriding stimulus-task defaults requires a modulation of connection strengths between cognitive modules and that the override mechanism predicted from cognitive theory is instantiated by frontal modulation of neural activity of brain regions specialized for sensory processing. PMID:25870571

  1. Control over the Strength of Connections Between Modules: A Double Dissociation Between Stimulus Format and Task Revealed by Granger Causality Mapping in fMRI

    Directory of Open Access Journals (Sweden)

    Britt eAnderson

    2015-03-01

    Full Text Available Drawing on theoretical and computational work with the localist Dual Route reading model and results from behavioral studies, Besner, Moroz, and O'Malley (2011 proposed that the ability to perform tasks that require overriding stimulus-specific defaults (e.g., semantics when naming Arabic numerals, and phonology when evaluating the parity of number words necessitate the ability to modulate the strength of connections between cognitive modules for lexical representation, semantics, and phonology on a task- and stimulus-specific basis. We used fMRI to evaluate this account by assessing changes in functional connectivity while participants performed tasks that did and did not require such stimulus-task default overrides. The occipital region showing the greatest modulation of BOLD signal strength for the two stimulus types was used as the seed region for Granger Causality Mapping (GCM. Our GCM analysis revealed a region of rostromedial frontal cortex with a crossover interaction. When participants performed tasks that required overriding stimulus type defaults (i.e., parity judgments of number words and naming Arabic numerals functional connectivity between the occipital region and rostromedial frontal cortex was present. Statistically significant functional connectivity was absent when the tasks were the default for the stimulus type (i.e., parity judgments of Arabic numerals and reading number words. This frontal region (BA 10 has previously been shown to be involved in goal-directed behaviour and maintenance of a specific task-set. We conclude that overriding stimulus-task defaults requires a modulation of connection strengths between cognitive modules and that the override mechanism predicted from cognitive theory is instantiated by frontal modulation of neural activity of brain regions specialized for sensory processing.

  2. The Electrocorticogram Signal of Seizures Analysis based on Granger Causal Algorithm%基于格兰杰因果算法的癫痫颅内脑电信号分析

    Institute of Scientific and Technical Information of China (English)

    吴林; 彭策

    2013-01-01

    利用格兰杰因果关系(Granger Causality,GC)探究癫痫大脑64通道之间的因果关系变化规律.癫痫失神发作前各个通道之间的因果强度为0.01左右,且两两通道之间均有因果关系,这与正常人大脑0.01~0.02的因果强度及方向相一致.失神发作时大脑左颞、顶区与枕区交界处因果信息强度增大到0.2以上,且信息流由此流出,其余脑区因果关系强度也增大到0.05以上.实验结果表明癫痫失神小发作前整个大脑系统的信息流向是平衡的,而癫痫发作时GC强度和方向均发生改变.%In this paper,it uses Granger causality to explore causality variation before,during,and after seizure onset between 64 channels in brain.Before seizure onset,the causality intensity between channels is about 0.01 and it has causal relationship in pairwise channels; it is consistent with the brain of able-bodied person about 0.01~0.02 GC values and information direction.During seizure attack,the GC intensity is above 0.2 and the causal flow is from junction of left temporal region,parietal region and occipital region to the others as well as the GC values of others is above 0.05.The experimental result indicates that it is balanceable about GC direction and intensity of flow before absence epilepsy small attack and it is changed during seizures.

  3. A Granger Causality Test of Non-performing Loan Ratio Affect to the Banking Industry%不良贷款率对银行业影响的统计关系检验∗

    Institute of Scientific and Technical Information of China (English)

    彭建刚; 邹克; 张倚胜

    2015-01-01

    In the 5% level of significance,non-performing loan ratio exists a one-way granger causality relationship on capital gains rate,net interest margin,and capital adequacy;the deposit loan ratio,liquidi-ty ratio exists a one-way granger causality relationship on non-performing loan ratio;while the granger causality relationship of the provision coverage ratio and non-performing loan ratio are different in different lag.When the non-performing loan ratio rises,commercial banks should not choose a high loan interest rate loan project to achieve its business performance by taking more risk.In the controllable premise of systemic risk,regulators and central banks can implement counter-cyclical adjustment by increasing toler-ance selectively and appropriately,and allowing some commercial banks or business lines to adjust to the provision of capital standards to reduce its pro-cyclical.Commercial banks should pay more attention to the balance between profitability,liquidity,security,while handle the non-performing loan rate of increase ra-tionally.%在5%的显著性水平下,不良贷款率对资本利润率、净利差、资本充足率有单向格兰杰因果关系;而存贷比、流动性比率对不良贷款率有单向格兰杰因果关系;拨备覆盖率与不良贷款率在不同滞后期格兰杰因果关系不同。当不良贷款率上升时,商业银行不应通过承担更高的风险选择高贷款利率的贷款项目以实现其经营绩效;在系统性风险可控的前提下,监管部门和中央银行实施逆周期调整,可适当有选择性地提高容忍度,允许部分商业银行或业务条线调整对资本的计提标准,降低其顺周期性;商业银行应注重盈利性、流动性、安全性之间的平衡,理性对待不良贷款率上升。

  4. Wiener-Granger causality for effective connectivity in the hidden states: Indication from probabilistic causality. Comment on "Foundational perspectives on causality in large-scale brain networks" by M. Mannino and S.L. Bressler

    Science.gov (United States)

    Tang, Wei

    2015-12-01

    Statistics and probability theory have advanced our understanding of random processes widely observed in the physical world. There is a remarkable trend in studying the brain by looking into the stochastic information processing in large-scale brain networks [1,2]. As the review by Mannino and Bressler [3] points out, the probabilistic notion of causality, with its rooted philosophical foundations, represents a revolutionary view on how different parts of the brain interact and integrate to generate function. Specifically, Probabilistic Causality (PC) asserts that a cause should increase the probability of occurrence of its effect, and PC between two brain regions entails that the probability for the activity in one region to occur increases when conditioned on the activity of the other. This definition claims inherent randomness in the causal relationship.

  5. Relationship between China’s Money Supply And Stock Index Based On The Granger Causality Test%我国货币供给与股价指数的Granger因果关系检验

    Institute of Scientific and Technical Information of China (English)

    张振敏; 程志超

    2015-01-01

    The aim of this paper was to reveal the relationship between the money supply and stock price.According to the Granger causality test theory,an empirical research was conducted depending on the data form Chinese stock market.The result showed that there was no clear causal relationship between the money supply and stock prices,which means that the stock market information could not predict the money supply changes effectively.%根据Granger的因果检验理论,以我国的股票市场为研究对象,实证分析货币供给与股价之间的因果关系。研究发现总体上货币供给与股价之间并无明显的因果关系存在,我国的股票市场对于货币供给变动的信息并不是有效的。

  6. Application of Granger Causality and Multiple Regression Analysis in Air Quality Monitoring%改进多元回归分析在空气质量监测的应用

    Institute of Scientific and Technical Information of China (English)

    金江强; 张怀相

    2016-01-01

    为提高空气质量的测量精度,利用各种空气污染物之间的关联性,提出了一种基于空气污染物之间的因果关系来提高空气质量测量精度的算法。首先针对空气污染物的时间序列建立了自回归差分滑动平均模型;然后通过 F统计量检验其格兰杰因果关系;接着利用逐步线性回归模型建立空气污染物之间的定量关系;最后运用实验数据分析并验证了算法的准确性和有效性。%In order to improve the accuracy of measurement of air quality ,this paper proposes an algorithm of improving air quality measurement precision by causality between air pollutants ,based on the contact between the various air pollutants . First of all , autoregressive integrated moving average (AIMA ) model with exogenous variables is established for time series of air pollutants .Secondly ,Granger causality is tested for air pollutants by F‐statistics . Then , stepwise linear regression mode is trained to establish a quantitative relationship in air pollutants which has causal relationship .Finally ,the accuracy and effectiveness of the algorithm has been validated by the analysis of experimental data .

  7. 国际原油价格影响因素实证研究——基于协整分析和格兰杰因果关系检验%Empirical Study on Factors Influencing International Crude Oil Price—Based on Cointegration Test and Granger Causality Test

    Institute of Scientific and Technical Information of China (English)

    缪建营; 李治国

    2011-01-01

    通过ADF检验、协整检验和格兰杰因果关系检验,以1990~2009年的年度数据为样本,对国际原油价格、探明储量、产量、消费量和贸易量5个变量进行实证分析,从计量的角度分析原油价格的影响因素;结果表明:原油价格与原油产量之间存在协整关系,即长期均衡关系;并且得出原油产量是原油价格的格兰杰原因,但原油价格并非原油产量的格兰杰原因。%This paper uses ADF test,cointegration test and Granger causality test to make empirical study on five factors such as international crude oil price,international crude oil reserve,international crude oil output,international crude oil consumption quantity and international crude oil trade quantity based on data of 1990~2009.The results show that crude oil price has cointegration relationship with crude oil production,i.e.long-run equilibrium relationship,and that the crude oil production is the Granger causality of crude oil price,but crude oil price is not the Granger causality of crude oil production.

  8. Causality

    OpenAIRE

    Antonakis, J.

    2015-01-01

    Making correct causal claims is important for research and practice. This article explains what causality is, and how it can be established via experimental design. Because experiments are infeasible in many applied settings, researchers often use "observational" methods to estimate causal models. In these situations, it is likely that model estimates are compromised by endogeneity. The article discusses the conditions that engender endogeneity and methods that can eliminate it.

  9. Heterogeneous neural pathways underlying acupuncture revealed by multivariate granger causality analyses%基于格兰杰因果分析的针刺不同效应阶段中枢神经传导通路研究

    Institute of Scientific and Technical Information of China (English)

    孙传铸; 白丽君; 牛璇; 陈红艳; 陈鹏; 张明; 劳力行

    2014-01-01

    Objectives: Although accumulating evidence has demonstrated a wide range of cortico-subcortical networks underlying acute effects of acupuncture, less is understood regarding how and by what neural pathways these brain areas interact. We have recently proposed that acupuncture is a slow-acting agent and can induce speciifc patterns of dynamic CNS activities. Implicit in this evidence was the prediction that the reconifguration of brain networks underlying both acute and sustained effects of acupuncture may elucidate its overall functional speciifcity.Materials and Methods:We address the idea directly by adopting a non-repeated event-related design paradigm and multivariate Granger causality analysis (mGCA).Results:We found that brain areas were only sparsely causal connected at early acupuncture needling stage, mainly including ascending path from the thalamus as well as top-down control signals from frontal cortices to nociceptive information processing areas. As time prolonged (sustained effect), more extensive regions integrated into a dense, causally interconnected network only following acupuncture at ST36 but not nonacupoint. Additionally, this reorganization of wide brain networks seemed to be evolved from the resting state.Conclusions:These findings highlighted that the specific effect of acupuncture may involve the integration of recurrent information lfow among multi-levels of brain networks.%目的:探讨针刺不同效应阶段是否会引发中枢神经信号不同的传导通路。材料与方法采用非重复事件相关的实验设计模式和多元格兰杰因果有效连接度分析方法。结果研究表明针刺即时效应仅引发大脑微弱、稀疏的因果有效连接,包括经丘脑的体感上行传导通路与由额叶皮层投射到疼痛反应区的自上而下的控制通路。持续性效应阶段,仅在针刺足三里穴后会引发广泛大脑区域的更为紧密的因果连接模式。结论针刺效应可能涉及大

  10. Causality

    Science.gov (United States)

    Pearl, Judea

    2000-03-01

    Written by one of the pre-eminent researchers in the field, this book provides a comprehensive exposition of modern analysis of causation. It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, philosophy, cognitive science, and the health and social sciences. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artifical intelligence, business, epidemiology, social science and economics. Students in these areas will find natural models, simple identification procedures, and precise mathematical definitions of causal concepts that traditional texts have tended to evade or make unduly complicated. This book will be of interest to professionals and students in a wide variety of fields. Anyone who wishes to elucidate meaningful relationships from data, predict effects of actions and policies, assess explanations of reported events, or form theories of causal understanding and causal speech will find this book stimulating and invaluable.

  11. 管理者过度自信对企业风险的影响——基于面板数据的格兰杰因果关系检验%Study on Impact of Managerial Overconfidence on Enterprise's Risk: Granger Causality Test Based on Panel Data

    Institute of Scientific and Technical Information of China (English)

    庄平; 李延喜

    2011-01-01

    选取管理者过度自信和企业风险的代理变量,利用2002-2009年我国上市公司的面板数据,通过单位根检验和格兰杰因果关系检验,研究管理者过度自信对企业风险的影响.结果表明,管理者过度自信是企业风险的格兰杰原因,且管理者过度自信引发的企业风险在管理者过度自信滞后的第二个经营年度表现显著;企业风险不是管理者过度自信的格兰杰原因.%Using the panel data of listed companies in China during 2002-2009, this paper selects the proxy variables of managerial overconfi-dence and enterprise's risk,and studies the relationship between managerial overconfidence and enterprise's risk through Granger causality test and unit root test. The empirical result shows that managerial overconfidence is the Granger cause of enterprise's risk, and enterprise's risk caused by managerial overconfidence is significantly shown in the second operation year because of the lag of overconfidence of manager, while enterprise's risk is not the Granger cause of managerial Overconfidence.

  12. 基于格兰杰因果关系检验的我国银行保险退保因素分析%Factor Analysis of the Surrender in Bancassurance in China---Based on Granger Causality Test

    Institute of Scientific and Technical Information of China (English)

    邹亚宝; 陈戈

    2014-01-01

    Due to the insufficient funds in bancassurance,this article analyze the market factors which affects the surrender of bancassurance product. Using Granger Causality Test,we domonstrate the hypothesis of“financial crisis”and“interest rate substitute”. It concluded that the volatility in short - term interest rates has not remarkable effect on the surrender of bancassurance product,while volatility in long - term interest rates has remarkable effect on it. Unemployment only affects the surrender of bancassurance product in the short term,and the fluctuation of portfolio investment takes an important role in it significantly. In order to bring down the surrender rate in our coun-try,the first thing we should do is to deepen the cooperation mechanism between the bank and insurance company. Besides,increasing the rate of return,offering bancassurance products properly and adding the risk - averting func-tion are proper methods to reduce the influence of market factors.%我国银行保险内存不足。通过格兰杰因果关系检验对“财务危机”和“利率替代”两种假说进行实证检验后得出:短期利率波动对银行保险退保影响不显著,长期利率波动对银行保险退保影响较显著,失业对银行保险退保短期影响较显著,证券投资波动对银行保险退保影响最为显著。为了降低我国银行保险的退保率,要深化银保合作机制,为了降低市场因素带来的影响,可适当提高银保产品的收益率,银保产品不要过于理财化,可适当增加一些保障功能。

  13. 浙江省科技经费投入与经济增长关系的研究%Study on Relationship between Sci-Tech Funds Input and Economic Growth Based on Granger Causality Test-taking an Example of Zhejiang Province

    Institute of Scientific and Technical Information of China (English)

    孟庆军; 王效敏

    2013-01-01

    研究采用格兰杰因果检验方法,对浙江省1990-2011年度研究与试验发展经费支出、大中型工业企业科技活动经费支出以及高等学校科技活动经费支出的统计,进行科技经费投入与经济增长之间关系的实证分析。研究结果显示,总体上,浙江省科技经费投入与经济增长之间存在着明显的格兰杰因果关系,并构成了稳定的均衡关系。长期来看,大中型工业企业科技经费投入与经济增长之间不存在明显的格兰杰因果关系。经济增长对科技经费投入基本不存在单项的格兰杰因果关系,经济的增长需要投入更多的科技经费,但同时不能忽视经费投入效率。%Adopting Grainger causality test, this study conducts the research on the relationship between sci-tech input and economic growth based on Zhejiang province through using the 1990-2011 annual statistical data, which put the research and experimental development expenditures, medium-sized industrial enterprises expenditures in scientiifc and technological activities and college technological activities expenditures as a co-integration object. hTe results show that, on the whole, there is a clear Granger causality between science and technology funding and economic growth of Zhejiang province, and constitute a stable equilibrium relationship. In the long term, there is no obvious granger causality between medium-sized industrial enterprises expenditures in science and technology funds and economic growth. Single granger causality between economic growth and science and technology fund does not exist. Based on research, we make an conclusion that the government need to put more science and technology funds, but at the same time, they cannot ignore the effciency of funding.

  14. FDI, Export and Regional Economic Growth An Application of Heterogeneous Panel Granger Causality Test%FDI、出口与区域经济增长——异质面板"格兰杰"因果检验的应用

    Institute of Scientific and Technical Information of China (English)

    雷欣; 陈继勇

    2012-01-01

    本文运用基于滞后增广向量自回归(LA.VAR)模型和Bootstrap的异质面板“格兰杰”因果检验方法,对中国1987~2010年的省际面板数据进行实证分析,检验外商直接投资(FDI)、出口和经济增长的关系。结果显示,总体上看,FDI、出口和经济增长两两之间存在异质双向因果关系;分开来看,仅有19个省区存在至少一个方向的因果关系,其中84%的省区位于中西部地区。在短期内,中西部地区外商直接投资、出口与经济增长的关系更为紧密。本文的政策涵义是,对部分中西部省区而言,仍有必要扩大招商引资或出口的规模,但对于东部发达地区而言,优化外商直接投资和出口贸易的结构,才是发挥对外开放促进长期经济增长潜力的关键。%This article uses Granger Causality test for heterogeneous panel data which is based on LAVAR model and Bootstrap as well as China's provinces data from 1987 to 2010 to check the relationships among FDI,Export and economic growth. This article is organized as follows: the firstsection is introduction and research reviews; the second section demonstrates the empirical method and data; the third sectionreports the empirical results; the last section orovides some conclusions and oolicv recommendations. The differences of this article include as follows : ( 1 ) Compared with previous studies based on time series data, this article uses the Chinese provincial panel data and constructs a panel VAR model which includes the three variables of FDI, export and economic growth. In order to improve the validity of statistical inference and the accu racy of Granger causality test, we utilize Bootstrap sampling technique to control the crosssection correlation among the provinces; (2) compared with previous studies based onhomogeneous panel VAR model, this article constructs a heterogeneous panel VAR model and causality test method

  15. Does electricity consumption panel Granger cause GDP? A new global evidence

    Energy Technology Data Exchange (ETDEWEB)

    Narayan, Paresh Kumar [School of Accounting, Economics and Finance, Faculty of Business and Economics, Deakin University, Melbourne (Australia); Narayan, Seema [School of Economics, Finance, and Marketing, RMIT University, Melbourne (Australia); Popp, Stephan [Department of Economics, University of Duisburg-Essen (Germany)

    2010-10-15

    The goal of this paper is to undertake a panel data investigation of long-run Granger causality between electricity consumption and real GDP for seven panels, which together consist of 93 countries. We use a new panel causality test and find that in the long-run both electricity consumption and real GDP have a bidirectional Granger causality relationship except for the Middle East where causality runs only from GDP to electricity consumption. Finally, for the G6 panel the estimates reveal a negative sign effect, implying that increasing electricity consumption in the six most industrialised nations will reduce GDP. (author)

  16. Carbon Emissions and Economic Growth: Causality Testing in Heterogenous Panels

    Energy Technology Data Exchange (ETDEWEB)

    David Maddison; Katrin Rehdanz [Department of Economics, University of Birmingham, Birmingham (United Kingdom)

    2008-09-30

    Numerous papers have examined data on energy and GDP for evidence of Granger causality. Using time series techniques these analyses not infrequently reach differing conclusions concerning the existence and direction of Granger causality. This paper presents a heterogenous panel approach to Granger causality testing. This technique is used to examine a panel of data for evidence of a causal relationship between GDP and carbon emissions per capita allowing for heterogeneity in short run dynamics and even the long run cointegrating vector. This technique is compared to the standard fixed dynamic effects approach to pooling individual error correction models. In one important case the heterogenous panel test for Granger causality reaches conclusions quite different to those from conventional tests of Granger causality. Except for Asia there is strong evidence for the existence of a bidirectional causal relationship between GDP per capita and CO{sub 2} emissions per capita.

  17. Study the Nonlinear Granger Causality between CPI and PPI---Based on Shenzhen's Monthly Data%CPI与PPI的非线性Granger因果关系研究--基于深圳市月度数据的实证分析

    Institute of Scientific and Technical Information of China (English)

    黄智淋

    2014-01-01

    Based on Shenzhen's CPI and PPI from January 2005 to December 2013, this paper investigates the nonlinear relationship between CPI and PPI by using nonlinear Granger causality test , then dynamic analyzes the nonlinear relationship between CPI and PPI at different period by using step-test procedure. The results of nonlinear Granger causality test indicate that there exists a unidirectional nonlinear Granger causality from PPI to CPI during the sample period. What's more , step-test shows that PPI is the nonlinear Granger causality of CPI. This suggests that the supply side factors have played a more important role than demand side factors in CPI inflation, and implies that price rise of upstream factors of production will lead to increase in downstream consumer prices, then result in enlarge the pressures of cost-push inflation. Therefore, we'd better consider the supply side for inflation control and adopt macro-control policies according to the dynamic relationship between CPI and PPI.%文章基于深圳市2005年1月至2013年12月的居民消费价格指数(CPI)和工业生产者出厂价格指数(PPI),运用非线性Granger因果关系检验,从非线性的角度考察深圳市的CPI与PPI之间的作用关系,并采用逐步检验方法对CPI与PPI之间在不同时期的作用关系进行动态分析。非线性Granger因果关系检验的结果表明,在所考察的样本时期内,存在着由PPI到CPI的单向非线性Granger因果关系。逐步检验则进一步显示, PPI是引起CPI变化的非线性Granger因果原因。这说明供给因素在以CPI衡量的通货膨胀中占优于需求因素,也意味着上游生产要素的价格上涨将传导至下游消费品的价格,以致加大了成本推动通货膨胀的压力。因此,治理通货膨胀应采取以供给调控为主的政策,并适时适度地根据CPI与PPI之间的动态关系进行宏观调控。

  18. 蚕茧价格、蚕种饲养量与蚕药用量关系的格兰杰因果检验%Granger Causality Test of Relationship Among Cocoon Price, Amount of Silkworm Eggs Distributed and Usage of Silkworm Drugs

    Institute of Scientific and Technical Information of China (English)

    康国平; 谭书生; 章建华; 郭锡杰

    2011-01-01

    Studying the relationship among three variables, namely cocoon price (CAP), amount of silkworm eggs distributed (SSQ) and usage of silkworm drugs (SMQ), will help to scientifically predict the economic development regularity of sericultural industry. Granger causality test method was employed to conduct stationary test, first-oder difference of variables and unit root test, and Granger causality test to the above three variables based on the annual data of Haian County, Jiangsu Province from 1991 to 2009. The results showed that there was a Granger causality relationship between cocoon price and amount of silkworm eggs distributed and between amount of silkworm eggs distributed and usage of silkworm drugs. There was no Granger causality relationship between cocoon price and usage of silkworm drugs. That is to say, the rise of cocoon price can lead to the increase of amount of silkworm eggs distributed, but the increase of a-mount of silkworm eggs distributed is not the cause of cocoon price rise. The lag phase of cocoon price's impact on a-mount of silkworm eggs distributed was two years, and the influence degree was gradually weakened in the third year. The increase of amount of silkworm eggs distributed could cause the increase of usage of silkworm drugs, but the lag phase of impact was just one year. The influence degree was not significant after one year. Judged from the practical trend, there was some relevance between cocoon price and usage of silkworm drugs. However, it was difficult to establish a functional relationship because the influ-ence was indirect. These investigation results were in general agreement with the actual situation of development and change of sericultural industry, verifying that Granger causality test method is applicable in studying the development regularity of relative factors in sericultural industry and economy.%研究蚕桑产业经济中蚕茧价格(CAP)、蚕种饲养量(简称发种量,SSQ)、蚕药用量(SMQ)3个变量之

  19. 从双边市场角度看证券交易所竞争力的提高——基于上海证券交易所数据的协整检验和格兰特因果检验%Study on the Improvement of Stock Exchanges' Competitiveness from the View of the Theory of Two-sided Markets——Based on the Granger causality test of data from Shanghai Stock Exchange

    Institute of Scientific and Technical Information of China (English)

    陈薪宇; 潘小军

    2012-01-01

    证券交易所是资本市场的载体,其竞争力水平影响本国的证券市场运行效率,定价是证券交易所提高竞争力的方法.从双边市场角度对此进行研究,采用格兰特因果检验方法对上海交易所数据进行了实证分析.研究结果表明投资者是上市公司的格兰特原因,上市公司不是投资者的格兰特原因.投资者增加,通过交叉网络外部性,能吸引更多公司来此上市.投资者是“鸡蛋相生”问题的关键点,扩大投资者规模对证券交易所非常重要.%Stock exchanges are the carrier of capital market, the competitiveness of which influents the security market' s efficiency of the nation. Pricing is the core of the competitiveness. It from the view of the theory of two-sided markets by using Granger causality test to analyze the data of Shanghai stock exchange is studied. The conclusion is that Investors are the Granger causality of listed companies while listed companies aren' t Investors' Granger causality. Increasing number of Investors can attract more companies by cross group-externalities. So compared to listed companies, Investors are the key to the scale of a stock exchange. It' s important for stock exchanges to expand the scale of investors.

  20. Altered effective connectivity network of the amygdala in posttraumatic stress disorder:a study based on granger causality a-nalysis%Granger因果检验对创伤后应激障碍杏仁核效应连接网络的研究

    Institute of Scientific and Technical Information of China (English)

    柯俊; 李凌江; 尹岩; 戚荣丰; 胡晓蕾; 段炼; 冯波; 向虎; 龚启勇; 卢光明

    2014-01-01

    目的:探讨创伤后应激障碍(posttraumatic stress disorder ,PTSD)患者杏仁核与全脑其它脑区间效应连接的改变。方法对经历汶川大地震的57例PTSD患者及77例对照行静息状态下的功能磁共振扫描,采用Granger因果(granger causality ,GC)检验方法分析双侧杏仁核与全脑其它脑区间影响的因果关系,进行组间比较并计算患者的临床用 PTSD诊断量表(clinician-Administered PTSD Scale ,CAPS)评分和异常脑区GC平均值的相关性。结果与对照组相比,PTSD患者杏仁核对内侧额回、扣带回、额上回、额下回、颞上回、颞下回和壳核的影响减弱,对海马和海马旁回、楔叶、楔前叶、丘脑的影响增强;而内侧额回、额中回、颞上回、颞中回、岛叶和壳核对杏仁核的影响减弱,楔叶、楔前叶和海马旁回对杏仁核的影响增强。PTSD患者的CAPS评分与杏仁核对颞上回和颞下回,额中回对杏仁核的影响呈负相关;而与杏仁核对楔前叶的影响呈正相关。结论 PTSD患者杏仁核与全脑其它脑区间的效应连接存在广泛异常,且与患者的症状严重程度相关。%Objective To explore the alteration of the effective connectivity between amygdala and other brain regions in posttraumatic stress disorder (PTSD) patients .Methods Fifty-seven patients with PTSD and seventy-seven controls who survived from the Wenchuan earthquake underwent the resting-state functional magnetic imaging scan .Granger causality analysis was used to compare the effective connectivity network of amygdala between PTSD patients and controls .In addi-tion ,Pearson correlation was performed between abnormal Granger causality and the Clinician-Administered PTSD Scale (CAPS) score of patients .Results Compared with controls ,PTSD patients showed decreased influence from amygdala to medial frontal gyrus ,cingulate cortex ,superior and inferior frontal gyri ,superior and inferior

  1. Granger Causality Test of Urban-rural Income Gap and Employment of Rural Labour Forces%城乡收入差距与农村劳动力就业的Granger因果检验——以寿光市为例

    Institute of Scientific and Technical Information of China (English)

    吕贵兴

    2012-01-01

    Taking Shouguang City in Shandong Province as an example, this article researches the mutual relationship between urban-rural income and employment of rural labour forces, and conducting cointegration test and Granger causality test on the variable sequences using statistical data. The results show that the average annual income of rural labour forces influences the income per capita of rural residents, and there is a Granger causality relationship between the income per capita of rural residents and urban employees' average wage. Engaging in production concerning agriculture, forestry, animal husbandry and fishery makes the total income per capita in rural areas of Shouguang City higher than the average wage of urban residents in Shouguang City, even in Weifang City. The comparative advantage in terms of income causes the city to loose attraction to rural residents in Shouguang City. The comparative advantage drives more rural labour forces in Shouguang City to engage in primary industry, thereby greatly reducing the pressure of employment and transfer of rural labour forces. Finally important following measures are put forward to promote employment and on-the-spot transfer of rural labour forces; vigorously propel agricultural industrialization; increase rural residents'income; improve the living conditions for rural residents.%以山东省寿光市为例,研究了城乡收入与农村劳动力就业的相互关系.利用统计数据,进行变量序列的协整检验与Granger因果检验,结果表明,农村劳动力年均收入影响农村居民人均收入,后者与职工平均工资存在Granger因果关系.从事农林牧渔业生产使得寿光农村人均总收入高于寿光乃至潍坊市的城镇居民平均工资,收入角度的比较利益使得城市对寿光农村居民不具有吸引力,极大地减小了农村劳动力就业和转移压力.从而指出大力推进农业产业化,提高农村居民收入,改善农村居民生活条件是促进农

  2. Temporal Causality between Human Capital and Real Income in Cointegrated VAR Processes: Empirical Evidence from China, 1960-1990

    OpenAIRE

    Paresh Kumar Narayan; Russell Smyth

    2004-01-01

    This article examines the causal relationship between human capital and real income using data for China from 1960 to 1999. In the long run there is unidirectional Granger causality running from human capital to real income, while in the short run there is unidirectional Granger causality running from real income to human capital.

  3. The Study Based on the Granger Causality and GARCH Model of the Correlation of RMB Spot and Forward Exchange Rate%基于格兰杰和GARCH模型对人民币即期与远期引导关系的研究

    Institute of Scientific and Technical Information of China (English)

    原浩; 杨常锴; 杨滟; 安佳

    2014-01-01

    采用格兰杰分析方法对2011年6月27日至2013年12月31日期间共919对人民币兑美元境内远期、香港离岸远期对境内即期汇率的引导作用进行研究,结果表明,境内远期市场和香港离岸市场的部分远期汇率对境内即期汇率有引导作用。其次使用GARCH模型检验,两个远期市场对境内即期汇率都有一定的溢出效应,且期限越小的远期汇率溢出效应越明显,香港离岸市场比境内远期市场溢出效应更明显。%In this paper,the granger causality test is employed to examine the relationship between RMBdomestic spot and forward exchange rate and Hong Kong’s RMB offshore forward exchange rate data during 27th June 2011 and 31st December 2013.The results show the evidence of unidirectional causality from some forward rates to domestic spot rate.The results from GARCH model also show the spillover effect from both domestic and offshore forward rates to spot rates.The less the term is,the more obvious the spillover effect is.And Hong Kong’s RMB offshore market is more obvious than domestic market.

  4. Finland 1993

    DEFF Research Database (Denmark)

    Ørstrup, Finn Rude

    1993-01-01

    Kompendium udarbejdet til en studierejse til Finland maj 1998 Kunstakademiets Arkitektskole, Institut 3H......Kompendium udarbejdet til en studierejse til Finland maj 1998 Kunstakademiets Arkitektskole, Institut 3H...

  5. 国际原油价格与我国原油进口量关系研究--基于系统思考与格兰杰因果检验%Study on the Relation between International Crude Oil Prices and China's Oil Imports--An Analysis based on System Thinking and Granger Causality Tests

    Institute of Scientific and Technical Information of China (English)

    张力菠; 谢丽琨

    2013-01-01

    Over the past nearly 20 years, China's crude oil imports climbed, while overall growth on the international price of cr-ude oil, so China's crude imports pushed Gao Guoji appeared on the international crude oil prices. Therefore, using system thinking method to build the international crude oil prices affect the causal feedback model, system analysis of the influencing factors of international crude oil prices and the causal feedback loop and feedback mechanisms, to identify the key influence factors and the dominant feedback structure. Granger causality test model was established to further the international crude oil price and China's crude oil imports the actual data analysis, quantitative research is the change between the two and mutual influence relations. Results show that the international crude oil prices and China's crude imports between the long-term stable equilibrium relationship, and there are from the international price of crude oil to one-way causal relationship of China's crude oil imports, not easy to attribute the cause of the international crude oil prices higher for the increase of China's crude oil imports. Finally put forward the corresponding strategies to respond to the long-term and short-term.%  过去近20年来,中国原油进口量不断攀升,同时国际原油价格总体上也呈增长态势。于是国际上出现了中国进口原油推高国际原油价格的说法。为此,利用系统思考方法构建了国际原油价格影响的因果反馈模型,系统分析了国际原油价格的诸多影响因素及其因果反馈环路及反馈机制,识别了关键影响因素及主导反馈结构;进一步建立了格兰杰因果检验模型对国际原油价格与中国原油进口量的实际数据进行分析,研究两者之间的变动和相互影响关系。结果表明,国际原油价格和我国原油进口量之间呈现长期稳定的均衡关系,且存在着从国际原油价格到我国原油进口

  6. Carbon Emissions and Economic Growth: Alternative Approaches to Causality Testing

    Energy Technology Data Exchange (ETDEWEB)

    Rehdanz, Katrin (Christian-Albrechts Univ., Kiel (Germany)); Maddison, David J. (Univ. of Birmingham, Dept. of Economics, Birmingham (United Kingdom))

    2008-07-01

    Numerous papers have examined data on energy and GDP for evidence of Granger causality. More recently this technique has been extended to looking at the relationship between carbon emissions and GDP per capita. These analyses frequently reach differing conclusions concerning the existence and direction of Granger causality. This paper compares the standard fixed-dynamic-effects approach to a heterogenous panel approach testing for evidence of a causal relationship between GDP per capita and carbon emissions per capita allowing for heterogeneity. Overall there is strong evidence for the existence of a bidirectional causal relationship between GDP per capita and CO{sub 2} emissions per capita

  7. Education and Economic Growth in Nigeria: A Granger Causality ...

    African Journals Online (AJOL)

    FIRST LADY

    the hypothesis of a growth strategy led by improvements in the education sector. .... administrators in formulating appropriate plans and strategies for the sector. Education and .... through factor accumulation and on the evolution of total factor productivity. Aighokhan et al ... The study used historical data to establish the.

  8. Parallel versus Serial Processing Dependencies in the Perisylvian Speech Network: A Granger Analysis of Intracranial EEG Data

    Science.gov (United States)

    Gow, David W., Jr.; Keller, Corey J.; Eskandar, Emad; Meng, Nate; Cash, Sydney S.

    2009-01-01

    In this work, we apply Granger causality analysis to high spatiotemporal resolution intracranial EEG (iEEG) data to examine how different components of the left perisylvian language network interact during spoken language perception. The specific focus is on the characterization of serial versus parallel processing dependencies in the dominant…

  9. Institutional Investors and Stock Market Development: A Causality Study

    OpenAIRE

    Guler Aras; Alovsat Muslumov

    2008-01-01

    This article examines causality relationships between institutional investors and stock market development based on the panel data compiled from 23 OECD countries for the years 1982 through 2000. In order to test causality relationship, Sims’ causality test based on Granger definition of causality was used in our study. Our empirical results provide evidence that there are statistically significant positive relationship between institutional investors and stock market development. The develop...

  10. 基于格兰杰因果检验的陕西省国际旅游消费与地区经济增长关系研究%A granger causality analysis on tourism and economic growth of Shaanxi

    Institute of Scientific and Technical Information of China (English)

    郑鹏; 马耀峰; 王洁洁; 李天顺

    2011-01-01

    改革开放以来,陕西省的国际旅游消费与国民生产总值均获得了快速的发展。文中依据1978-2008年的相关统计数据,采用Eviews6.0软件,运用协整分析和格兰杰因果关系方法检验两者之间的关系,并建立两者间的推拉关系模型。研究结果显示:陕西国际旅游消费与地方经济存在着协整关系,且国际旅游消费是地方经济增长的原因;陕西国际旅游消费水平普遍较低,购物、娱乐和其它费用却增长迅速,这使得消费结构高级化指数不断增高,也意味着国际旅游消费结构日趋合理;以陕西国际旅游消费为自变量,国民生产总值为因变量,建立推拉方程,边际弹性分析显示,国际旅游消费每增长1亿元,推动陕西国民生产总值增加8.9232亿元,国际旅游消费对地方经济拉动的潜力巨大。%Since reform and opening,Shaanxi Province gained rapid development in both tourism and economy.Based on relevant statistics data in 1978-2008,using Eviews6.0 software,the authors applied cointegration and Granger causality to test the relationship between tourism and economy,and establish a push and pull model which is about tourism and economic.The results showed that: ①there is cointegration between the development of tourism and the local economy in Shaanxi,that is,a long-term stable relationship exists among inbound tourism,domestic tourism and GDP;② inbound tourism and domestic tourism are the reasons of GDP growth that can promote the development of tourism in Shaanxi,and inbound tourism for promoting economic development in Shaanxi Province is better than that of domestic tourism;③ the gross national product increase is the reason of domestic tourism growth,not the reason for the growth of inbound tourism,local economic development stimulates the domestic tourism obviously.

  11. Causality Between Urban Concentration and Environmental Quality

    Directory of Open Access Journals (Sweden)

    Amin Pujiati

    2015-08-01

    Full Text Available Population is concentrated in urban areas can cause the external diseconomies on environment if it exceeds the carrying capacity of the space and the urban economy. Otherwise the quality of the environment is getting better, led to the concentration of population in urban areas are increasingly high. This study aims to analyze the relationship of causality between the urban concentration and environmental quality in urban agglomeration areas. The data used in the study of secondary data obtained from the Central Bureau of statistics and the City Government from 2000 to 2013. The analytical method used is the Granger causality and descriptive. Granger causality study results showed no pattern of reciprocal causality, between urban concentration and the quality of the environment, but there unidirectional relationship between the urban concentration and environmental quality. This means that increasing urban concentration led to decreased environmental quality.

  12. Membership Finland

    CERN Document Server

    Rubbia,C

    1991-01-01

    Le DG C.Rubbia et la vice présidente du conseil du Cern souhaite la bienvenue à l'adhésion de la Finlande, comme 15me membre du Cern depuis le 1. janvier 1991 en présence du secrétaire generale et de l'ambassadeur

  13. Electricity consumption and economic growth nexus in Portugal using cointegration and causality approaches

    Energy Technology Data Exchange (ETDEWEB)

    Shahbaz, Muhammad [COMSATS Institute of Information Technology, Lahore (Pakistan); Tang, Chor Foon, E-mail: tcfoon@yahoo.com [Department of Economics, Faculty of Economics and Administration, University of Malaya, 50603 Kuala Lumpur (Malaysia); Shahbaz Shabbir, Muhammad [University of Illinois at Urbana-Champaign, Champaign (United States)

    2011-06-15

    The aim of this paper is to re-examine the relationship between electricity consumption, economic growth, and employment in Portugal using the cointegration and Granger causality frameworks. This study covers the sample period from 1971 to 2009. We examine the presence of a long-run equilibrium relationship using the bounds testing approach to cointegration within the Unrestricted Error-Correction Model (UECM). Moreover, we examine the direction of causality between electricity consumption, economic growth, and employment in Portugal using the Granger causality test within the Vector Error-Correction Model (VECM). As a summary of the empirical findings, we find that electricity consumption, economic growth, and employment in Portugal are cointegrated and there is bi-directional Granger causality between the three variables in the long-run. With the exception of the Granger causality between electricity consumption and economic growth, the rest of the variables are also bi-directional Granger causality in the short-run. Furthermore, we find that there is unidirectional Granger causality running from economic growth to electricity consumption, but no evidence of reversal causality. - Highlights: > We re-examine the relationship between electricity consumption, economic growth, and employment in Portugal. > The electricity consumption and economic growth is causing each other in the long-run. > In the short-run, economic growth Granger-cause electricity consumption, but no evidence of reversal causality. > Energy conservation policy will deteriorate the process of economic growth in the long-run. > Portugal should increase investment on R and D to design new energy savings technology.

  14. Is There Correlation Relationship between Service Industry Agglomeration and Regional Urbanization in China?--Based on the Analysis of Granger Causality Test of Provincial Panel Data from 1987 to 2011%我国服务业集聚与地区城市化存在关联关系吗?--基于1987年~2011年省级面板数据格兰杰因果检验的分析

    Institute of Scientific and Technical Information of China (English)

    纪玉俊; 丁科华

    2014-01-01

    Based on the Granger causality test of panel data, this paper makes the empirical analysis of correlation relationship between service industry agglomeration and urbanization of the provinces in our country divided into four areas of eastern, central, west and northeast . Although there exists significant regional economic difference, it reveals that there is no or one-way or two-way relationship between service industry agglomeration and urbanization in every province of four regions, and the reason is also different. From the perspective of regional urbanization, each region should adjust measures according to local conditions and realize positive interaction between service industry agglomeration and urbanization in different stages of development.%本文通过面板数据格兰杰因果检验的方法,对我国东、中、西及东北四区的各省份服务业集聚与城市化的关联关系进行了实证分析。研究发现,虽然存在着明显的区域经济差异,但四个地区各个省份服务业集聚与城市化都表现出没有或具有单向及双向的关联关系,其原因也各有不同。从区域城市化的角度而言,各个地区要因地制宜,从而在不同的发展阶段实现服务业集聚与城市化的良性互动。

  15. The mutual causality analysis between the stock and futures markets

    Science.gov (United States)

    Yao, Can-Zhong; Lin, Qing-Wen

    2017-07-01

    In this paper we employ the conditional Granger causality model to estimate the information flow, and find that the improved model outperforms the Granger causality model in revealing the asymmetric correlation between stocks and futures in the Chinese market. First, we find that information flows estimated by Granger causality tests from futures to stocks are greater than those from stocks to futures. Additionally, average correlation coefficients capture some important characteristics between stock prices and information flows over time. Further, we find that direct information flows estimated by conditional Granger causality tests from stocks to futures are greater than those from futures to stocks. Besides, the substantial increases of information flows and direct information flows exhibit a certain degree of synchronism with the occurrences of important events. Finally, the comparative analysis with the asymmetric ratio and the bootstrap technique demonstrates the slight asymmetry of information flows and the significant asymmetry of direct information flows. It reveals that the information flows from futures to stocks are slightly greater than those in the reverse direction, while the direct information flows from stocks to futures are significantly greater than those in the reverse direction.

  16. Stock prices, exchange rates and causality in Malaysia: a note

    OpenAIRE

    2006-01-01

    This article contributes to the debate on stock prices and exchange rates in Malaysia. It examines causal relations using a new Granger non-causality test proposed by Toda and Yamamoto (Journal of Econometrics, 66, 225-50, 1995). Among the findings of interest, there is a feedback interaction between exchange rates and stock prices for the pre-crisis period. The results also reveal that exchange rates lead stock prices for the crisis period. In a financially liberalized environment, exchange ...

  17. Granger Test to Determine Causes of Harmful algal Blooms in TaiLake during the Last Decade

    Science.gov (United States)

    Guo, W.; Wu, F.

    2016-12-01

    Eutrophication-driven harmful cyanobacteria blooms can threaten stability of lake ecosystems. A key to solving this problem is identifying the main cause of algal blooms so that appropriate remediation can be employed. A test of causality was used to analyze data for Meiling Bay in Tai Lake (Ch: Taihu) from 2000 to 2012. After filtration of data by use of the stationary test and the co-integration test, the Granger causality test and impulse response analysis were used to analyze potential bloom causes from physicochemical parameters to chlorophyll-a concentration. Results of stationary tests showed that logarithms of secchi disk depth (lnSD), suspended solids (lnSS), lnNH4-N/NOx-N and pH were determined to be stationary as a function of time and could not be considered to be causal for changes in biomass of phytoplankton observed during that period. Results of co-integration tests indicated existence of long-run co-integrating relationships among natural logarithms of chlorophyll-a (lnChl-a), water temperature (lnWT), total organic carbon (lnTOC) and ratio of nitrogen to phosphorus (lnN/P). The Granger causality test suggested that once thresholds for nutrients such as nitrogen and phosphorus had been reached, WT could increase the likelihood or severities of cyanobacteria blooms. An unidirectional Granger relationship from N/P to Chl-a was established, the result indicated that because concentrations of TN in Meiliang Bay had reached their thresholds, it no longer limited proliferation of cyanobacteria and TP should be controlled to reduce the likelihood of algae blooms. The impulse response analysis implied that lagging effects of water temperature and N/P ratio could influence the variation of Chla concentration at certain lag periods. The results can advance understanding of mechanisms on formation of harmful cyanobacteria blooms.

  18. Correlation analysis and causality test between Ludong-Huanghai block and South Japan

    Institute of Scientific and Technical Information of China (English)

    ZHENG Jian-chang; JIANG Hai-kun

    2007-01-01

    In this paper, we make a comparative analysis and correlation test for the seismic activities in the South Japan and the Ludong-Huanghai block (a secondary tectonic unit in the North China) and approach the relationship between the energy release processes of these two areas by using co-integration analysis and Granger causality test for the time series of random variables. The results show that the seismic activities in these two areas are correlative and synchronous to a certain extent, and their release series of cumulative strain energy are contemporaneously correlative. Both energy series are first-order difference stationary processes and there is secular and steady co-integration between them. We make a positive analysis on the first-order difference energy series through Granger causality test based on vector error correction (VEC) model and find there is unilateral Granger causality and prominent co-integration between the two energy release processes.

  19. Causality between Foreign Direct Investment and Tourism : Empirical Evidence from India

    OpenAIRE

    Saroja Selvanathan; Selvanathan, E.A.; Brinda Viswanathan

    2009-01-01

    This paper investigates the causal link between foreign direct investment and tourism in India by employing the Granger causality test under a VAR framework. A one-way causality link is found from foreign direct investment to tourism in India. This evidence once again adds to the need for appropriate policies and plans to further expand and develop tourism given that FDI flow into India is expected to be strong in the coming years, bringing along a demand for tourism as well.

  20. Causal Relationship Between Relative Price Variability and Inflation in Turkey: Evidence from Panel Data

    OpenAIRE

    2016-01-01

    This study investigates the causal relationship between inflation and relative price variability in Turkey for the period of January 2003-January 2014, by using panel data. In the study, a Granger (1969) non-causality test in heterogeneous panel data models developed by Dumitrescu and Hurlin (2012) is utilized to determine the causal relations between inflation rate relative price variability. The panel data consists of 4123 observations: 133 time observations and 31 cross-section observatio...

  1. The Causal Relationship Between Exchange Rates and Inflation in Turkey:1984-2003

    OpenAIRE

    2006-01-01

    In this study, we investigate empirically the causal relationship between nominal exchange rates and inflation by using high-frequency data of nominal exchange rates and inflation of Turkey. To determine the appropriate Granger causality relations, unit root and cointegtration models are used. With time-series techniques, this study provides evidence that a long-run relationship between nominal exchange rates and inflation exist. However, our results indicate that a causal relationship occurs...

  2. The Causal Relationship between Stock Prices and Exchange Rates: Evidence from the G-7

    OpenAIRE

    Shyh-Wei Chen; Tzu-Chun Chen

    2011-01-01

    We examine the nexus of stock prices and exchange rates for the G-7 countries by using the vector error correction model, the bounds testing methodology and linear and non-linear Granger causality methods. The empirical results substantiate that a long-run level equilibrium relationship exists among the exchange rates and stock prices for the UK and France. The results from the linear causality tests indicate significant short-run and long-run causal relations between the two financial market...

  3. Econometric causality

    OpenAIRE

    Heckman, James J.

    2008-01-01

    This paper presents the econometric approach to causal modeling. It is motivated by policy problems. New causal parameters are defined and identified to address specific policy problems. Economists embrace a scientific approach to causality and model the preferences and choices of agents to infer subjective (agent) evaluations as well as objective outcomes. Anticipated and realized subjective and objective outcomes are distinguished. Models for simultaneous causality are developed. The paper ...

  4. 中国进口贸易与经济增长——基于格兰杰因果关系的实证研究%China's Import Trade and Economic Growth——Based on Empirical Research of Granger Causality

    Institute of Scientific and Technical Information of China (English)

    关嘉麟

    2012-01-01

    Based on the data from 1978 to 2009, a research, which aims at testing the short-term and long-term causal relationship of China's import trade and economic growth is conducted by setting up Error Correction Mod- el. The result shows that import trade and economic growth has bidirectional causality. Long-term acceleration of import is more significant than its short-term acceleration. This result proves that trade development strategy should be adjusted from export-oriented trade strategy to the strategy of balancing the import and export trade in China 12th Five-Year Plan.%利用1978~2009年间的数据,通过建立误差修正模型,分别检验中国进口与经济增长的短期和长期因果关系。实证结果显示,进口贸易与中国经济增长具有双向的Granger因果关系,进口对经济增长的长期促进作用要比短期的促进作用更显著。这一结果支持我国十二五规划中将长期依赖出口导向型贸易发展战略调整为进口、出口平衡发展的贸易战略。

  5. Does Fiscal Deficit Granger Cause Impulsiveness in Inflation Rate in Nigeria?

    Directory of Open Access Journals (Sweden)

    Oseni Isiaq Olasunkanmi

    2016-08-01

    Full Text Available This study examines the direction of causality between fiscal policy and inflation volatility in Nigeria for the periods 1981 to 2014. Studies have examined the relationship between fiscal policy and inflation volatility without taking cognizant of the direction of relationship that exist between the two variables, hence this study. The study employs quarterly time series data on fiscal deficit and consumer price index (measure of inflation rate from 1981:1 to 2013:3 and obtains from the central bank of Nigeria statistical bulletin 2014 while the volatility data is generated through GARCH (1,1 method and analyze using the Pairwise Granger Causality Test. The results of the study showed that there is bi-directional causality between fiscal deficit ( − = 5.86 & 3.96; < 0.05 and inflation volatility. The implication of this result is that volatility in inflation rate is traceable to the persistent nature of the excess government expenditure over revenue of the Nigerian economy and vice versa; this will inform the government, policy makers and individual the reasons for continuous fluctuation in the prices of goods and services in the country. The paper contributes to knowledge by providing information on the causes of fluctuation in inflation rate in Nigeria.

  6. K-causality coincides with stable causality

    OpenAIRE

    Minguzzi, E

    2008-01-01

    It is proven that K-causality coincides with stable causality, and that in a K-causal spacetime the relation K^+ coincides with the Seifert's relation. As a consequence the causal relation "the spacetime is strongly causal and the closure of the causal relation is transitive" stays between stable causality and causal continuity.

  7. Causal inference

    Directory of Open Access Journals (Sweden)

    Richard Shoemaker

    2014-04-01

    Full Text Available Establishing causality has been a problem throughout history of philosophy of science. This paper discusses the philosophy of causal inference along the different school of thoughts and methods: Rationalism, Empiricism, Inductive method, Hypothetical deductive method with pros and cons. The article it starting from the Problem of Hume, also close to the positions of Russell, Carnap, Popper and Kuhn to better understand the modern interpretation and implications of causal inference in epidemiological research.

  8. Causal universe

    CERN Document Server

    Ellis, George FR; Pabjan, Tadeusz

    2013-01-01

    Written by philosophers, cosmologists, and physicists, this collection of essays deals with causality, which is a core issue for both science and philosophy. Readers will learn about different types of causality in complex systems and about new perspectives on this issue based on physical and cosmological considerations. In addition, the book includes essays pertaining to the problem of causality in ancient Greek philosophy, and to the problem of God's relation to the causal structures of nature viewed in the light of contemporary physics and cosmology.

  9. A Simple Test for Causality in Volatility

    Directory of Open Access Journals (Sweden)

    Chia-Lin Chang

    2017-03-01

    Full Text Available An early development in testing for causality (technically, Granger non-causality in the conditional variance (or volatility associated with financial returns was the portmanteau statistic for non-causality in the variance of Cheng and Ng (1996. A subsequent development was the Lagrange Multiplier (LM test of non-causality in the conditional variance by Hafner and Herwartz (2006, who provided simulation results to show that their LM test was more powerful than the portmanteau statistic for sample sizes of 1000 and 4000 observations. While the LM test for causality proposed by Hafner and Herwartz (2006 is an interesting and useful development, it is nonetheless arbitrary. In particular, the specification on which the LM test is based does not rely on an underlying stochastic process, so the alternative hypothesis is also arbitrary, which can affect the power of the test. The purpose of the paper is to derive a simple test for causality in volatility that provides regularity conditions arising from the underlying stochastic process, namely a random coefficient autoregressive process, and a test for which the (quasi- maximum likelihood estimates have valid asymptotic properties under the null hypothesis of non-causality. The simple test is intuitively appealing as it is based on an underlying stochastic process, is sympathetic to Granger’s (1969, 1988 notion of time series predictability, is easy to implement, and has a regularity condition that is not available in the LM test.

  10. Causal and causally separable processes

    Science.gov (United States)

    Oreshkov, Ognyan; Giarmatzi, Christina

    2016-09-01

    The idea that events are equipped with a partial causal order is central to our understanding of physics in the tested regimes: given two pointlike events A and B, either A is in the causal past of B, B is in the causal past of A, or A and B are space-like separated. Operationally, the meaning of these order relations corresponds to constraints on the possible correlations between experiments performed in the vicinities of the respective events: if A is in the causal past of B, an experimenter at A could signal to an experimenter at B but not the other way around, while if A and B are space-like separated, no signaling is possible in either direction. In the context of a concrete physical theory, the correlations compatible with a given causal configuration may obey further constraints. For instance, space-like correlations in quantum mechanics arise from local measurements on joint quantum states, while time-like correlations are established via quantum channels. Similarly to other variables, however, the causal order of a set of events could be random, and little is understood about the constraints that causality implies in this case. A main difficulty concerns the fact that the order of events can now generally depend on the operations performed at the locations of these events, since, for instance, an operation at A could influence the order in which B and C occur in A’s future. So far, no formal theory of causality compatible with such dynamical causal order has been developed. Apart from being of fundamental interest in the context of inferring causal relations, such a theory is imperative for understanding recent suggestions that the causal order of events in quantum mechanics can be indefinite. Here, we develop such a theory in the general multipartite case. Starting from a background-independent definition of causality, we derive an iteratively formulated canonical decomposition of multipartite causal correlations. For a fixed number of settings and

  11. Causal mapping

    DEFF Research Database (Denmark)

    Rasmussen, Lauge Baungaard

    2006-01-01

    The lecture note explains how to use the causal mapping method as well as the theoretical framework aoosciated to the method......The lecture note explains how to use the causal mapping method as well as the theoretical framework aoosciated to the method...

  12. Higher Education and Unemployment: A Cointegration and Causality Analysis of the Case of Turkey

    Science.gov (United States)

    Erdem, Ekrem; Tugcu, Can Tansel

    2012-01-01

    This article analyses the short and the long-term relations between higher education and unemployment in Turkey for the period 1960-2007. It chooses the recently developed ARDL cointegration and Granger causality of Dolado and Lutkepohl (1996) methods. While the proxy of unemployment is total unemployment rate, higher education graduates were…

  13. Higher Education and Unemployment: A Cointegration and Causality Analysis of the Case of Turkey

    Science.gov (United States)

    Erdem, Ekrem; Tugcu, Can Tansel

    2012-01-01

    This article analyses the short and the long-term relations between higher education and unemployment in Turkey for the period 1960-2007. It chooses the recently developed ARDL cointegration and Granger causality of Dolado and Lutkepohl (1996) methods. While the proxy of unemployment is total unemployment rate, higher education graduates were…

  14. Education and Economic Growth in Pakistan: A Cointegration and Causality Analysis

    Science.gov (United States)

    Afzal, Muhammad; Rehman, Hafeez Ur; Farooq, Muhammad Shahid; Sarwar, Kafeel

    2011-01-01

    This study explored the cointegration and causality between education and economic growth in Pakistan by using time series data on real gross domestic product (RGDP), labour force, physical capital and education from 1970-1971 to 2008-2009 were used. Autoregressive Distributed Lag (ARDL) Model of Cointegration and the Augmented Granger Causality…

  15. Trade Openness and Economic Growth: A Panel Cointegration and Causality Analysis for the Newest EU Countries

    Directory of Open Access Journals (Sweden)

    Nikolaos Dritsakis

    2016-03-01

    Full Text Available This paper explores the relationship between trade openness and economic growth using data for the thirteen newest European Union members. The study covers the period of 1995–2013. We have applied panel cointegration and causality approaches to examine the long-run and the causal relationship between the variables. Empirical results confirm the presence of a cointegrating vector between trade openness and economic growth, in this group of the thirteen countries. An error correction model (ECM, followed by the two steps of Engle and Granger was used to capture the short and long-run dynamics. The impact of economic growth and trade openness is found to be positive. Finally, the panel Granger causality analysis reveals a unidirectional causal relationship running from trade openness to economic growth, both in the short and in the long-run

  16. The causal relationship between Foreign Direct Investment and Current Account: an empirical investigation for Pakistan economy

    Directory of Open Access Journals (Sweden)

    Muhammad ASIM

    2013-08-01

    Full Text Available This paper investigates relationship between FDI and current account (CA in Pakistan using the Johansen-Juselius cointegration technique and the Granger causality test. The study results indicate that FDI and CA are cointegrated and thus exhibit a reliable long run relationship. The Granger causality test findings indicate that the causality between FDI and CA is uni-directional. However, there is no short run causality from FDI to CA and vice versa. Therefore, as a policy implication that FDI inflows may cause to the deterioration of the balance of payments in the long run should be taken into account when policy makers decide to implement policies to attract foreign investors.

  17. Causal Relationship Between Relative Price Variability and Inflation in Turkey:

    Directory of Open Access Journals (Sweden)

    Nebiye Yamak

    2016-09-01

    Full Text Available This study investigates the causal relationship between inflation and relative price variability in Turkey for the period of January 2003-January 2014, by using panel data. In the study, a Granger (1969 non-causality test in heterogeneous panel data models developed by Dumitrescu and Hurlin (2012 is utilized to determine the causal relations between inflation rate relative price variability. The panel data consists of 4123 observations: 133 time observations and 31 cross-section observations. The results of panel causality test indicate that there is a bidirectional causality between inflation rate and relative price variability by not supporting the imperfection information model of Lucas and the menu cost model of Ball and Mankiw.

  18. Algorithms of causal inference for the analysis of effective connectivity among brain regions

    Directory of Open Access Journals (Sweden)

    Daniel eChicharro

    2014-07-01

    Full Text Available In recent years, powerful general algorithms of causal inference have been developed. In particular, in the framework of Pearl’s causality, algorithms of inductive causation (IC and IC* provide a procedure to determine which causal connections among nodes in a network can be inferred from empirical observations even in the presence of latent variables, indicating the limits of what can be learned without active manipulation of the system. These algorithms can in principle become important complements to established techniques such as Granger causality and Dynamic Causal Modeling (DCM to analyze causal influences (effective connectivity among brain regions. However, their application to dynamic processes has not been yet examined. Here we study how to apply these algorithms to time-varying signals such as electrophysiological or neuroimaging signals. We propose a new algorithm which combines the basic principles of the previous algorithms with Granger causality to obtain a representation of the causal relations suited to dynamic processes. Furthermore, we use graphical criteria to predict dynamic statistical dependencies between the signals from the causal structure. We show how some problems for causal inference from neural signals (e.g. measurement noise, hemodynamic responses, and time aggregation can be understood in a general graphical approach. Focusing on the effect of spatial aggregation, we show that when causal inference is performed at a coarser scale than the one at which the neural sources interact, results strongly depend on the degree of integration of the neural sources aggregated in the signals, and thus characterize more the intra-areal properties than the interactions among regions. We finally discuss how the explicit consideration of latent processes contributes to understand Granger causality and DCM as well as to distinguish functional and effective connectivity.

  19. Algorithms of causal inference for the analysis of effective connectivity among brain regions.

    Science.gov (United States)

    Chicharro, Daniel; Panzeri, Stefano

    2014-01-01

    In recent years, powerful general algorithms of causal inference have been developed. In particular, in the framework of Pearl's causality, algorithms of inductive causation (IC and IC(*)) provide a procedure to determine which causal connections among nodes in a network can be inferred from empirical observations even in the presence of latent variables, indicating the limits of what can be learned without active manipulation of the system. These algorithms can in principle become important complements to established techniques such as Granger causality and Dynamic Causal Modeling (DCM) to analyze causal influences (effective connectivity) among brain regions. However, their application to dynamic processes has not been yet examined. Here we study how to apply these algorithms to time-varying signals such as electrophysiological or neuroimaging signals. We propose a new algorithm which combines the basic principles of the previous algorithms with Granger causality to obtain a representation of the causal relations suited to dynamic processes. Furthermore, we use graphical criteria to predict dynamic statistical dependencies between the signals from the causal structure. We show how some problems for causal inference from neural signals (e.g., measurement noise, hemodynamic responses, and time aggregation) can be understood in a general graphical approach. Focusing on the effect of spatial aggregation, we show that when causal inference is performed at a coarser scale than the one at which the neural sources interact, results strongly depend on the degree of integration of the neural sources aggregated in the signals, and thus characterize more the intra-areal properties than the interactions among regions. We finally discuss how the explicit consideration of latent processes contributes to understand Granger causality and DCM as well as to distinguish functional and effective connectivity.

  20. Causal measures of structure and plasticity in simulated and living neural networks.

    Directory of Open Access Journals (Sweden)

    Alex J Cadotte

    Full Text Available A major goal of neuroscience is to understand the relationship between neural structures and their function. Recording of neural activity with arrays of electrodes is a primary tool employed toward this goal. However, the relationships among the neural activity recorded by these arrays are often highly complex making it problematic to accurately quantify a network's structural information and then relate that structure to its function. Current statistical methods including cross correlation and coherence have achieved only modest success in characterizing the structural connectivity. Over the last decade an alternative technique known as Granger causality is emerging within neuroscience. This technique, borrowed from the field of economics, provides a strong mathematical foundation based on linear auto-regression to detect and quantify "causal" relationships among different time series. This paper presents a combination of three Granger based analytical methods that can quickly provide a relatively complete representation of the causal structure within a neural network. These are a simple pairwise Granger causality metric, a conditional metric, and a little known computationally inexpensive subtractive conditional method. Each causal metric is first described and evaluated in a series of biologically plausible neural simulations. We then demonstrate how Granger causality can detect and quantify changes in the strength of those relationships during plasticity using 60 channel spike train data from an in vitro cortical network measured on a microelectrode array. We show that these metrics can not only detect the presence of causal relationships, they also provide crucial information about the strength and direction of that relationship, particularly when that relationship maybe changing during plasticity. Although we focus on the analysis of multichannel spike train data the metrics we describe are applicable to any stationary time series in which

  1. The Causal Relationship between Corruption and Poverty: A Panel Data Analysis

    OpenAIRE

    2010-01-01

    Most of the studies which have investigated the link between corruption and poverty may draw conclusions on causality in the form of models that only show correlation. This study is set out to investigate the Granger causal relationship between corruption and poverty. It uses dynamic panel system GMM estimators, focuses on capability poverty using human poverty index (HPI) and is based on a sample of 97 developing countries during 1997-2006. The empirical findings reveal that corruption and p...

  2. Foreign direct investment and profit outflows: a causality analysis for the Brazilian economy

    OpenAIRE

    Fernando Seabra; Lisandra Flach

    2005-01-01

    Most empirical works have focused on the effects of foreign direct investment (FDI) to exports and other economic performance indicators, whereas its impacts to profit outflows has been relatively neglected. This paper investigates the nature of the causal relationship between FDI and profit remittance in Brazil using the Granger causality test procedure developed by Toda and Yamamoto (1995). The findings in this paper indicate that FDI causes profit remittance and emphasize significant adver...

  3. Causality relationship between coal consumption and GDP: Difference of major OECD and non-OECD countries

    Energy Technology Data Exchange (ETDEWEB)

    Jinke, L.; Hualing, S.; Dianming, G. [Shandong Institute for Business & Technology, Yantai (China)

    2008-06-15

    This paper uses Granger causality tests to examine the differences of causal relationships between coal consumption and GDP in major OECD and non-OECD countries, using data for the period of 1980-2005. What we discovered is that unidirectional causality running from GDP to coal consumption exists in Japan and China, and no causality relationship between coal consumption and GDP in India, South Korea and South Africa while the series are not cointegrated in USA. The major OECD or non-OECD countries especially China, India and South Africa should reduce their CO{sub 2} emissions in coal consumption to reach sustainable development.

  4. Causality Networks

    OpenAIRE

    Ishanu Chattopadhyay

    2014-01-01

    While correlation measures are used to discern statistical relationships between observed variables in almost all branches of data-driven scientific inquiry, what we are really interested in is the existence of causal dependence. Designing an efficient causality test, that may be carried out in the absence of restrictive pre-suppositions on the underlying dynamical structure of the data at hand, is non-trivial. Nevertheless, ability to computationally infer statistical prima facie evidence of...

  5. The Causal Relationship between Health and Education Expenditures in Malaysia

    Directory of Open Access Journals (Sweden)

    Chor Foon TANG

    2011-08-01

    Full Text Available A major macroeconomic policy in generating economic growth is to encourage investments on human capital such as health and education. This is because both health and education make significant contribution to increasing productivity of the labour force which ultimately exerts a positive effect on raising output levels. A question that arises is whether investments on health and education have a causal relationship and if so, what is the directional causality? The objective of this study is to examine the causal relationship between health and education expenditures in Malaysia. This study covered annual data from 1970 to 2007. Using Granger causality as well as Toda and Yamamoto MWALD causality approaches, this study suggests that education Granger-causes health expenditure in both the short run and long run. The findings of this study implied that the Malaysian society places preference on education expenditure rather than health. This preference is not unexpected as generally, an educated and knowledgeable society precedes a healthy one. Before a society has attained a relatively higher level of education, it is less aware of the importance of health. Thus, expenditure on education should lead expenditure on health.

  6. THE CAUSALITY RELATION BETWEEN FINANCIAL DEVELOPMENT AND ECONOMIC GROWTH: AN ANALYSIS FOR EMERGING ECONOMIES

    Directory of Open Access Journals (Sweden)

    Şeref BOZOKLU

    2013-12-01

    Full Text Available This study examines the relationship between financial development and economicgrowth employing panel Granger causality test developed by Dumitrescu ve Hurlin (2012for Brazil, Chile, China, Egypt, Hungry, India, Indonesia, Malaysia, Mexico, Peru,Philippines, South Korea, Thailand and Turkey. We used yearly data over the period 1988-2011. Domestic credits to Gross Domestic Product (GDP ratio and real GDP per capitaare used as indicators for financial development and economic growth respectively. Theempirical results strongly indicate that financial development Granger-causes economicgrowth and that these countries can accelerate their growth rates by improving theirfinancial systems. 

  7. Epidemiological causality.

    Science.gov (United States)

    Morabia, Alfredo

    2005-01-01

    Epidemiological methods, which combine population thinking and group comparisons, can primarily identify causes of disease in populations. There is therefore a tension between our intuitive notion of a cause, which we want to be deterministic and invariant at the individual level, and the epidemiological notion of causes, which are invariant only at the population level. Epidemiologists have given heretofore a pragmatic solution to this tension. Causal inference in epidemiology consists in checking the logical coherence of a causality statement and determining whether what has been found grossly contradicts what we think we already know: how strong is the association? Is there a dose-response relationship? Does the cause precede the effect? Is the effect biologically plausible? Etc. This approach to causal inference can be traced back to the English philosophers David Hume and John Stuart Mill. On the other hand, the mode of establishing causality, devised by Jakob Henle and Robert Koch, which has been fruitful in bacteriology, requires that in every instance the effect invariably follows the cause (e.g., inoculation of Koch bacillus and tuberculosis). This is incompatible with epidemiological causality which has to deal with probabilistic effects (e.g., smoking and lung cancer), and is therefore invariant only for the population.

  8. Women in physics in Finland

    Science.gov (United States)

    Banzuzi, Kukka

    2013-03-01

    The representation of women in physics and related fields of study in Finland, career advancement of female physicists in Finland, and the actions carried out in recent years to improve the situation are summarized.

  9. Learning Why Things Change: The Difference-Based Causality Learner

    CERN Document Server

    Voortman, Mark; Druzdzel, Marek J

    2012-01-01

    In this paper, we present the Difference- Based Causality Learner (DBCL), an algorithm for learning a class of discrete-time dynamic models that represents all causation across time by means of difference equations driving change in a system. We motivate this representation with real-world mechanical systems and prove DBCL's correctness for learning structure from time series data, an endeavour that is complicated by the existence of latent derivatives that have to be detected. We also prove that, under common assumptions for causal discovery, DBCL will identify the presence or absence of feedback loops, making the model more useful for predicting the effects of manipulating variables when the system is in equilibrium. We argue analytically and show empirically the advantages of DBCL over vector autoregression (VAR) and Granger causality models as well as modified forms of Bayesian and constraintbased structure discovery algorithms. Finally, we show that our algorithm can discover causal directions of alpha r...

  10. Foreign direct investment and policy framework: New Granger causality evidence from African countries

    Directory of Open Access Journals (Sweden)

    Rafiu Adewale Aregbeshola

    2014-11-01

    Full Text Available The strategic importance of foreign direct investment in the contemporary economies has been tremendous.While various countries (developed and developing economies have benefitted from the direct and spillovereffects of FDI, which range from improved technology and knowledge diffusion through to individual andcorporate capability enhancement, FDI outflow remains largely channelled to the developed countries, andthe rapidly developing countries in Asia and South America. Evidence suggests that the developmentenhancingeffects of FDI are felt more highly in the developing economies, such as economies in Africa.However, FDI inflow to the developing economies has been very low. Using data generated from the AfricanDevelopment Indicators (ADI between 1980 and 2008 in econometric estimations, this paper finds thatgovernment policies (especially fiscal and monetary policies play significant roles in facilitating FDI inflow tothe African countries studied. The study thereby suggests an improved regulatory framework to make Africamore attractive to inflow of FDI.

  11. Granger Causalities Between Interest Rate, Price Level, Money Supply and Real Gdp in the Czech Republic

    National Research Council Canada - National Science Library

    Tomáš Urbanovský

    2017-01-01

    ... – interest rate, price level, money supply and real GDP – in the Czech Republic in order to find out definite implications of its interactions and give recommendations to macroeconomic policy authorities...

  12. Lending for Growth? A Granger Causality Analysis of China's Finance-Growth Nexus

    NARCIS (Netherlands)

    Andersson, F.N.G.; Burzynska, K.; Opper, S.

    2016-01-01

    China’s banking sector is dominated by four distinct organizational forms: policy banks (PBs), state-owned commercial banks (SOCBs), joint stock commercial banks (JSCBs), and rural credit cooperatives (RCCs). Economic analyses have especially focused on the development of bank efficiency and profita

  13. Multinational enterprises, foreign direct investment and trade in China : A cointegration and Granger-causality approach

    NARCIS (Netherlands)

    Zhang, Jianhong; Jacobs, Jan; Witteloostuijn, Arjen van

    2004-01-01

    Multinational enterprises (MNEs) play a dominant role in the international business (IB) literature. Traditionally, by far the majority of IB studies deal with issues at the micro level of the individual MNE, or at the meso level of a sample of individual MNEs. This paper focuses on a macro-level is

  14. Multinational enterprises, foreign direct investment and trade in China : A cointegration and Granger-causality approach

    NARCIS (Netherlands)

    Zhang, Jianhong; Jacobs, Jan; Witteloostuijn, Arjen van

    2004-01-01

    Multinational enterprises (MNEs) play a dominant role in the international business (IB) literature. Traditionally, by far the majority of IB studies deal with issues at the micro level of the individual MNE, or at the meso level of a sample of individual MNEs. This paper focuses on a macro-level is

  15. Multinational enterprises, foreign direct investment and trade in China : A cointegration and Granger-causality approach

    NARCIS (Netherlands)

    Zhang, Jianhong; Jacobs, Jan; Witteloostuijn, Arjen van

    2004-01-01

    Multinational enterprises (MNEs) play a dominant role in the international business (IB) literature. Traditionally, by far the majority of IB studies deal with issues at the micro level of the individual MNE, or at the meso level of a sample of individual MNEs. This paper focuses on a macro-level

  16. Linear and nonlinear causality between sectoral electricity consumption and economic growth. Evidence from Taiwan

    Energy Technology Data Exchange (ETDEWEB)

    Cheng-Lang, Yang; Chang, Chih-Heng [Department of Managerial Economics, Nanhua University, Chiayi 62102 (China); Lin, Hung-Pin [Department of International Business and Trade, Shu-Te University, Kaohsiung 82445 (China)

    2010-11-15

    This study investigates the linear and nonlinear causality between the total electricity consumption (TEC) and real gross domestic production (RGDP). Unlike previous literature, we solve the undetermined relation between RGDP and electricity consumption by classifying TEC into industrial sector consumption (ISC) and residential sector consumption (RSC) as well as investigating how TEC, ISC, and RSC influence Taiwan's RGDP. By using the Granger's linear causality test, it is shown that (1) there is a bidirectional causality among TEC, ISC, and RGDP, but a neutrality between RSC and RGDP with regard to the linear causality and (2) there is still a bidirectional causality between TEC and RGDP, but a unidirectional causality between RSC and RGDP with regard to the nonlinear causality. On the basis of (1) and (2), we suggest that the electricity policy formulators loosen the restriction on ISC and limit RSC in order to achieve the goal of economic growth. (author)

  17. Linear and nonlinear causality between sectoral electricity consumption and economic growth: Evidence from Taiwan

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Cheng-Lang [Department of Managerial Economics, Nanhua University, Chiayi 62102, Taiwan (China); Lin, Hung-Pin, E-mail: lhp0606@stu.edu.t [Department of International Business and Trade, Shu-Te University, Kaohsiung 82445, Taiwan (China); Chang, Chih-Heng [Department of Managerial Economics, Nanhua University, Chiayi 62102, Taiwan (China)

    2010-11-15

    This study investigates the linear and nonlinear causality between the total electricity consumption (TEC) and real gross domestic production (RGDP). Unlike previous literature, we solve the undetermined relation between RGDP and electricity consumption by classifying TEC into industrial sector consumption (ISC) and residential sector consumption (RSC) as well as investigating how TEC, ISC, and RSC influence Taiwan's RGDP. By using the Granger's linear causality test, it is shown that (i) there is a bidirectional causality among TEC, ISC, and RGDP, but a neutrality between RSC and RGDP with regard to the linear causality and (ii) there is still a bidirectional causality between TEC and RGDP, but a unidirectional causality between RSC and RGDP with regard to the nonlinear causality. On the basis of (i) and (ii), we suggest that the electricity policy formulators loosen the restriction on ISC and limit RSC in order to achieve the goal of economic growth.

  18. Causality Principle

    OpenAIRE

    Chi, Do Minh

    2001-01-01

    We advance a famous principle - causality principle - but under a new view. This principle is a principium automatically leading to most fundamental laws of the nature. It is the inner origin of variation, rules evolutionary processes of things, and the answer of the quest for ultimate theories of the Universe.

  19. Causality links among renewable energy consumption, CO2 emissions, and economic growth in Africa: evidence from a panel ARDL-PMG approach.

    Science.gov (United States)

    Attiaoui, Imed; Toumi, Hassen; Ammouri, Bilel; Gargouri, Ilhem

    2017-05-01

    This research examines the causality (For the remainder of the paper, the notion of causality refers to Granger causality.) links among renewable energy consumption (REC), CO2 emissions (CE), non-renewable energy consumption (NREC), and economic growth (GDP) using an autoregressive distributed lag model based on the pooled mean group estimation (ARDL-PMG) and applying Granger causality tests for a panel consisting of 22 African countries for the period between 1990 and 2011. There is unidirectional and irreversible short-run causality from CE to GDP. The causal direction between CE and REC is unobservable over the short-term. Moreover, we find unidirectional, short-run causality from REC to GDP. When testing per pair of variables, there are short-run bidirectional causalities among REC, CE, and GDP. However, if we add CE to the variables REC and NREC, the causality to GDP is observable, and causality from the pair REC and NREC to economic growth is neutral. Likewise, if we add NREC to the variables GDP and REC, there is causality. There are bidirectional long-run causalities among REC, CE, and GDP, which supports the feedback assumption. Causality from GDP to REC is not strong for the panel. If we test per pair of variables, the strong causality from GDP and CE to REC is neutral. The long-run PMG estimates show that NREC and gross domestic product increase CE, whereas REC decreases CE.

  20. Exploratory Causal Analysis in Bivariate Time Series Data

    Science.gov (United States)

    McCracken, James M.

    Many scientific disciplines rely on observational data of systems for which it is difficult (or impossible) to implement controlled experiments and data analysis techniques are required for identifying causal information and relationships directly from observational data. This need has lead to the development of many different time series causality approaches and tools including transfer entropy, convergent cross-mapping (CCM), and Granger causality statistics. In this thesis, the existing time series causality method of CCM is extended by introducing a new method called pairwise asymmetric inference (PAI). It is found that CCM may provide counter-intuitive causal inferences for simple dynamics with strong intuitive notions of causality, and the CCM causal inference can be a function of physical parameters that are seemingly unrelated to the existence of a driving relationship in the system. For example, a CCM causal inference might alternate between ''voltage drives current'' and ''current drives voltage'' as the frequency of the voltage signal is changed in a series circuit with a single resistor and inductor. PAI is introduced to address both of these limitations. Many of the current approaches in the times series causality literature are not computationally straightforward to apply, do not follow directly from assumptions of probabilistic causality, depend on assumed models for the time series generating process, or rely on embedding procedures. A new approach, called causal leaning, is introduced in this work to avoid these issues. The leaning is found to provide causal inferences that agree with intuition for both simple systems and more complicated empirical examples, including space weather data sets. The leaning may provide a clearer interpretation of the results than those from existing time series causality tools. A practicing analyst can explore the literature to find many proposals for identifying drivers and causal connections in times series data

  1. Getting to Finland

    DEFF Research Database (Denmark)

    Holm, Claus

    2015-01-01

    Kan man både opnå topplaceringer i PISA og blive Nordens mester i lighed gennem uddannelse? Finland kan. Men har den danske folkeskole mod til at tage samme type af ansvar for skabe større lighed gennem uddannelse, end vi hidtil har opnået?...

  2. Electromobility in Finland

    Energy Technology Data Exchange (ETDEWEB)

    Koskue, Mikko [Finpro, Muenchen (Germany). Tekes EVE Programme (Electric Vehicle Systems)

    2013-07-01

    Finland has set up several programs and platforms to be well prepared for the electric mobility development. The goal is to establish an international community focusing on the creation of new business around electric vehicles and related machinery and systems. (orig.)

  3. Causality and cointegration analysis between macroeconomic variables and the Bovespa.

    Directory of Open Access Journals (Sweden)

    Fabiano Mello da Silva

    Full Text Available The aim of this study is to analyze the causality relationship among a set of macroeconomic variables, represented by the exchange rate, interest rate, inflation (CPI, industrial production index as a proxy for gross domestic product in relation to the index of the São Paulo Stock Exchange (Bovespa. The period of analysis corresponded to the months from January 1995 to December 2010, making a total of 192 observations for each variable. Johansen tests, through the statistics of the trace and of the maximum eigenvalue, indicated the existence of at least one cointegration vector. In the analysis of Granger (1988 causality tests via error correction, it was found that a short-term causality existed between the CPI and the Bovespa. Regarding the Granger (1988 long-term causality, the results indicated a long-term behaviour among the macroeconomic variables with the BOVESPA. The results of the long-term normalized vector for the Bovespa variable showed that most signals of the cointegration equation parameters are in accordance with what is suggested by the economic theory. In other words, there was a positive behaviour of the GDP and a negative behaviour of the inflation and of the exchange rate (expected to be a positive relationship in relation to the Bovespa, with the exception of the Selic rate, which was not significant with that index. The variance of the Bovespa was explained by itself in over 90% at the twelfth month, followed by the country risk, with less than 5%.

  4. Causality and cointegration analysis between macroeconomic variables and the Bovespa.

    Science.gov (United States)

    da Silva, Fabiano Mello; Coronel, Daniel Arruda; Vieira, Kelmara Mendes

    2014-01-01

    The aim of this study is to analyze the causality relationship among a set of macroeconomic variables, represented by the exchange rate, interest rate, inflation (CPI), industrial production index as a proxy for gross domestic product in relation to the index of the São Paulo Stock Exchange (Bovespa). The period of analysis corresponded to the months from January 1995 to December 2010, making a total of 192 observations for each variable. Johansen tests, through the statistics of the trace and of the maximum eigenvalue, indicated the existence of at least one cointegration vector. In the analysis of Granger (1988) causality tests via error correction, it was found that a short-term causality existed between the CPI and the Bovespa. Regarding the Granger (1988) long-term causality, the results indicated a long-term behaviour among the macroeconomic variables with the BOVESPA. The results of the long-term normalized vector for the Bovespa variable showed that most signals of the cointegration equation parameters are in accordance with what is suggested by the economic theory. In other words, there was a positive behaviour of the GDP and a negative behaviour of the inflation and of the exchange rate (expected to be a positive relationship) in relation to the Bovespa, with the exception of the Selic rate, which was not significant with that index. The variance of the Bovespa was explained by itself in over 90% at the twelfth month, followed by the country risk, with less than 5%.

  5. Cointegration and Causality among Foreign Direct Investment in Tourism Sector, GDP, and Exchange Rate Volatility in Turkey

    OpenAIRE

    2007-01-01

    The Granger-causality (GC) and error correction (ECM) techniques were applied 1980-2005 data for Turkey to examine cointegration and causality among foreign direct investment(FDI) in tourism sector, overall GDP, and exchange rate volatility (EX). According to the ECM technique, the hypothesis that “no cointegration” was rejected for all three variables. The GC results detect causality runs from one-way from GDP to FDI, but the GC results detect bi-directional causality between GDP and EX sugg...

  6. Renforskningen i Finland

    Directory of Open Access Journals (Sweden)

    Mauri Nieminen

    1984-05-01

    Full Text Available Temaet ble bredt formidlet først med en gjennomgang av forskning før 1982. I de seneste årene har forskningen hatt karakter av både tillempet (anvendt og grunnleggende forskning som foregår på hele 20 steder i Finland, både ved universiteter, høgskoler og forskningsstasjoner. Den finske renbeteslagsforeningen skal også fremme forskning. 

  7. Biogerontology in Finland.

    Science.gov (United States)

    Strandberg, Timo E; Sipilä, Sarianna

    2011-02-01

    This paper describes current biogerontology research in Finland especially in the universities with professorships in gerontology/geriatrics. If biogerontology is broadly taken to include all research in basic mechanisms of normal ageing as well as age-related diseases, the most prevalent current topics include basic research in genetics, mitochondrial function, musculoskeletal physiology, neurodegenerative and vascular diseases. The research activity of each institute and their international collaboration is briefly described with examples focused on recent publications in the field of biogerontology.

  8. Capturing connectivity and causality in complex industrial processes

    CERN Document Server

    Yang, Fan; Shah, Sirish L; Chen, Tongwen

    2014-01-01

    This brief reviews concepts of inter-relationship in modern industrial processes, biological and social systems. Specifically ideas of connectivity and causality within and between elements of a complex system are treated; these ideas are of great importance in analysing and influencing mechanisms, structural properties and their dynamic behaviour, especially for fault diagnosis and hazard analysis. Fault detection and isolation for industrial processes being concerned with root causes and fault propagation, the brief shows that, process connectivity and causality information can be captured in two ways: ·      from process knowledge: structural modeling based on first-principles structural models can be merged with adjacency/reachability matrices or topology models obtained from process flow-sheets described in standard formats; and ·      from process data: cross-correlation analysis, Granger causality and its extensions, frequency domain methods, information-theoretical methods, and Bayesian ne...

  9. Estimating the directed information to infer causal relationships in ensemble neural spike train recordings.

    Science.gov (United States)

    Quinn, Christopher J; Coleman, Todd P; Kiyavash, Negar; Hatsopoulos, Nicholas G

    2011-02-01

    Advances in recording technologies have given neuroscience researchers access to large amounts of data, in particular, simultaneous, individual recordings of large groups of neurons in different parts of the brain. A variety of quantitative techniques have been utilized to analyze the spiking activities of the neurons to elucidate the functional connectivity of the recorded neurons. In the past, researchers have used correlative measures. More recently, to better capture the dynamic, complex relationships present in the data, neuroscientists have employed causal measures-most of which are variants of Granger causality-with limited success. This paper motivates the directed information, an information and control theoretic concept, as a modality-independent embodiment of Granger's original notion of causality. Key properties include: (a) it is nonzero if and only if one process causally influences another, and (b) its specific value can be interpreted as the strength of a causal relationship. We next describe how the causally conditioned directed information between two processes given knowledge of others provides a network version of causality: it is nonzero if and only if, in the presence of the present and past of other processes, one process causally influences another. This notion is shown to be able to differentiate between true direct causal influences, common inputs, and cascade effects in more two processes. We next describe a procedure to estimate the directed information on neural spike trains using point process generalized linear models, maximum likelihood estimation and information-theoretic model order selection. We demonstrate that on a simulated network of neurons, it (a) correctly identifies all pairwise causal relationships and (b) correctly identifies network causal relationships. This procedure is then used to analyze ensemble spike train recordings in primary motor cortex of an awake monkey while performing target reaching tasks, uncovering

  10. CAUSALITY AMONG NEW YORK, LONDON, TOKYO AND HONG KONG STOCK MARKETS

    Directory of Open Access Journals (Sweden)

    Nissim Ben David

    2011-08-01

    Full Text Available Investors tend to look into the possibility of broadening their investment activities across countries in order to diversify portfolio risk. This requires an understanding of regional and global linkages of stock markets. In this study, I examine the co-movements in worlds' largest equity markets. I used the daily data of S&P 500, Nikkey225, Hang Seng and FTSE100 for the period Jan-Nov 2009 in order to examine causality between the markets. Granger causality results show that eastern markets are affected by both S&P 500 and FTSE100, but do not affect western markets. Estimating the rate of change of each index as a function of its lags and of the lags of indexes that were found to granger-cause it, I find a very low predictability for S&P 500, Hang Seng and FTSE100 ,while the Nikkey 225 is pretty highly predictable.

  11. Causality relationship between the price of oil and economic growth in Japan

    Energy Technology Data Exchange (ETDEWEB)

    Hanabusa, Kunihiro [Graduate School of Economics, Kobe University, 2-1, Rokkodai, Nada, Kobe 657-8501 (Japan)

    2009-05-15

    This paper investigates the relationship between the price of oil and economic growth in Japan during the period from 2000 to 2008 using an exponential generalized autoregressive conditional heteroskedasticity (EGARCH) model. We employ a residual cross-correlation function (CCF) approach developed by [Cheung, Y.W., Ng, N.K., 1996. A causality-in-variance test and its application to financial market prices. Journal of Econometrics 72, 33-48]. The empirical results reveal that the economic growth rate Granger-causes the change of oil price in mean and variance and the change of oil price Granger-causes the economic growth rate in mean and variance. Previous studies have analyzed the response of economic activity to oil price shocks. However, we analyze the causality relations for both means and variances, and identify the direction of information flow and the timing of causation. (author)

  12. Analysis of co-integration and causality between coal consumption and economic growth in China

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, X.; Zhao, X.; Gu, R. [North China Electric Power University, Beijing (China)

    2008-06-15

    Using annual data from 1980 to 2005, the correlation between coal consumption and economic growth in China was investigated within a multivariate framework which includes coal consumption (GDP), structural changes and efficiency improvements. The results show that there is a long- term equilibrium between coal consumption and the other three variables. The error correction model is applied to forecast coal consumption and gives good results. The Granger causality test results suggest that there is a unidirectional Granger causality running from GDP and efficiency improvements to coal consumption respectively. From the orthogonalised impulse function, GDP, and structure changes have a positive effect on coal consumption but efficiency has a negative effect on coal consumption. 13 refs., 2 figs., 4 tabs.

  13. Teachers as Leaders in Finland

    Science.gov (United States)

    Sahlberg, Pasi

    2013-01-01

    During the last decade, thousands of visitors have flocked to Finland--now a leader in education rankings--to uncover this small Nordic country's secret to its education success. In this article, Finnish educator and scholar Pasi Sahlberg explains how Finland has managed such a feat. A rigorous graduate degree and at least five years of full-time…

  14. Economic growth and energy consumption causal nexus viewed through a bootstrap rolling window

    Energy Technology Data Exchange (ETDEWEB)

    Balcilar, Mehmet [Department of Economics, Eastern Mediterranean University, Famagusta, Turkish Republic of Northern Cyprus, via Mersin 10 (Turkey); Ozdemir, Zeynel Abidin [Department of Economics, Gazi University, Besevler, 06500, Ankara (Turkey); Arslanturk, Yalcin [Gazi University, Teknikokullar, 06500, Ankara (Turkey)

    2010-11-15

    One puzzling results in the literature on energy consumption-economic growth causality is the variability of results particularly across sample periods, sample sizes, and model specification. In order overcome these issues this paper analyzes the causal links between energy consumption and economic growth for G-7 countries using bootstrap Granger non-causality tests with fixed size rolling subsamples. The data used includes annual total energy consumption and real Gross Domestic Product (GDP) series from 1960 to 2006 for G-7 countries, excluding Germany, for which the sample period starts from 1971. Using the full sample bootstrap Granger causality test, we find that there is predictive power from energy consumption to economic growth only for Canada. However, parameter instability tests show that none of the estimated models have constant parameters and hence the full sample results are not reliable. Analogous to the full sample results, the results obtained from the bootstrap rolling window estimation indicate no consistent causal links between energy consumption and economic growth. We, however, find that causal links are present between the series in various subsamples. Furthermore, these subsample periods correspond to significant economic events, indicating that the findings are not statistical artefacts, but correspond to real economic changes. Our results encompass previous findings and offer an explanation to varying findings. (author)

  15. Finland to Join ESO

    Science.gov (United States)

    2004-02-01

    Finland will become the eleventh member state of the European Southern Observatory (ESO) [1]. Today, during a ceremony at the ESO Headquarters in Garching (Germany), a corresponding Agreement was signed by the Finnish Minister of Education and Science, Ms. Tuula Haatainen and the ESO Director General, Dr. Catherine Cesarsky, in the presence of other high officials from Finland and the ESO member states (see Video Clip 02/04 below). Following subsequent ratification by the Finnish Parliament of the ESO Convention and the associated protocols [2], it is foreseen that Finland will formally join ESO on July 1, 2004. Uniting European Astronomy ESO PR Photo 03/04 ESO PR Photo 03/04 Caption : Signing of the Finland-ESO Agreement on February 9, 2004, at the ESO Headquarters in Garching (Germany). At the table, the ESO Director General, Dr. Catherine Cesarsky, and the Finnish Minister of Education and Science, Ms. Tuula Haatainen . [Preview - JPEG: 400 x 499 pix - 52k] [Normal - JPEG: 800 x 997 pix - 720k] [Full Res - JPEG: 2126 x 2649 pix - 2.9M] The Finnish Minister of Education and Science, Ms. Tuula Haatainen, began her speech with these words: "On behalf of Finland, I am happy and proud that we are now joining the European Southern Observatory, one of the most successful megaprojects of European science. ESO is an excellent example of the potential of European cooperation in science, and along with the ALMA project, more and more of global cooperation as well." She also mentioned that besides science ESO offers many technological challenges and opportunities. And she added: "In Finland we will try to promote also technological and industrial cooperation with ESO, and we hope that the ESO side will help us to create good working relations. I am confident that Finland's membership in ESO will be beneficial to both sides." Dr. Catherine Cesarsky, ESO Director General, warmly welcomed the Finnish intention to join ESO. "With the accession of their country to ESO, Finnish

  16. Infrared technology in Finland

    Science.gov (United States)

    Hartikainen, Jari A.

    2003-01-01

    This paper presents the main actors in the Finnish infrared research community in the Defense Forces, the civilian research institutes and industry. Within the Defence Forces, the Defence Forces Research Centre (PvTT) has a key role as the most important research institute dealing with military technology in Finland and as an integrator of civilian expertise. The basic research strategy of the Finnish Defense Forces is to rely on external research institutes (either domestic or foreign) and to concentrate its own resources only on the areas where external expertise is not available. Accordingly, the research focus of PvTT is on the signature research and the environmental conditions affecting the performance of infrared sensors. The paper also describes the work done at the Technical Research Centre of Finland (VTT) and at various universities. The role of the Finnish defense industry has been fairly modest, but both its own products and recent technology transfer agreements may change the situation in the long run.

  17. AN EMPIRICAL ANALYSIS OF CAUSAL RELATIONSHIP BETWEEN STOCK MARKET AND MACROECONOMIC VARIABLES IN INDIA

    Directory of Open Access Journals (Sweden)

    Ashish Kumar

    2011-05-01

    Full Text Available The present paper is aimed at studying the nature of the causal relationship between stock prices and macroeconomic variables in India, if any such relationship exists. For this purpose the techniques of unit– root tests, cointegration and the Granger causality test have been applied between the NSE Index ‘Nifty’ and the macroeconomic variables, viz. , Real effective economic rate (REER, Foreign Exchange Reserve (FER, and Balance of Trade (BoT, Foreign Direct Investment (FDI, Index of industrial production (IIP, Wholesale price index (WPI using monthly data for the period from 1st April 2006 to 31st March 2010 have been studied.The major findings of the study are (i there is no co integration between Nifty and all other variables except Wholesale price index (WPI as per Johansen Co integration test. Therefore causal relationship between such macro economic variables having no co integration with nifty is not established. (ii Nifty does not Granger Cause WPI and WPI also does not Granger Cause Nifty.

  18. Cointegration and causality between electricity consumption and GDP: empirical evidence from Malawi

    Energy Technology Data Exchange (ETDEWEB)

    Jumbe, C.B.L. [Agriculture Univ. of Norway, Aas (Norway). Dept. of Economics and Social Sciences

    2004-01-01

    The Granger-causality (GC) and error correction (ECM) techniques were applied on 1970-1999 data for Malawi to examine cointegration and causality between electricity consumption (kWh) and, respectively, overall GDP, agricultural-GDP (AGDP) and non-agricultural-GDP (NGDP). Cointegration was established between kWh and, respectively, GDP and NGDP, but not with AGDP. The GC results detect bi-directional causality between kWh and GDP suggesting that kWh and GDP are jointly determined, but one-way causality running from NGDP to kWh. The ECM results detect causality running one-way from GDP (also from NGDP) to kWh suggesting that a permanent rise in GDP may cause a permanent growth in electricity consumption. (Author)

  19. Cointegration and causality between electricity consumption and GDP. Empirical evidence from Malawi

    Energy Technology Data Exchange (ETDEWEB)

    Jumbe, Charles B.L. [Department of Economics and Social Sciences, Agriculture University of Norway, P.B. 5033, As N-1432 (Norway)

    2004-01-01

    The Granger-causality (GC) and error correction (ECM) techniques were applied on 1970-1999 data for Malawi to examine cointegration and causality between electricity consumption (kWh) and, respectively, overall GDP, agricultural-GDP (AGDP) and non-agricultural-GDP (NGDP). Cointegration was established between kWh and, respectively, GDP and NGDP, but not with AGDP. The GC results detect bi-directional causality between kWh and GDP suggesting that kWh and GDP are jointly determined, but one-way causality running from NGDP to kWh. The ECM results detect causality running one-way from GDP (also from NGDP) to kWh suggesting that a permanent rise in GDP may cause a permanent growth in electricity consumption.

  20. Causality between Exports and Economic Growth: Investigating Suitable Trade Policy for Pakistan

    Directory of Open Access Journals (Sweden)

    Shujaat ABBAS

    2012-11-01

    Full Text Available This study investigates causal relationship between GDP and exports for the period of 1975 to 2010. The aim of this study is to check affectivity of export promotion policy adopted by Pakistan during 1990s. Johansen test of Cointegration and Granger Causality employed to determine short run and long run causality. The result of Cointegration reveals existence of one positive cointegrating equation. The result of Causality test show short run and long run causality run from GDP to exports. The result concludes that both in short and long run only growth in production cause exports growth. Government should attempt to develop production side, which in long run develop trade and economy.

  1. The frequency domain causality analysis between energy consumption and income in the United States

    Directory of Open Access Journals (Sweden)

    Aviral Kumar Tiwari

    2014-03-01

    Full Text Available We investigated Granger-causality in the frequency domain between primary energy consumption/electricity consumption and GDP for the US by employing approach of Lemmens et al. (2008 and covering the period of January, 1973 to December, 2008. We found that causal and reverse causal relations between primary energy consumption and GDP and electricity consumption and GDP vary across frequencies. Our unique contribution in the existing literature lies in decomposing the causality on the basis of time horizons and demonstrating bidirectional the short-run, the medium-run and the long-run causality between GDP and primary energy consumption/electricity consumption and thus providing evidence for the feedback hypothesis. These results have important implications for the US for planning of the short, the medium and the long run energy and economic growth related policies.

  2. Causal Relationship Between Relative Price Variability and Inflation in Turkey: Evidence from Panel Data

    Directory of Open Access Journals (Sweden)

    Nebiye Yamak

    2016-06-01

    Full Text Available This study investigates the causal relationship between inflation and relative price variability in Turkey for the period of January 2003-January 2014, by using panel data. In the study, a Granger (1969 non-causality test in heterogeneous panel data models developed by Dumitrescu and Hurlin (2012 is utilized to determine the causal relations between inflation rate relative price variability. The panel data consists of 4123 observations: 133 time observations and 31 cross-section observations. The results of panel causality test indicate that there is a bidirectional causality between inflation rate and relative price variability by not supporting the imperfection information model of Lucas and the menu cost model of Ball and Mankiw.

  3. Causal Effect Estimation Methods

    OpenAIRE

    2014-01-01

    Relationship between two popular modeling frameworks of causal inference from observational data, namely, causal graphical model and potential outcome causal model is discussed. How some popular causal effect estimators found in applications of the potential outcome causal model, such as inverse probability of treatment weighted estimator and doubly robust estimator can be obtained by using the causal graphical model is shown. We confine to the simple case of binary outcome and treatment vari...

  4. Circular causality.

    Science.gov (United States)

    Thomas, R

    2006-07-01

    The problem of disentangling complex dynamic systems is addressed, especially with a view to identifying those variables that take part in the essential qualitative behaviour of systems. The author presents a series of reflections about the methods of formalisation together with the principles that govern the global operation of systems. In particular, a section on circuits, nuclei, and circular causality and a rather detailed description of the analytic use of the generalised asynchronous logical description, together with a brief description of its synthetic use (OreverseO logic). Some basic rules are recalled, such as the fact that a positive circuit is a necessary condition of multistationarity. Also, the interest of considering as a model, rather than a well-defined set of differential equations, a variety of systems that differ from each other only by the values of constant terms is emphasised. All these systems have a common Jacobian matrix and for all of them phase space has exactly the same structure. It means that all can be partitioned in the same way as regards the signs of the eigenvalues and thus as regards the precise nature of any steady states that might be present. Which steady states are actually present, depends on the values of terms of order zero in the ordinary differential equations (ODEs), and it is easy to find for which values of these terms a given point in phase space is steady. Models can be synthesised first at the level of the circuits involved in the Jacobian matrix (that determines which types and numbers of steady states are consistent with the model), then only at the level of terms of order zero in the ODE's (that determines which of the steady states actually exist), hence the title 'Circular casuality'.

  5. CO{sub 2} emissions, GDP and energy intensity: A multivariate cointegration and causality analysis for Greece, 1977-2007

    Energy Technology Data Exchange (ETDEWEB)

    Hatzigeorgiou, Emmanouil; Polatidis, Heracles; Haralambopoulos, Dias [Energy Management Laboratory, Dept. of Environment, University of the Aegean, University Hill, Xenia Building, Mytilene 81100 (Greece)

    2011-04-15

    This paper deals with the causal relationship analysis between Gross Domestic Product, Energy Intensity and CO{sub 2} emissions in Greece from 1977 to 2007, by means of Johansen cointegration tests and Granger-causality tests based on a multivariate Vector Error Correction Modeling. Results indicate that there is a set of uni-directional and bi-directional causalities among the selected time series. We performed a model Variance Decomposition Analysis using Choleski technique and we provided a comparison with other studies. The findings of the study have significant policy implications for countries like Greece as the decoupling of CO{sub 2} emissions and economic growth seems quite unlikely. (author)

  6. Approcher la Finlande.

    Directory of Open Access Journals (Sweden)

    Isabelle Debilly

    2004-01-01

    Full Text Available Cet ouvrage est fondé sur Finland, a cultural encyclopedia paru en 1997 ; il s'agit donc bien d'une traduction mais le terme d'encyclopédie a été considéré comme trop connoté dans la culture française depuis Diderot et d'Alembert, aussi le terme d' approche lui a été préféré. Ce livre ne se veut pas exhaustif, mais son objectif est de présenter une vision quelque peu décalée de la culture finlandaise ; il s'agit en tout cas de sortir de la vision ...

  7. Causal reasoning with forces

    Science.gov (United States)

    Wolff, Phillip; Barbey, Aron K.

    2015-01-01

    Causal composition allows people to generate new causal relations by combining existing causal knowledge. We introduce a new computational model of such reasoning, the force theory, which holds that people compose causal relations by simulating the processes that join forces in the world, and compare this theory with the mental model theory (Khemlani et al., 2014) and the causal model theory (Sloman et al., 2009), which explain causal composition on the basis of mental models and structural equations, respectively. In one experiment, the force theory was uniquely able to account for people's ability to compose causal relationships from complex animations of real-world events. In three additional experiments, the force theory did as well as or better than the other two theories in explaining the causal compositions people generated from linguistically presented causal relations. Implications for causal learning and the hierarchical structure of causal knowledge are discussed. PMID:25653611

  8. Causally nonseparable processes admitting a causal model

    Science.gov (United States)

    Feix, Adrien; Araújo, Mateus; Brukner, Časlav

    2016-08-01

    A recent framework of quantum theory with no global causal order predicts the existence of ‘causally nonseparable’ processes. Some of these processes produce correlations incompatible with any causal order (they violate so-called ‘causal inequalities’ analogous to Bell inequalities) while others do not (they admit a ‘causal model’ analogous to a local model). Here we show for the first time that bipartite causally nonseparable processes with a causal model exist, and give evidence that they have no clear physical interpretation. We also provide an algorithm to generate processes of this kind and show that they have nonzero measure in the set of all processes. We demonstrate the existence of processes which stop violating causal inequalities but are still causally nonseparable when mixed with a certain amount of ‘white noise’. This is reminiscent of the behavior of Werner states in the context of entanglement and nonlocality. Finally, we provide numerical evidence for the existence of causally nonseparable processes which have a causal model even when extended with an entangled state shared among the parties.

  9. Causality in physiological signals.

    Science.gov (United States)

    Müller, Andreas; Kraemer, Jan F; Penzel, Thomas; Bonnemeier, Hendrik; Kurths, Jürgen; Wessel, Niels

    2016-05-01

    Health is one of the most important non-material assets and thus also has an enormous influence on material values, since treating and preventing diseases is expensive. The number one cause of death worldwide today originates in cardiovascular diseases. For these reasons the aim of understanding the functions and the interactions of the cardiovascular system is and has been a major research topic throughout various disciplines for more than a hundred years. The purpose of most of today's research is to get as much information as possible with the lowest possible effort and the least discomfort for the subject or patient, e.g. via non-invasive measurements. A family of tools whose importance has been growing during the last years is known under the headline of coupling measures. The rationale for this kind of analysis is to identify the structure of interactions in a system of multiple components. Important information lies for example in the coupling direction, the coupling strength, and occurring time lags. In this work, we will, after a brief general introduction covering the development of cardiovascular time series analysis, introduce, explain and review some of the most important coupling measures and classify them according to their origin and capabilities in the light of physiological analyses. We will begin with classical correlation measures, go via Granger-causality-based tools, entropy-based techniques (e.g. momentary information transfer), nonlinear prediction measures (e.g. mutual prediction) to symbolic dynamics (e.g. symbolic coupling traces). All these methods have contributed important insights into physiological interactions like cardiorespiratory coupling, neuro-cardio-coupling and many more. Furthermore, we will cover tools to detect and analyze synchronization and coordination (e.g. synchrogram and coordigram). As a last point we will address time dependent couplings as identified using a recent approach employing ensembles of time series. The

  10. Measures of Causality in Complex Datasets with Application to Financial Data

    Directory of Open Access Journals (Sweden)

    Anna Zaremba

    2014-04-01

    Full Text Available This article investigates the causality structure of financial time series. We concentrate on three main approaches to measuring causality: linear Granger causality, kernel generalisations of Granger causality (based on ridge regression and the Hilbert–Schmidt norm of the cross-covariance operator and transfer entropy, examining each method and comparing their theoretical properties, with special attention given to the ability to capture nonlinear causality. We also present the theoretical benefits of applying non-symmetrical measures rather than symmetrical measures of dependence. We apply the measures to a range of simulated and real data. The simulated data sets were generated with linear and several types of nonlinear dependence, using bivariate, as well as multivariate settings. An application to real-world financial data highlights the practical difficulties, as well as the potential of the methods. We use two real data sets: (1 U.S. inflation and one-month Libor; (2 S&P data and exchange rates for the following currencies: AUDJPY, CADJPY, NZDJPY, AUDCHF, CADCHF, NZDCHF. Overall, we reach the conclusion that no single method can be recognised as the best in all circumstances, and each of the methods has its domain of best applicability. We also highlight areas for improvement and future research.

  11. Workplace harassment prevention in Finland

    OpenAIRE

    Lorek, Angelika

    2015-01-01

    The proposed research concerns the engagement of companies operating in Finland in prevention of workplace harassment. The main target of the thesis is to understand the importance of the prevention of workplace harassment in the work environment. Research analyses what measures companies take in order to prevent workplace harassment and how is it monitored. As a primary research, interview findings of four Finnish companies (“Company X”, DHL Finland, ISS Palvelut and Management Institute...

  12. Causas do desmatamento da Amazônia: uma aplicação do teste de causalidade de Granger acerca das principais fontes de desmatamento nos municípios da Amazônia Legal brasileira

    Directory of Open Access Journals (Sweden)

    Marcelo Bentes Diniz

    2009-04-01

    Full Text Available Many are the factors indicated by the pertinent literature concerning the causes of deforestation in Brazilian Legal Amazon. From endogenous aspects as the edafo-climatic conditions to aspects related to anthropic action, like the population movements, urban growth, and especially, the independent or induced actions of the different public and private economic agents who have acted in the region, historically configuring the processes of occupation of the land and economic exploitation of the Amazonian region. The objective of this article is to perform a causality test, in the Granger sense, in the main variables suggested as important that explain the deforestation of the Legal Amazon, in the period from 1997 to 2006. The methodology to be used is based on dynamic models for the panel data, developed by Holtz-Eakin et al. (1988 and Arellano-Bond (1991 who developed a causality test based on the seminal article of Granger (1969. Among the main results found is the empirical evidence that there is a bidirectional causality between deforestation and the areas of permanent and temporary cultures, as well as the size of the cattle herd.

  13. On the Temporal Causal Relationship Between Macroeconomic Variables

    Directory of Open Access Journals (Sweden)

    Srinivasan Palamalai

    2014-02-01

    Full Text Available The present study examines the dynamic interactions among macroeconomic variables such as real output, prices, money supply, interest rate (IR, and exchange rate (EXR in India during the pre-economic crisis and economic crisis periods, using the autoregressive distributed lag (ARDL bounds test for cointegration, Johansen and Juselius multivariate cointegration test, Granger causality/Block exogeneity Wald test based on Vector Error Correction Model, variance decomposition analysis and impulse response functions. The empirical results reveal a stronger long-run bilateral relationship between real output, price level, IR, and EXR during the pre-crisis sample period. Moreover, the empirical results confirm a unidirectional short-run causality running from price level to EXR, IR to price level, and real output to money supply during the pre-crisis period. Also, it is evident from the test results that there exist short-run bidirectional relationships running between real output and EXR, price level and IR, and IR and EXR in the pre-crisis era, respectively. Most importantly, long-run bidirectional causality is found between real output, EXR, and IR during the economic crisis period. And the study results indicate short-run bidirectional causality between money supply and EXR, IR and price level, and IR and output in India during the crisis era. Also, a short-run unidirectional causality runs from prices to real output in the crisis period.

  14. Information flow and causality as rigorous notions ab initio

    Science.gov (United States)

    Liang, X. San

    2016-11-01

    Information flow or information transfer the widely applicable general physics notion can be rigorously derived from first principles, rather than axiomatically proposed as an ansatz. Its logical association with causality is firmly rooted in the dynamical system that lies beneath. The principle of nil causality that reads, an event is not causal to another if the evolution of the latter is independent of the former, which transfer entropy analysis and Granger causality test fail to verify in many situations, turns out to be a proven theorem here. Established in this study are the information flows among the components of time-discrete mappings and time-continuous dynamical systems, both deterministic and stochastic. They have been obtained explicitly in closed form, and put to applications with the benchmark systems such as the Kaplan-Yorke map, Rössler system, baker transformation, Hénon map, and stochastic potential flow. Besides unraveling the causal relations as expected from the respective systems, some of the applications show that the information flow structure underlying a complex trajectory pattern could be tractable. For linear systems, the resulting remarkably concise formula asserts analytically that causation implies correlation, while correlation does not imply causation, providing a mathematical basis for the long-standing philosophical debate over causation versus correlation.

  15. The causality between energy consumption and economic growth in Turkey

    Energy Technology Data Exchange (ETDEWEB)

    Erdal, Guelistan; Esenguen, Kemal [Department of Agricultural Economics, Faculty of Agriculture, Gaziosmanpasa University, 60240 Tokat (Turkey); Erdal, Hilmi [Department of Technical Programs, Tokat Vocational School, Gaziosmanpasa University, 60240 Tokat (Turkey)

    2008-10-15

    This paper applies the causality test to examine the causal relationship between primary energy consumption (EC) and real Gross National Product (GNP) for Turkey during 1970-2006. We employ unit root tests, the augmented Dickey-Fuller (ADF) and the Philips-Perron (PP), Johansen cointegration test, and Pair-wise Granger causality test to examine relation between EC and GNP. Our empirical results indicate that the two series are found to be non-stationary. However, first differences of these series lead to stationarity. Further, the results indicate that EC and GNP are cointegrated and there is bidirectional causality running from EC to GNP and vice versa. This means that an increase in EC directly affects economic growth and that economic growth also stimulates further EC. This bidirectional causality relationship between EC and GNP determined for Turkey at 1970-2006 period is in accordance with the ones in literature reported for similar countries. Consequently, we conclude that energy is a limiting factor to economic growth in Turkey and, hence, shocks to energy supply will have a negative impact on economic growth. (author)

  16. Effectiveness of Exchange Rate in Pakistan: Causality Analysis

    Directory of Open Access Journals (Sweden)

    Rana Ejaz Ali Khan

    2012-06-01

    Full Text Available The study analyzed the effectiveness of exchange rate on macroeconomic variables of Pakistan. The precise objective of the study is to examine the causality between exchange rate, trade, inflation, FDI and GDP through a series of models. On the annual time series data for the years 1980-2009 unit root test for stationarity, Johansen’s cointegration test for long-run equilibrium relationship between the variables for each model and Granger Causality test to check the causality between the variables is applied. The main findings are as: there is no long-run equilibrium relationship between exchange rate and inflation, but there exists long-run equilibrium relationship between exchange rate and trade. Thereis also long-run equilibrium relationship between exchange rate and FDI and causality runs in both directions, i.e. exchange rate to FDI and FDI to exchange rate. Finally, there is long-run equilibrium relationship between exchange rate and GDP but causality doesnot run in either direction.

  17. Ultraviolet radiation in Finland

    Energy Technology Data Exchange (ETDEWEB)

    Taalas, P.; Koskela, T.; Damski, J.; Supperi, A. [Finnish Meteorological Inst., Helsinki (Finland). Section of Ozone and UV Research; Kyroe, E. [Finnish Meteorological Inst., Sodankylae (Finland). Sodankylae Observatory

    1996-12-31

    Solar ultraviolet radiation is damaging for living organisms due to its high energy pro each photon. The UV radiation is often separated into three regions according to the wavelength: UVC (200-280 nm), UVB (280-320 nm) and UVA (320-400 nm). The most hazardous part, UVC is absorbed completely in the upper atmosphere by molecular oxygen. UVB radiation is absorbed by atmospheric ozone partly, and it is reaching Earth`s surface, as UVA radiation. Besides atmospheric ozone, very important factors in determining the intensity of UVB radiation globally are the solar zenith angle and cloudiness. It may be calculated from global ozone changes that the clear-sky UVB doses may have enhanced by 10-15 % during spring and 5-10 % during summer at the latitudes of Finland, following the decrease of total ozone between 1979-90. The Finnish ozone and UV monitoring activities have become a part of international activities, especially the EU Environment and Climate Programme`s research projects. The main national level effort has been the Finnish Academy`s climatic change programme, SILMU 1990-95. This presentation summarises the scientific results reached during the SILMU project

  18. Testing for causality in reconstructed state spaces by an optimized mixed prediction method

    Science.gov (United States)

    Krakovská, Anna; Hanzely, Filip

    2016-11-01

    In this study, a method of causality detection was designed to reveal coupling between dynamical systems represented by time series. The method is based on the predictions in reconstructed state spaces. The results of the proposed method were compared with outcomes of two other methods, the Granger VAR test of causality and the convergent cross-mapping. We used two types of test data. The first test example is a unidirectional connection of chaotic systems of Rössler and Lorenz type. The second one, the fishery model, is an example of two correlated observables without a causal relationship. The results showed that the proposed method of optimized mixed prediction was able to reveal the presence and the direction of coupling and distinguish causality from mere correlation as well.

  19. Analysis of services trade and employment in China by co-integration and causality

    Institute of Scientific and Technical Information of China (English)

    LIU Yu-lin; DAI Jun

    2007-01-01

    This article describes a study by co-integration test and Granger causality test on the relationships between China's services trades and employment using the data of services trade from the WTO website and the employment data from China Statistic Yearbook for the years from 1982 to 2003. Co-integration test showed that 1% increase in export value and import value of services created respectively 0.205% and 0.068 7% more job opportunities in the service sector. Both export and import of services impacted positively on employment in service industry, and export did more than import. However, in the short run, the impacts of services export and import on employment in service industry were both very small, though positive; and the impacts of employment in service industry on both export and import of services were very big, but not stable. Granger causality test indicated that employment in service industry was a Granger cause of services export. The findings highlight the importance of facilitating services import and reducing import barriers, and suggest that the competitiveness of China's labor-intensive services trade can be exploited to boost services export and help employment in service sector, and that the structure of services trade should be optimized by shifting from labor-intensive to knowledge-and technology-intensive services thus to enhance China's competitiveness of services export.

  20. Causal reasoning in physics

    CERN Document Server

    Frisch, Mathias

    2014-01-01

    Much has been written on the role of causal notions and causal reasoning in the so-called 'special sciences' and in common sense. But does causal reasoning also play a role in physics? Mathias Frisch argues that, contrary to what influential philosophical arguments purport to show, the answer is yes. Time-asymmetric causal structures are as integral a part of the representational toolkit of physics as a theory's dynamical equations. Frisch develops his argument partly through a critique of anti-causal arguments and partly through a detailed examination of actual examples of causal notions in physics, including causal principles invoked in linear response theory and in representations of radiation phenomena. Offering a new perspective on the nature of scientific theories and causal reasoning, this book will be of interest to professional philosophers, graduate students, and anyone interested in the role of causal thinking in science.

  1. Theories of Causality

    Science.gov (United States)

    Jones, Robert

    2010-03-01

    There are a wide range of views on causality. To some (e.g. Karl Popper) causality is superfluous. Bertrand Russell said ``In advanced science the word cause never occurs. Causality is a relic of a bygone age.'' At the other extreme Rafael Sorkin and L. Bombelli suggest that space and time do not exist but are only an approximation to a reality that is simply a discrete ordered set, a ``causal set.'' For them causality IS reality. Others, like Judea Pearl and Nancy Cartwright are seaking to build a complex fundamental theory of causality (Causality, Cambridge Univ. Press, 2000) Or perhaps a theory of causality is simply the theory of functions. This is more or less my take on causality.

  2. Economic growth and energy consumption in Algeria: a causality analysis; Croissance economique et consommation energetique en Algerie: une analyse en termes de causalite

    Energy Technology Data Exchange (ETDEWEB)

    Cherfi, S. [Faculte des Sciences Economiques, Sciences de Gestion et des Sciences Commerciales, Dept. des Sciences Commerciales, Universite d' Oran (Algeria)

    2011-07-15

    The purpose of this study is to review the causal link in the Granger sense, between energy consumption and economic growth in Algeria, to determine its implications for economic policy. The analysis was done based on Granger static and causality tests using statistical data on per capita primary energy consumption and gross domestic product per inhabitant in Algeria, over the 1965-2008 period. The results of the survey show that there is, in Algeria, a strong link between energy consumption per inhabitant and GDP per inhabitant. The results also suggest the lack of a long term impetus (no co-integration) between energy consumption and economic growth. In addition, there is a one-way causal link between GDP and energy consumption, i.e. the prior GDP data provides a better forecast of energy consumption level, but not the contrary. In other words, GDP explains consumption, not the contrary. (author)

  3. Causality Analysis of fMRI Data Based on the Directed Information Theory Framework.

    Science.gov (United States)

    Wang, Zhe; Alahmadi, Ahmed; Zhu, David C; Li, Tongtong

    2016-05-01

    This paper aims to conduct fMRI-based causality analysis in brain connectivity by exploiting the directed information (DI) theory framework. Unlike the well-known Granger causality (GC) analysis, which relies on the linear prediction technique, the DI theory framework does not have any modeling constraints on the sequences to be evaluated and ensures estimation convergence. Moreover, it can be used to generate the GC graphs. In this paper, first, we introduce the core concepts in the DI framework. Second, we present how to conduct causality analysis using DI measures between two time series. We provide the detailed procedure on how to calculate the DI for two finite-time series. The two major steps involved here are optimal bin size selection for data digitization and probability estimation. Finally, we demonstrate the applicability of DI-based causality analysis using both the simulated data and experimental fMRI data, and compare the results with that of the GC analysis. Our analysis indicates that GC analysis is effective in detecting linear or nearly linear causal relationship, but may have difficulty in capturing nonlinear causal relationships. On the other hand, DI-based causality analysis is more effective in capturing both linear and nonlinear causal relationships. Moreover, it is observed that brain connectivity among different regions generally involves dynamic two-way information transmissions between them. Our results show that when bidirectional information flow is present, DI is more effective than GC to quantify the overall causal relationship.

  4. Causality analysis in business performance measurement system using system dynamics methodology

    Science.gov (United States)

    Yusof, Zainuridah; Yusoff, Wan Fadzilah Wan; Maarof, Faridah

    2014-07-01

    One of the main components of the Balanced Scorecard (BSC) that differentiates it from any other performance measurement system (PMS) is the Strategy Map with its unidirectional causality feature. Despite its apparent popularity, criticisms on the causality have been rigorously discussed by earlier researchers. In seeking empirical evidence of causality, propositions based on the service profit chain theory were developed and tested using the econometrics analysis, Granger causality test on the 45 data points. However, the insufficiency of well-established causality models was found as only 40% of the causal linkages were supported by the data. Expert knowledge was suggested to be used in the situations of insufficiency of historical data. The Delphi method was selected and conducted in obtaining the consensus of the causality existence among the 15 selected expert persons by utilizing 3 rounds of questionnaires. Study revealed that only 20% of the propositions were not supported. The existences of bidirectional causality which demonstrate significant dynamic environmental complexity through interaction among measures were obtained from both methods. With that, a computer modeling and simulation using System Dynamics (SD) methodology was develop as an experimental platform to identify how policies impacting the business performance in such environments. The reproduction, sensitivity and extreme condition tests were conducted onto developed SD model to ensure their capability in mimic the reality, robustness and validity for causality analysis platform. This study applied a theoretical service management model within the BSC domain to a practical situation using SD methodology where very limited work has been done.

  5. Causality in Science

    Directory of Open Access Journals (Sweden)

    Cristina Puente Águeda

    2011-10-01

    Full Text Available Causality is a fundamental notion in every field of science. Since the times of Aristotle, causal relationships have been a matter of study as a way to generate knowledge and provide for explanations. In this paper I review the notion of causality through different scientific areas such as physics, biology, engineering, etc. In the scientific area, causality is usually seen as a precise relation: the same cause provokes always the same effect. But in the everyday world, the links between cause and effect are frequently imprecise or imperfect in nature. Fuzzy logic offers an adequate framework for dealing with imperfect causality, so a few notions of fuzzy causality are introduced.

  6. Bayesian Causal Induction

    CERN Document Server

    Ortega, Pedro A

    2011-01-01

    Discovering causal relationships is a hard task, often hindered by the need for intervention, and often requiring large amounts of data to resolve statistical uncertainty. However, humans quickly arrive at useful causal relationships. One possible reason is that humans use strong prior knowledge; and rather than encoding hard causal relationships, they encode beliefs over causal structures, allowing for sound generalization from the observations they obtain from directly acting in the world. In this work we propose a Bayesian approach to causal induction which allows modeling beliefs over multiple causal hypotheses and predicting the behavior of the world under causal interventions. We then illustrate how this method extracts causal information from data containing interventions and observations.

  7. When two become one: the limits of causality analysis of brain dynamics.

    Science.gov (United States)

    Chicharro, Daniel; Ledberg, Anders

    2012-01-01

    Biological systems often consist of multiple interacting subsystems, the brain being a prominent example. To understand the functions of such systems it is important to analyze if and how the subsystems interact and to describe the effect of these interactions. In this work we investigate the extent to which the cause-and-effect framework is applicable to such interacting subsystems. We base our work on a standard notion of causal effects and define a new concept called natural causal effect. This new concept takes into account that when studying interactions in biological systems, one is often not interested in the effect of perturbations that alter the dynamics. The interest is instead in how the causal connections participate in the generation of the observed natural dynamics. We identify the constraints on the structure of the causal connections that determine the existence of natural causal effects. In particular, we show that the influence of the causal connections on the natural dynamics of the system often cannot be analyzed in terms of the causal effect of one subsystem on another. Only when the causing subsystem is autonomous with respect to the rest can this interpretation be made. We note that subsystems in the brain are often bidirectionally connected, which means that interactions rarely should be quantified in terms of cause-and-effect. We furthermore introduce a framework for how natural causal effects can be characterized when they exist. Our work also has important consequences for the interpretation of other approaches commonly applied to study causality in the brain. Specifically, we discuss how the notion of natural causal effects can be combined with Granger causality and Dynamic Causal Modeling (DCM). Our results are generic and the concept of natural causal effects is relevant in all areas where the effects of interactions between subsystems are of interest.

  8. When two become one: the limits of causality analysis of brain dynamics.

    Directory of Open Access Journals (Sweden)

    Daniel Chicharro

    Full Text Available Biological systems often consist of multiple interacting subsystems, the brain being a prominent example. To understand the functions of such systems it is important to analyze if and how the subsystems interact and to describe the effect of these interactions. In this work we investigate the extent to which the cause-and-effect framework is applicable to such interacting subsystems. We base our work on a standard notion of causal effects and define a new concept called natural causal effect. This new concept takes into account that when studying interactions in biological systems, one is often not interested in the effect of perturbations that alter the dynamics. The interest is instead in how the causal connections participate in the generation of the observed natural dynamics. We identify the constraints on the structure of the causal connections that determine the existence of natural causal effects. In particular, we show that the influence of the causal connections on the natural dynamics of the system often cannot be analyzed in terms of the causal effect of one subsystem on another. Only when the causing subsystem is autonomous with respect to the rest can this interpretation be made. We note that subsystems in the brain are often bidirectionally connected, which means that interactions rarely should be quantified in terms of cause-and-effect. We furthermore introduce a framework for how natural causal effects can be characterized when they exist. Our work also has important consequences for the interpretation of other approaches commonly applied to study causality in the brain. Specifically, we discuss how the notion of natural causal effects can be combined with Granger causality and Dynamic Causal Modeling (DCM. Our results are generic and the concept of natural causal effects is relevant in all areas where the effects of interactions between subsystems are of interest.

  9. Organic food and farming research in Finland

    OpenAIRE

    Nykänen, Arja

    2006-01-01

    In Finland we have a tendency of increasing activities in organic food and farming research during last five years. Most of the organic food and farming research i Finland is carried out at the MTT Agrifood Research Finland. The rest is done at the universities and other institutes.

  10. Canadian Art Partnership Program in Finland

    Science.gov (United States)

    Ketovuori, Mikko

    2011-01-01

    This article is about a multidisciplinary R&D project in which a Canadian Learning Through The Arts (LTTA) program was imported to Finland in 2003-2004. Cultural differences in arts education in Finland and Canada are discussed. While Finland has a national school curriculum with all the arts included. Canada relies more on partnerships to…

  11. Energy consumption and GDP in Tunisia: Cointegration and causality analysis

    Energy Technology Data Exchange (ETDEWEB)

    Belloumi, Mounir [Institute of High Commercial Studies of Sousse, University of Sousse. B.P. 40 Street Ceiture, Sahloul III, 4054 Sousse (Tunisia)], E-mail: mounir.balloumi@gmail.com

    2009-07-15

    In this paper, the Johansen cointegration technique is used to examine the causal relationship between per capita energy consumption (PCEC) and per capita gross domestic product (PCGDP) for Tunisia during the 1971-2004 period. In order to test for Granger causality in the presence of cointegration among the variables, a vector error correction model (VECM) is used instead of a vector autoregressive (VAR) model. Our estimation results indicate that the PCGDP and PCEC for Tunisia are related by one cointegrating vector and that there is a long-run bi-directional causal relationship between the two series and a short-run unidirectional causality from energy to gross domestic product (GDP). The source of causation in the long-run is found to be the error-correction terms in both directions. Hence, an important policy implication resulting from this analysis is that energy can be considered as a limiting factor to GDP growth in Tunisia. Conclusions for Tunisia may also be relevant for a number of countries that have to go through a similar development path of increasing pressure on already scarce energy resources.

  12. Energy consumption and GDP in Tunisia Cointegration and causality analysis

    Energy Technology Data Exchange (ETDEWEB)

    Belloumi, Mounir [Institute of High Commercial Studies of Sousse, University of Sousse. B.P. 40 Street Ceiture, Sahloul III, 4054 Sousse (Tunisia)

    2009-07-15

    In this paper, the Johansen cointegration technique is used to examine the causal relationship between per capita energy consumption (PCEC) and per capita gross domestic product (PCGDP) for Tunisia during the 1971-2004 period. In order to test for Granger causality in the presence of cointegration among the variables, a vector error correction model (VECM) is used instead of a vector autoregressive (VAR) model. Our estimation results indicate that the PCGDP and PCEC for Tunisia are related by one cointegrating vector and that there is a long-run bi-directional causal relationship between the two series and a short-run unidirectional causality from energy to gross domestic product (GDP). The source of causation in the long-run is found to be the error-correction terms in both directions. Hence, an important policy implication resulting from this analysis is that energy can be considered as a limiting factor to GDP growth in Tunisia. Conclusions for Tunisia may also be relevant for a number of countries that have to go through a similar development path of increasing pressure on already scarce energy resources. (author)

  13. Causality for nonlocal phenomena

    CERN Document Server

    Eckstein, Michał

    2015-01-01

    Drawing from the theory of optimal transport we propose a rigorous notion of a causal relation for Borel probability measures on a given spacetime. To prepare the ground, we explore the borderland between causality, topology and measure theory. We provide various characterisations of the proposed causal relation, which turn out to be equivalent if the underlying spacetime has a sufficiently robust causal structure. We also present the notion of the 'Lorentz-Wasserstein distance' and study its basic properties. Finally, we discuss how various results on causality in quantum theory, aggregated around Hegerfeldt's theorem, fit into our framework.

  14. The relationship between crude oil spot and futures prices: Cointegration, linear and nonlinear causality

    Energy Technology Data Exchange (ETDEWEB)

    Bekiros, Stelios D.; Diks, Cees G.H. [Center for Nonlinear Dynamics in Economics and Finance (CeNDEF), Department of Quantitative Economics, University of Amsterdam, Roetersstraat 11, 1018 WB Amsterdam (Netherlands)

    2008-09-15

    The present study investigates the linear and nonlinear causal linkages between daily spot and futures prices for maturities of one, two, three and four months of West Texas Intermediate (WTI) crude oil. The data cover two periods October 1991-October 1999 and November 1999-October 2007, with the latter being significantly more turbulent. Apart from the conventional linear Granger test we apply a new nonparametric test for nonlinear causality by Diks and Panchenko after controlling for cointegration. In addition to the traditional pairwise analysis, we test for causality while correcting for the effects of the other variables. To check if any of the observed causality is strictly nonlinear in nature, we also examine the nonlinear causal relationships of VECM filtered residuals. Finally, we investigate the hypothesis of nonlinear non-causality after controlling for conditional heteroskedasticity in the data using a GARCH-BEKK model. Whilst the linear causal relationships disappear after VECM cointegration filtering, nonlinear causal linkages in some cases persist even after GARCH filtering in both periods. This indicates that spot and futures returns may exhibit asymmetric GARCH effects and/or statistically significant higher order conditional moments. Moreover, the results imply that if nonlinear effects are accounted for, neither market leads or lags the other consistently, videlicet the pattern of leads and lags changes over time. (author)

  15. Causalities between CO{sub 2}, electricity, and other energy variables during phase I and phase II of the EU ETS

    Energy Technology Data Exchange (ETDEWEB)

    Keppler, Jan Horst [Professor of Economics, CGEMP, Universite Paris-Dauphine, Place du Marechal de Lattre de Tassigny, 75775 Paris Cedex 16 (France); Mansanet-Bataller, Maria [CDC Climat Research and University of Valencia, Faculty of Economics, Department of Financial Economics, Av Tarongers s/n 46022 Valencia (Spain)

    2010-07-15

    The topic of this article is the analysis of the interplay between daily carbon, electricity and gas price data with the European Union Emission Trading System (EU ETS) for CO{sub 2} emissions. In a first step we have performed Granger causality tests for Phase I of the EU ETS (January 2005 until December 2007) and the first year of Phase II of the EU ETS (2008). The analysis includes both spot and forward markets - given the close interactions between the two sets of markets. The results show that during Phase I coal and gas prices, through the clean dark and spark spread, impacted CO{sub 2} futures prices, which in return Granger caused electricity prices. During the first year of the Phase II, the short-run rent capture theory (in which electricity prices Granger cause CO{sub 2} prices) prevailed. On the basis of the qualitative results of the Granger causality tests we obtained the formulation testable equations for quantitative analysis. Standard OLS regressions yielded statistically robust and theoretically coherent results. (author)

  16. Finland country report

    Energy Technology Data Exchange (ETDEWEB)

    Rantamaeki, Karin [VTT Technical Research Centre of Finland (Finland)

    2008-07-01

    engineering at Helsinki (TKK) and Lappeenranta (LUT) Universities of Technology; - Radiochemistry: University of Helsinki (UH); - Some activities in other universities too; - Finnish specialty in all technical areas is close connection of students with industry, research institutes and the authorities; Summer trainees; Diploma (Master's) theses; Special course at professional level after graduation covering whole area of nuclear safety: - For new staff and recruits from other fields (5 times, 270 participants), - Organised jointly by the Ministry of Employment and the Economy and all institutes in nuclear energy. 'Radiant Women' Seminar in 2007: For female decision makers and opinion leaders; Some 70 participants; Theme 'The climate changes - changes in everyday life'; Opening speech by Ms. Sirkka Hautojaervi, Permanent Secretary of the Ministry of the Environment; 'Finland and its adaptation to the climate change', senior researcher Susanna Kankaanpaeae, the Finnish Environment Institute; 'Prevention of climate change in everyday life', communications director Paeivi Laitila from Motiva; 'CO{sub 2}-studies and the effect of the sea on the climate change', senior researcher Heidi Pettersson, the Marine Research Institute. Christmas party in January for Energy Channel members who visited the research department of the Radiation and Nuclear Safety authority STUK. Number of Energy Channel members: {approx}80.

  17. Testing the Granger noncausality hypothesis in stationary nonlinear models of unknown functional form

    DEFF Research Database (Denmark)

    Péguin-Feissolle, Anne; Strikholm, Birgit; Teräsvirta, Timo

    In this paper we propose a general method for testing the Granger noncausality hypothesis in stationary nonlinear models of unknown functional form. These tests are based on a Taylor expansion of the nonlinear model around a given point in the sample space. We study the performance of our tests...

  18. Energy Consumption and Economic Growth in Algeria: Cointegration and Causality Analysis

    Directory of Open Access Journals (Sweden)

    Cherfi Souhila

    2012-01-01

    Full Text Available This study investigates the energy consumption-growth nexus in Algeria. The causal relationship between the logarithm of per capita energy consumption (LPCEC and the logarithm of per capita GDP (LPCGDP during the 1965-2008 period is examined using the threshold cointegration and Granger causality tests. The estimation results indicate that the LPCEC and LPCGDP for Algeria are non cointegrated and that there is a uni-directional causality running from LPCGDP to LPCEC, but not vice versa. The research results strongly support the neoclassical perspective that energy consumption is not a limiting factor to economic growth in Algeria. Accordingly, an important policy implication resulting from this analysis is that government can pursue the conservation energy policies that aim at curtailing energy use for environmental friendly development purposes without creating severe effects on economic growth. The energy should be efficiently allocated into more productive sectors of the economy.

  19. A study on causality between EBITDA and return of shares of brazilian companies (2008 - 2014

    Directory of Open Access Journals (Sweden)

    Cleyton de Oliveira Ritta

    2017-05-01

    Full Text Available The overall objective of the research was to identify the relationship between EBITDA and the return of shares of Brazilian companies listed on the BM&FBovespa, through the application of the Granger Causality Test. The research is characterized as descriptive, documentary with a quantitative approach. The results showed that the EBITDA margin on the net revenue was, on average, of 30.43% within the investigated period. Causal relationships occurred in 26 companies between the variables EBITDA (REBITDA Return and Return of Shares (RACAO.Research results do not allow a definitive conclusion about the influence of the EBITDA variable on the variable return of shares and vice versa, since there was a balance in the results according to the econometric test, confirming earlier studies.However, they do contribute to the literature by identifying causal relationship in a number of companies, which shows the relevance of accounting information to the capital markets.

  20. CAUSAL RELATIONSHIP BETWEEN FOSSIL FUEL CONSUMPTION AND ECONOMIC GROWTH IN JAPAN: A MULTIVARIATE APPROACH

    Directory of Open Access Journals (Sweden)

    Hazuki Ishida

    2013-01-01

    Full Text Available This paper explores whether Japanese economy can continue to grow without extensive dependence on fossil fuels. The paper conducts time series analysis using a multivariate model of fossil fuels, non-fossil energy, labor, stock and GDP to investigate the relationship between fossil fuel consumption and economic growth in Japan. The results of cointegration tests indicate long-run relationships among the variables. Using a vector error-correction model, the study reveals bidirectional causality between fossil fuels and GDP. The results also show that there is no causal relationship between non-fossil energy and GDP. The results of cointegration analysis, Granger causality tests, and variance decomposition analysis imply that non-fossil energy may not necessarily be able to play the role of fossil fuels. Japan cannot seem to realize both continuous economic growth and the departure from dependence on fossil fuels. Hence, growth-oriented macroeconomic policies should be re-examined.

  1. Application of adaptive nonlinear Granger causality: Disclosing network changes before and after absence seizure onset in a genetic rat model

    NARCIS (Netherlands)

    Sysoeva, M.V.; Sitnikova, E.Y.; Sysoev, I.V.; Bezruchko, B.P.; Luijtelaar, E.L.J.M. van

    2014-01-01

    Background: Advanced methods of signal analysis of the preictal and ictal activity dynamics characterizing absence epilepsy in humans with absences and in genetic animal models have revealed new and unknown electroencephalographic characteristics, that has led to new insights and theories. New metho

  2. Canonical correlation analysis and Wiener-Granger causality tests : Useful tools for the specification of VAR models

    NARCIS (Netherlands)

    Horvath, C.; Leeflang, P.S.H.; Otter, P.W.

    2002-01-01

    Dynamic multivariate models ha e become popular in analyzing the behavior of competitive marketing systems because they are capable of incorporating all the relationships in a competitive marketing environment. In this paper we consider VAR models, the most frequently used dynamic multivariate model

  3. Canonical correlation analysis and Wiener-Granger causality tests : Useful tools for the specification of VAR models

    NARCIS (Netherlands)

    Horvath, C.; Leeflang, P.S.H.; Otter, P.W.

    Dynamic multivariate models ha e become popular in analyzing the behavior of competitive marketing systems because they are capable of incorporating all the relationships in a competitive marketing environment. In this paper we consider VAR models, the most frequently used dynamic multivariate

  4. Energetic Causal Sets

    CERN Document Server

    Cortês, Marina

    2013-01-01

    We propose an approach to quantum theory based on the energetic causal sets, introduced in Cort\\^{e}s and Smolin (2013). Fundamental processes are causal sets whose events carry momentum and energy, which are transmitted along causal links and conserved at each event. Fundamentally there are amplitudes for such causal processes, but no space-time. An embedding of the causal processes in an emergent space-time arises only at the semiclassical level. Hence, fundamentally there are no commutation relations, no uncertainty principle and, indeed, no hbar. All that remains of quantum theory is the relationship between the absolute value squared of complex amplitudes and probabilities. Consequently, we find that neither locality, nor non locality, are primary concepts, only causality exists at the fundamental level.

  5. Causal Decision Trees

    OpenAIRE

    2015-01-01

    Uncovering causal relationships in data is a major objective of data analytics. Causal relationships are normally discovered with designed experiments, e.g. randomised controlled trials, which, however are expensive or infeasible to be conducted in many cases. Causal relationships can also be found using some well designed observational studies, but they require domain experts' knowledge and the process is normally time consuming. Hence there is a need for scalable and automated methods for c...

  6. How to be causal

    CERN Document Server

    Kinsler, Paul

    2011-01-01

    I explain a simple definition of causality in widespread use, and indicate how it links to the Kramers Kronig relations. The specification of causality in terms of temporal differential eqations then shows us the way to write down dynamical models so that their causal nature in the sense used here should be obvious to all. In particular, I apply this reasoning to Maxwell's equations, which is an instructive example since their casual properties are sometimes debated.

  7. STRUCTURAL BREAKS, COINTEGRATION, AND CAUSALITY BY VECM ANALYSIS OF CRUDE OIL AND FOOD PRICE

    Directory of Open Access Journals (Sweden)

    Aynur Pala

    2013-01-01

    Full Text Available This papers investigated form of the linkage beetwen crude oil price index and food price index, using Johansen Cointegration test, and Granger Causality by VECM. Empirical results for monthly data from 1990:01 to 2011:08 indicated that evidence for breaks after 2008:08 and 2008:11. We find a clear long-run relationship between these series for the full and sub sample. Cointegration regression coefficient is negative at the 1990:01-2008:08 time period, but adversely positive at the 2008:11-2011:08 time period. This results represent that relation between crude oil and food price chanced.

  8. A multivariate causality test of carbon dioxide emissions, energy consumption and economic growth in China

    Energy Technology Data Exchange (ETDEWEB)

    Chang, Ching-Chih [Department of Transportation and Communication Management Science, National Cheng Kung University, No. 1, University Road, Tainan 70101 (China)

    2010-11-15

    This paper uses multivariate co-integration Granger causality tests to investigate the correlations between carbon dioxide emissions, energy consumption and economic growth in China. Some researchers have argued that the adoption of a reduction in carbon dioxide emissions and energy consumption as a long term policy goal will result in a closed-form relationship, to the detriment of the economy. Therefore, a perspective that can make allowances for the fact that the exclusive pursuit of economic growth will increase energy consumption and CO{sub 2} emissions is required; to the extent that such growth will have adverse effects with regard to global climate change. (author)

  9. Government Expenditure, Defense Expenditure and Economic Growth: a Causality Analysis for BRICS

    Directory of Open Access Journals (Sweden)

    Salman Ali Shah

    2016-12-01

    Full Text Available This paper empirically examines the effects of civilian and military portions of government expenditure on economic growth of five key emerging economies Brazil, Russia, India, China and South Africa (BRICS. We ran separate Cointegration and Granger causality tests for each country using data taken from WDI and SIPRI while taking account of the limitations of time series data. We got interestingly different effects of military expenditure on economic growth across countries especially for the three nuclear powers Russia, India and China. India and Brazil showed negative, Russia and China showed positive while South Arica showed no effect on economic growth in terms of government civilian expenditure.

  10. Utilização do custo-meta por empresas brasileiras como estratégia de gestão: alguns estudos setoriais utilizando o método da causalidade de Granger

    Directory of Open Access Journals (Sweden)

    Marcos Antonio Souza

    2005-12-01

    Full Text Available Este artigo tem como objetivo básico desenvolver, com apoio no teste de causalidade de Granger, uma técnica de pesquisa que possa avaliar, no agregado de empresas e como uma alternativa ao estudo de caso, as estratégias de preços adotadas por empresas brasileiras. Em especial, busca-se distinguir aquelas empresas que adotam o custometa como estratégia, em relação àquelas empresas que adotam o custo mais margem ou, ainda, daquelas que não apresentam uma estratégia clara de preços e custos. Quarenta e sete empresas, de oito setores distintos, foram analisadas mediante a utilização do método de causalidade de Granger. Os resultados evidenciaram a falta de estratégia com relação à gestão de preços e custos das empresas, na maioria dos casos. Em particular, a hipótese da estratégia de custo-meta predominou somente no setor de distribuição de energia elétrica. Os resultados apresentados são suscetíveis a várias contribuições e podem servir como uma agenda para futuras pesquisas.This article aims to develop, based on the Granger-causality test, a research technique to assess, in business sectors and as an alternative for case studies, the price strategies adopted by Brazilian companies. It focuses on the differentiation between those companies which use target costing as a strategy from those using the cost plus margin, or yet, from companies without a clear strategy for establishing prices and costs. Forty-seven companies from eight different segments were analyzed through Granger causality. In most cases, the results revealed a lack of strategy in terms of company price and cost management. Target costing was only predominant in the electric power distribution sector. The research results suggest possibilities for future studies.

  11. Cointegration and Causality Test Among Export, Import, and Foreign Exchange

    Directory of Open Access Journals (Sweden)

    Haryono Subiyakto

    2016-06-01

    Full Text Available The rupiah exchange rate, import, and export are the important indicators in economy, including the Indonesia economy. The debate regarding the relationship among the exchange rate, import, and export has been persisting for several decades. Some researchers found that there is a relationship among those three and others explained that there is no correlation among them. The aim of this research is to obtain the empirical evidence of the causal relationship among the export, import, and foreign exchange rate by using the monthly data from January 2010 to April 2014. The export and import data are the export and import values in US dollar. The exchange rate data is the median exchange rates of the Indonesian Bank. The Johansen Cointegration Test and the Granger Causality Test are used to analyze the data. The research result shows that export and import have no causal relationship at five percent. Next, the foreign exchange rate influences the export and import at 10 percent level. The result indicates that the foreign exchange rate has small effects on the export and import. Based on the results, the government should control the balance of trade and should not make any policy that is based on the exchange rate values. Finally, it can be said that the exchange rate policy is not effective in increasing the exports and reducing the imports.

  12. Editorial: Causal cognition

    NARCIS (Netherlands)

    Blaisdell, A.P.; Beckers, T.

    2009-01-01

    The article discusses various reports published within the issue, including one on psychological approaches to causal discovery in humans, one on the representational and reasoning capacities that underlie causal cognition in rats and one on the generality of knowledge of Great Ape.

  13. Causality in Classical Electrodynamics

    Science.gov (United States)

    Savage, Craig

    2012-01-01

    Causality in electrodynamics is a subject of some confusion, especially regarding the application of Faraday's law and the Ampere-Maxwell law. This has led to the suggestion that we should not teach students that electric and magnetic fields can cause each other, but rather focus on charges and currents as the causal agents. In this paper I argue…

  14. Causality and Lifshitz Holography

    Energy Technology Data Exchange (ETDEWEB)

    Koroteev, Peter [Department of Physics and Astronomy, University of Minnesota, 116 Church Street S.E., Minneapolis, MN 55455 (United States)

    2011-07-15

    We study signal propagation in theories with Lifshitz scaling using the gravity dual and show that backgrounds with z<1 are incompatible with causality of the strongly coupled theory. We argue that causality violations in z<1 theories show up in boundary correlation functions as superluminal modes.

  15. The Systemic, Long-run Relation among Gasoline Demand, Gasoline Price, Income, and Vehicle Ownership in OECD Countries: Evidence from Panel Cointegration and Causality Modeling

    OpenAIRE

    Liddle, Brantley

    2012-01-01

    This paper analyzes gasoline consumption per capita, income (GDP per capita), gasoline price, and car ownership per capita for a panel of OECD countries by employing panel unit root and cointegration testing, panel Dynamic and Fully Modified OLS estimations, and panel Granger-causality tests. The four variables are determined to be panel I(1) and cointegrated. Estimated long-run and short-run income elasticities are smaller than what typically had been found previously. Lastly, gasoline consu...

  16. Pull factors of Finland and voluntary work

    OpenAIRE

    Jurvakainen, Janika

    2016-01-01

    This thesis studies pull factors of Finland and voluntary work. The aim of this study is to understand the pull factors of Finland from the perspective of young travelers. Which pull factors attract to choose Finland as their destination? In addition, which pull factors attract young travelers to participate in international voluntary work? The commissioner of this thesis is Allianssi Youth Exchange. The thesis is research-based and includes a quantitative Webropol survey and some qualit...

  17. Causality in Europeanization Research

    DEFF Research Database (Denmark)

    Lynggaard, Kennet

    2012-01-01

    Discourse analysis as a methodology is perhaps not readily associated with substantive causality claims. At the same time the study of discourses is very much the study of conceptions of causal relations among a set, or sets, of agents. Within Europeanization research we have seen endeavours...... to develop discursive institutional analytical frameworks and something that comes close to the formulation of hypothesis on the effects of European Union (EU) policies and institutions on domestic change. Even if these efforts so far do not necessarily amount to substantive theories or claims of causality......, it suggests that discourse analysis and the study of causality are by no means opposites. The study of Europeanization discourses may even be seen as an essential step in the move towards claims of causality in Europeanization research. This chapter deals with the question of how we may move from the study...

  18. Agency, time, and causality.

    Science.gov (United States)

    Widlok, Thomas

    2014-01-01

    Cognitive Scientists interested in causal cognition increasingly search for evidence from non-Western Educational Industrial Rich Democratic people but find only very few cross-cultural studies that specifically target causal cognition. This article suggests how information about causality can be retrieved from ethnographic monographs, specifically from ethnographies that discuss agency and concepts of time. Many apparent cultural differences with regard to causal cognition dissolve when cultural extensions of agency and personhood to non-humans are taken into account. At the same time considerable variability remains when we include notions of time, linearity and sequence. The article focuses on ethnographic case studies from Africa but provides a more general perspective on the role of ethnography in research on the diversity and universality of causal cognition.

  19. Non-Causal Computation

    Directory of Open Access Journals (Sweden)

    Ämin Baumeler

    2017-07-01

    Full Text Available Computation models such as circuits describe sequences of computation steps that are carried out one after the other. In other words, algorithm design is traditionally subject to the restriction imposed by a fixed causal order. We address a novel computing paradigm beyond quantum computing, replacing this assumption by mere logical consistency: We study non-causal circuits, where a fixed time structure within a gate is locally assumed whilst the global causal structure between the gates is dropped. We present examples of logically consistent non-causal circuits outperforming all causal ones; they imply that suppressing loops entirely is more restrictive than just avoiding the contradictions they can give rise to. That fact is already known for correlations as well as for communication, and we here extend it to computation.

  20. Causality in demand

    DEFF Research Database (Denmark)

    Nielsen, Max; Jensen, Frank; Setälä, Jari;

    2011-01-01

    This article focuses on causality in demand. A methodology where causality is imposed and tested within an empirical co-integrated demand model, not prespecified, is suggested. The methodology allows different causality of different products within the same demand system. The methodology is applied...... to fish demand. On the German market for farmed trout and substitutes, it is found that supply sources, i.e. aquaculture and fishery, are not the only determinant of causality. Storing, tightness of management and aggregation level of integrated markets might also be important. The methodological...... implication is that more explicit focus on causality in demand analyses provides improved information. The results suggest that frozen trout forms part of a large European whitefish market, where prices of fresh trout are formed on a relatively separate market. Redfish is a substitute on both markets...

  1. Agency, time and causality

    Directory of Open Access Journals (Sweden)

    Thomas eWidlok

    2014-11-01

    Full Text Available Cognitive Scientists interested in causal cognition increasingly search for evidence from non-WEIRD people but find only very few cross-cultural studies that specifically target causal cognition. This article suggests how information about causality can be retrieved from ethnographic monographs, specifically from ethnographies that discuss agency and concepts of time. Many apparent cultural differences with regard to causal cognition dissolve when cultural extensions of agency and personhood to non-humans are taken into account. At the same time considerable variability remains when we include notions of time, linearity and sequence. The article focuses on ethnographic case studies from Africa but provides a more general perspective on the role of ethnography in research on the diversity and universality of causal cognition.

  2. Regression to Causality

    DEFF Research Database (Denmark)

    Bordacconi, Mats Joe; Larsen, Martin Vinæs

    2014-01-01

    Humans are fundamentally primed for making causal attributions based on correlations. This implies that researchers must be careful to present their results in a manner that inhibits unwarranted causal attribution. In this paper, we present the results of an experiment that suggests regression...... models – one of the primary vehicles for analyzing statistical results in political science – encourage causal interpretation. Specifically, we demonstrate that presenting observational results in a regression model, rather than as a simple comparison of means, makes causal interpretation of the results...... of equivalent results presented as either regression models or as a test of two sample means. Our experiment shows that the subjects who were presented with results as estimates from a regression model were more inclined to interpret these results causally. Our experiment implies that scholars using regression...

  3. 75 FR 30431 - Carboxymethylcellulose from Finland, Mexico, Netherlands, and Sweden

    Science.gov (United States)

    2010-06-01

    ... COMMISSION Carboxymethylcellulose from Finland, Mexico, Netherlands, and Sweden AGENCY: United States... on carboxymethylcellulose from Finland, Mexico, Netherlands, and Sweden. SUMMARY: The Commission... carboxymethylcellulose from Finland, Mexico, Netherlands, and Sweden would be likely to lead to continuation...

  4. Causality between income and emission. A country group-specific econometric analysis

    Energy Technology Data Exchange (ETDEWEB)

    Coondoo, Dipankor [Economic Research Unit, Indian Statistical Institute, 203 B.T. Road, 35 Kolkata (India); Dinda, Soumyananda [S.R. Fatepuria College, Beldanga, West Bengal, Murshidabad (India)

    2002-03-01

    Empirical studies of the Environmental Kuznets Curve (EKC) examine the presence or otherwise of an inverted U-shaped relationship between the level of pollution and the level of income. Customarily, in the diagram of EKC the level of income is shown on the horizontal axis and that of pollution on the vertical axis. Thus, it is presumed that the relationship between income and pollution is one of unidirectional causality with income causing environmental changes and not vice versa. The validity of this presumption is now being questioned. It is being asserted that the nature and direction of causality may vary from one country to the other. In this paper, we present the results of a study of income-CO{sub 2} emission causality based on a Granger causality test to cross-country panel data on per capita income and the corresponding per capita CO{sub 2} emission data. Briefly, our results indicate three different types of causality relationship holding for different country groups. For the developed country groups of North America and Western Europe (and also for Eastern Europe) the causality is found to run from emission to income. For the country groups of Central and South America, Oceania and Japan causality from income to emission is obtained. Finally, for the country groups of Asia and Africa the causality is found to be bi-directional. The regression equations estimated as part of the Granger causality test further suggest that for the country groups of North America and Western Europe the growth rate of emission has become stationary around a zero mean, and a shock in the growth rate of emission tends to generate a corresponding shock in the growth rate of income. In contrast, for the country groups of Central and South America, Oceania and Japan a shock in the income growth rate is likely to result in a corresponding shock in the growth rate of emission. Finally, causality being bi-directional for the country groups of Asia and Africa, the income and the

  5. Altered causal connectivity of resting state brain networks in amnesic MCI.

    Directory of Open Access Journals (Sweden)

    Peipeng Liang

    Full Text Available Most neuroimaging studies of resting state networks in amnesic mild cognitive impairment (aMCI have concentrated on functional connectivity (FC based on instantaneous correlation in a single network. The purpose of the current study was to investigate effective connectivity in aMCI patients based on Granger causality of four important networks at resting state derived from functional magnetic resonance imaging data--default mode network (DMN, hippocampal cortical memory network (HCMN, dorsal attention network (DAN and fronto-parietal control network (FPCN. Structural and functional MRI data were collected from 16 aMCI patients and 16 age, gender-matched healthy controls. Correlation-purged Granger causality analysis was used, taking gray matter atrophy as covariates, to compare the group difference between aMCI patients and healthy controls. We found that the causal connectivity between networks in aMCI patients was significantly altered with both increases and decreases in the aMCI group as compared to healthy controls. Some alterations were significantly correlated with the disease severity as measured by mini-mental state examination (MMSE, and California verbal learning test (CVLT scores. When the whole-brain signal averaged over the entire brain was used as a nuisance co-variate, the within-group maps were significantly altered while the between-group difference maps did not. These results suggest that the alterations in causal influences may be one of the possible underlying substrates of cognitive impairments in aMCI. The present study extends and complements previous FC studies and demonstrates the coexistence of causal disconnection and compensation in aMCI patients, and thus might provide insights into biological mechanism of the disease.

  6. Causally symmetric spacetimes

    Energy Technology Data Exchange (ETDEWEB)

    Tipler, F.J.

    1977-08-01

    Causally symmetric spacetimes are spacetimes with J/sup +/(S) isometric to J/sup -/(S) for some set S. We discuss certain properties of these spacetimes, showing for example that, if S is a maximal Cauchy surface with matter everywhere on S, then the spacetime has singularities in both J/sup +/(S) and J/sup -/(S). We also consider totally vicious spacetimes, a class of causally symmetric spacetimes for which I/sup +/(p) =I/sup -/(p) = M for any point p in M. Two different notions of stability in general relativity are discussed, using various types of causally symmetric spacetimes as starting points for perturbations.

  7. Linear and nonlinear causality between renewable energy consumption and economic growth in the USA

    Directory of Open Access Journals (Sweden)

    Haiyun Xu

    2016-12-01

    Full Text Available This study aims to investigate Granger causality between renewable energy consumption (REC and economic growth (EG for USA. To accomplish this objective and to add the stronger evidence to the controversial issue, the tests were done under a new framework that embeds wavelet analysis, a novel tool, in nonlinear causality test approaches developed recently. The classical linear causality test procedure was also involved for comparison. The empirical data sources from the USA Energy Information Administration and Economist Intelligence Unit (EIU CountryData database. Sample period is from January 1993 to October 2014. The results indicate significantly the existence of unidirectional causality from EG to REC and support the conservation hypothesis. In additional, further evidences show that the causal relationship among them is not constant and depends on the time scale or frequency ranges, and that wavelet analysis is an important aid to capture the nonlinear causality. This suggests that renewable energy limitations do not seem to damage economic growth. These results have implications of importance for research analysts as well as policy makers of energy economy.

  8. Identifying Seizure Onset Zone From the Causal Connectivity Inferred Using Directed Information

    Science.gov (United States)

    Malladi, Rakesh; Kalamangalam, Giridhar; Tandon, Nitin; Aazhang, Behnaam

    2016-10-01

    In this paper, we developed a model-based and a data-driven estimator for directed information (DI) to infer the causal connectivity graph between electrocorticographic (ECoG) signals recorded from brain and to identify the seizure onset zone (SOZ) in epileptic patients. Directed information, an information theoretic quantity, is a general metric to infer causal connectivity between time-series and is not restricted to a particular class of models unlike the popular metrics based on Granger causality or transfer entropy. The proposed estimators are shown to be almost surely convergent. Causal connectivity between ECoG electrodes in five epileptic patients is inferred using the proposed DI estimators, after validating their performance on simulated data. We then proposed a model-based and a data-driven SOZ identification algorithm to identify SOZ from the causal connectivity inferred using model-based and data-driven DI estimators respectively. The data-driven SOZ identification outperforms the model-based SOZ identification algorithm when benchmarked against visual analysis by neurologist, the current clinical gold standard. The causal connectivity analysis presented here is the first step towards developing novel non-surgical treatments for epilepsy.

  9. IN TURKEY ECONOMICS CAUSALITY RELATIONSHIP AMONG ECONOMIC GROWTH, EXPORT AND EXIMBANK LOANS: 2002- 2015

    Directory of Open Access Journals (Sweden)

    Serpil ERGÜN BÜLBÜL

    2016-08-01

    Full Text Available In this study, the causality relationship among economic growth, exports and Eximbank loans was examined by using the data that Turkey’s post-transition program to strong economy in the period (2002:Q1-2015:Q3. In the context of causality process, firstly, stationarity is investigated by using Augmented Dickey-Fuller (ADF unit root test, long-term relationship is investigated by using Johansen co-integration test and then causality relationship is examined by using Granger test and impulse response analysis is carried out.According to the results of causality analysis, a bidirectional causality between exports and economic growth and a unilateral causality from exports to Eximbank loans have been obversed. In the results of cointegration analysis, a long-term relationship between exports and Eximbank loans could not be detected. Also it was analyzed by impulse-response analysis with the help of graphs how each variables reacts to different shock in 8 quarters.

  10. Causal Links between Foreign Direct Investments and Trade: A Comparative Study of India and China

    Directory of Open Access Journals (Sweden)

    Renu SHARMA

    2013-05-01

    Full Text Available Global economic environment is changing rapidly during the last two decades. This change is reflected in widening and intensifying international linkages in trade and FDI. Various countries are now favouring economic reforms for attaining rapid and sustained growth. The scope for transnational production has expended due to reduction of the barriers to international trade and the various regional integration agreements between the different countries. This paper examines the causal relationships between FDI and trade (i.e Exports and Imports in India and China. Granger causality test has been employed to examine the causal relation between FDI and trade by using the data over the period of 1976-2011.The results for China show unidirectional causality running from FDI to imports and FDI to exports, however, there exist bidirectional causality between imports and exports. India gives the results which are not similar to China where bidirectional causality between FDI and imports; FDI and exports; and exports and imports have been found.

  11. Greenfield nuclear power for Finland

    Energy Technology Data Exchange (ETDEWEB)

    Saarenpaa, Tapio

    2010-09-15

    In Finland, licensing for new nuclear power is ongoing. The political approval is to be completed in 2010. Fennovoima's project is unique in various ways: (i) the company was established only in 2007, (ii) its ownership includes a mixture of local energy companies, electricity-intensive industries and international nuclear competence through E.ON, and (iii) it has two alternative greenfield sites. There are five prerequisites for a successful nuclear power project in a transparent democracy of today: (1) need for additional power capacity, (2) actor prepared to invest, (3) established competence, (4) available site, (5) open communications, and (6) favorable public opinion.

  12. Area Handbook Series: Finland: A Country Study

    Science.gov (United States)

    1988-12-01

    Peggy Pixley. David P. Cabitto, who was assisted by Sandra K. Cotugno and Kimberly A. Lord, provided invaluable graphics support. Stan- ley M. Sciora...Right Wing in Finland (Rus- sian and East European Series, 22.). Bloomington: Indiana University Press, 1962. Runeberg, Carl Michael. Finlands Historia

  13. What Lessons Does Finland Give:Characteristics of Education in Finland%What Lessons Does Finland Give: Characteristics of Education in Finland

    Institute of Scientific and Technical Information of China (English)

    陈曦

    2016-01-01

    Finland became outstanding on the world's list of education after 2000 in the following PISA conducted by OECD in 2000, 2003, 2006, 2009. There are still many lessons that can be drawn from the sound education system in Finland which lead to its success of education: equality, lifelong learning, and teacher education.

  14. Causal Newton Gravity Law

    CERN Document Server

    Zinoviev, Yury M

    2012-01-01

    The equations of the relativistic causal Newton gravity law for the planets of the solar system are studied in the approximation when the Sun rests at the coordinates origin and the planets do not iteract between each other.

  15. Causal spin foams

    CERN Document Server

    Immirzi, Giorgio

    2016-01-01

    I discuss how to impose causality on spin-foam models, separating forward and backward propagation, turning a given triangulation to a 'causal set', and giving asymptotically the exponential of the Regge action, not a cosine. I show the equivalence of the prescriptions which have been proposed to achieve this. Essential to the argument is the closure condition for the 4-simplices, all made of space-like tetrahedra.

  16. Quantum Causal Graph Dynamics

    CERN Document Server

    Arrighi, Pablo

    2016-01-01

    Consider a graph having quantum systems lying at each node. Suppose that the whole thing evolves in discrete time steps, according to a global, unitary causal operator. By causal we mean that information can only propagate at a bounded speed, with respect to the distance given by the graph. Suppose, moreover, that the graph itself is subject to the evolution, and may be driven to be in a quantum superposition of graphs---in accordance to the superposition principle. We show that these unitary causal operators must decompose as a finite-depth circuit of local unitary gates. This unifies a result on Quantum Cellular Automata with another on Reversible Causal Graph Dynamics. Along the way we formalize a notion of causality which is valid in the context of quantum superpositions of time-varying graphs, and has a number of good properties. Keywords: Quantum Lattice Gas Automata, Block-representation, Curtis-Hedlund-Lyndon, No-signalling, Localizability, Quantum Gravity, Quantum Graphity, Causal Dynamical Triangula...

  17. Systemic risk and causality dynamics of the world international shipping market

    Science.gov (United States)

    Zhang, Xin; Podobnik, Boris; Kenett, Dror Y.; Eugene Stanley, H.

    2014-12-01

    Various studies have reported that many economic systems have been exhibiting an increase in the correlation between different market sectors, a factor that exacerbates the level of systemic risk. We measure this systemic risk of three major world shipping markets, (i) the new ship market, (ii) the second-hand ship market, and (iii) the freight market, as well as the shipping stock market. Based on correlation networks during three time periods, that prior to the financial crisis, during the crisis, and after the crisis, minimal spanning trees (MSTs) and hierarchical trees (HTs) both exhibit complex dynamics, i.e., different market sectors tend to be more closely linked during financial crisis. Brownian distance correlation and Granger causality test both can be used to explore the directional interconnectedness of market sectors, while Brownian distance correlation captures more dependent relationships, which are not observed in the Granger causality test. These two measures can also identify and quantify market regression periods, implying that they contain predictive power for the current crisis.

  18. Causality and correlations between BSE and NYSE indexes: A Janus faced relationship

    Science.gov (United States)

    Neeraj; Panigrahi, Prasanta K.

    2017-09-01

    We study the multi-scale temporal correlations and causality connections between the New York Stock Exchange (NYSE) and Bombay Stock Exchange (BSE) monthly average closing price indexes for a period of 300 months, encompassing the time period of the liberalisation of the Indian economy and its gradual global exposure. In multi-scale analysis; clearly identifiable 1, 2 and 3 year non-stationary periodic modulations in NYSE and BSE have been observed, with NYSE commensurating changes in BSE at 3 years scale. Interestingly, at one year time scale, the two exchanges are phase locked only during the turbulent times, while at the scale of three year, in-phase nature is observed for a much longer time frame. The two year time period, having characteristics of both one and three year variations, acts as the transition regime. The normalised NYSE's stock value is found to Granger cause those of BSE, with a time lag of 9 months. Surprisingly, observed Granger causality of high frequency variations reveals BSE behaviour getting reflected in the NYSE index fluctuations, after a smaller time lag. This Janus faced relationship, shows that smaller stock exchanges may provide a natural setting for simulating market fluctuations of much bigger exchanges. This possibly arises due to the fact that high frequency fluctuations form an universal part of the financial time series, and are expected to exhibit similar characteristics in open market economies.

  19. On the causal dynamics between emissions, nuclear energy, renewable energy, and economic growth

    Energy Technology Data Exchange (ETDEWEB)

    Apergis, Nicholas [Department of Banking and Financial Management, University of Piraeus, Karaoli and Dimitriou 80, Piraeus, ATTIKI 18534 (Greece); Payne, James E. [Department of Economics, Illinois State University, Normal, IL 61790-4200 (United States); Menyah, Kojo [London Metropolitan Business School, London Metropolitan University, 84 Moorgate, London, EC2M 6SQ (United Kingdom); Wolde-Rufael, Yemane

    2010-09-15

    This paper examines the causal relationship between CO{sub 2} emissions, nuclear energy consumption, renewable energy consumption, and economic growth for a group of 19 developed and developing countries for the period 1984-2007 using a panel error correction model. The long-run estimates indicate that there is a statistically significant negative association between nuclear energy consumption and emissions, but a statistically significant positive relationship between emissions and renewable energy consumption. The results from the panel Granger causality tests suggest that in the short-run nuclear energy consumption plays an important role in reducing CO{sub 2} emissions whereas renewable energy consumption does not contribute to reductions in emissions. This may be due to the lack of adequate storage technology to overcome intermittent supply problems as a result electricity producers have to rely on emission generating energy sources to meet peak load demand. (author)

  20. Causality Relationship Between Import, Export and Growth Rate in Developing Countries

    Directory of Open Access Journals (Sweden)

    Serhat YUKSEL

    2017-06-01

    Full Text Available In this paper, we tried to determine the relationship between imports, exports and growth rate in developing countries. Within this scope, 6 developing countries (Argentina, Brazil, China, Malaysia, Mexico and Turkey were analyzed in this study. In order to achieve this purpose, annual data for the periods between 1961 and 2014 was tested by using Engle Granger co-integration analysis, Vector Error Correction Model and Toda Yamamoto causality analysis. According to the result of the analysis, it was determined that there is not any relationship among three variables in Brazil and Mexico. On the other hand, we defined that increase in export causes higher growth rate in Argentina. Moreover, it was concluded that there is a causal relationship from import to export in China and Turkey. Furthermore, it was determined that export causes higher import in Malaysia. Therefore, it can be concluded that the relationship between import, export and growth rate is not same for all developing countries..

  1. INVESTIGATION ON THE CAUSAL RELATIONSHIP BETWEEN INFLATION, OUTPUT GROWTH AND THEIR UNCERTAINTIES IN ROMANIA

    Directory of Open Access Journals (Sweden)

    Mircea ASANDULUI

    2016-11-01

    Full Text Available Based on monthly-recorded data for the 1990-2014 period related to output growth and inflation, we use heteroskedastic models in order to estimate the nominal and real uncertainty in Romania. Real uncertainty is derived from output growth volatility and nominal uncertainty is derived from inflation volatility. Of the 12 possible hypotheses regarding causal relationships between output growth, inflation, nominal uncertainty and real uncertainty, we consider 7 hypotheses for which we find strong theoretical arguments and empirical evidence in literature. In order to ensure the robustness of the results, the Granger-causality tests are performed for 4, 8 and 12 lags, which are then used to test 7 economic hypotheses.

  2. Investigation of Causal Relationship between Stock Prices and Trading Volume using Toda and Yamamoto Procedure

    Directory of Open Access Journals (Sweden)

    Sushil BAJAJ

    2014-11-01

    Full Text Available The present study probes the relationship between the stock prices and trading volume. For achieving this purpose, daily data of adjusted closing stock prices, trading volume of 39 individual securities and S&P CNX Nifty from January 1, 1998 to May 31, 2013 have been used. In this study, instead of applying ordinary Granger causality test to investigate the relationship between stock prices and trading volume, Toda and Yamamoto (1995 procedure has been applied for analyzing the data. Lag length chosen by AIC and FPE criterion has been insured by running Lagrange Multiplier (LM test and causality determined by Toda and Yamamoto test has also been confirmed by using VAR methodology. Although, Toda and Yamamoto and VAR test produced little dissimilar results, nevertheless, the empirical analysis provides sufficient grounds to declare the presence of interaction between stock prices and trading volume.

  3. DISAGGREGATE ENERGY CONSUMPTION AND TOTAL FACTOR PRODUCTIVITY: A COINTEGRATION AND CAUSALITY ANALYSIS FOR THE TURKISH ECONOMY.

    Directory of Open Access Journals (Sweden)

    Can Tansel Tugcu

    2013-01-01

    Full Text Available The aim of this study is to investigate the long and the short-run relationships between disaggregate energy consumption (i.e. alternative and nuclear, fossil and renewable and total factor productivity growth in the Turkish economy for the period 1970-2011. To this end, ARDL bounds testing approach to cointegration and the Dolado and Lütkepohl’s Granger causality analyses were employed. Results showed that disaggregate energy consumption is cointegrated to total factor productivity growth and there exists bi-directional causal relationships among the variables in consideration. Besides, findings revealed that the share of renewable energy consumption in total energy consumption is the only energy type which positively affects total factor productivity growth in the Turkish economy. This result implies that an improvement in the share of renewable energy consumption in total energy consumption is crucial for economic efficiency.

  4. On the causal links between FDI and growth in developing countries

    DEFF Research Database (Denmark)

    Hansen, Henrik; Rand, John

    2006-01-01

    We analyse the Granger causal relationships between foreign direct investment (FDI) and GDP in a sample of 31 developing countries covering 31 years. Using estimators for heterogeneous panel data we find bi-directional causality between the FDI-to-GDP ratio and the level of GDP. FDI has a lasting...... impact on GDP, while GDP has no long-run impact on the FDI-to-GDP ratio. In that sense FDI causes growth. Furthermore, in a model for GDP and FDI as a fraction of gross capital formation (GCF) we also find long-run effects from FDI to GDP. This finding may be interpreted as evidence in favour...... of the hypotheses that FDI has an impact on GDP via knowledge transfers and adoption of new technology...

  5. Causal relationship between CO₂ emissions, real GDP, energy consumption, financial development, trade openness, and urbanization in Tunisia.

    Science.gov (United States)

    Farhani, Sahbi; Ozturk, Ilhan

    2015-10-01

    The aim of this paper is to examine the causal relationship between CO2 emissions, real GDP, energy consumption, financial development, trade openness, and urbanization in Tunisia over the period of 1971-2012. The long-run relationship is investigated by the auto-regressive distributed lag (ARDL) bounds testing approach to cointegration and error correction method (ECM). The results of the analysis reveal a positive sign for the coefficient of financial development, suggesting that the financial development in Tunisia has taken place at the expense of environmental pollution. The Tunisian case also shows a positive monotonic relationship between real GDP and CO2 emissions. This means that the results do not support the validity of environmental Kuznets curve (EKC) hypothesis. In addition, the paper explores causal relationship between the variables by using Granger causality models and it concludes that financial development plays a vital role in the Tunisian economy.

  6. Causality discovery technology

    Science.gov (United States)

    Chen, M.; Ertl, T.; Jirotka, M.; Trefethen, A.; Schmidt, A.; Coecke, B.; Bañares-Alcántara, R.

    2012-11-01

    Causality is the fabric of our dynamic world. We all make frequent attempts to reason causation relationships of everyday events (e.g., what was the cause of my headache, or what has upset Alice?). We attempt to manage causality all the time through planning and scheduling. The greatest scientific discoveries are usually about causality (e.g., Newton found the cause for an apple to fall, and Darwin discovered natural selection). Meanwhile, we continue to seek a comprehensive understanding about the causes of numerous complex phenomena, such as social divisions, economic crisis, global warming, home-grown terrorism, etc. Humans analyse and reason causality based on observation, experimentation and acquired a priori knowledge. Today's technologies enable us to make observations and carry out experiments in an unprecedented scale that has created data mountains everywhere. Whereas there are exciting opportunities to discover new causation relationships, there are also unparalleled challenges to benefit from such data mountains. In this article, we present a case for developing a new piece of ICT, called Causality Discovery Technology. We reason about the necessity, feasibility and potential impact of such a technology.

  7. Assimetria causal: um estudo

    Directory of Open Access Journals (Sweden)

    Túlio Aguiar

    2003-12-01

    Full Text Available Neste artigo, examinamos o aspecto assimétrico da relação causal, confrontando-o com o ponto de vista humiano e neo-humiano. Seguindo Hausman e Ehring, favorecemos uma abordagem situacional para a assimetria causal. Nós exploramos a análise do famoso exemplo do mastro (Flagpole, esclarecendo as conexões entre causação e explicação. Nosso diagnóstico geral é que a tradição neo-humiana supõe, equivocadamente, que as relações nômicas, com exceção de pequenos detalhes, exaurem as relações causais.This paper examines the asymmetrical aspect of causal relation, confronting it to Humean and Neo-Humean's view. Following Hausman and Ehring, we favor a situational approach to causal asymmetry. We explore the Hausman's analysis of flagpole's example, clearing the connexions between causation and explanation. Our general diagnosis is that the Neo-humean tradition wrongly supposes that nomic relations, with the exception of minor details, exhaust the causal relations.

  8. Biased causal inseparable game

    CERN Document Server

    Bhattacharya, Some Sankar

    2015-01-01

    Here we study the \\emph{causal inseparable} game introduced in [\\href{http://www.nature.com/ncomms/journal/v3/n10/full/ncomms2076.html}{Nat. Commun. {\\bf3}, 1092 (2012)}], but it's biased version. Two separated parties, Alice and Bob, generate biased bits (say input bit) in their respective local laboratories. Bob generates another biased bit (say decision bit) which determines their goal: whether Alice has to guess Bob's bit or vice-verse. Under the assumption that events are ordered with respect to some global causal relation, we show that the success probability of this biased causal game is upper bounded, giving rise to \\emph{biased causal inequality} (BCI). In the \\emph{process matrix} formalism, which is locally in agreement with quantum physics but assume no global causal order, we show that there exist \\emph{inseparable} process matrices that violate the BCI for arbitrary bias in the decision bit. In such scenario we also derive the maximal violation of the BCI under local operations involving tracele...

  9. The Secret to Finland's Success: Educating Teachers. Research Brief

    Science.gov (United States)

    Sahlberg, Pasi

    2010-01-01

    In the last decade, Finland has emerged as the leading OECD country in educational achievement. In examining the sources of Finland's dramatic rise to the top, research shows one key element that has impacted Finland's success above all others: excellent teachers. This policy brief details the key elements of Finland's successful system, examining…

  10. Study design in causal models

    OpenAIRE

    2012-01-01

    The causal assumptions, the study design and the data are the elements required for scientific inference in empirical research. The research is adequately communicated only if all of these elements and their relations are described precisely. Causal models with design describe the study design and the missing data mechanism together with the causal structure and allow the direct application of causal calculus in the estimation of the causal effects. The flow of the study is visualized by orde...

  11. Health technology assessment in Finland

    DEFF Research Database (Denmark)

    Mäkelä, Marjukka; Roine, Risto P

    2010-01-01

    Since the 1990s, health policy makers in Finland have been supportive of evidence-based medicine and approaches to implement its results. The Finnish Office for Health Technology Assessment (Finohta) has grown from a small start in 1995 to a medium-sized health technology assessment (HTA) agency......, with special responsibility in providing assessments to underpin national policies in screening. External evaluations enhanced the rapid growth. In the Finnish environment, decision making on health technologies is extremely decentralized, so Finohta has developed some practical tools for implementing HTA...... findings. The Managed Uptake of Medical Methods program links the hospital districts to agree on introduction of technologies. The Ohtanen database provides Finnish-language summaries of major assessments made in other countries....

  12. New Orthodox Immigration in Finland

    Directory of Open Access Journals (Sweden)

    Tuomas Martikainen

    2005-01-01

    Full Text Available The Finnish Orthodox Church is the second largest religious organization in Finland with ca. 57,000 members. During the last 15 years its membership has grown 7% because of international migration. The migrants are mainly from the former Soviet Union (e.g. Estonia, Russia and Ukraine, but there are also small groups from, e.g., Greece, Ethiopia and Romania. The article is a case study of the immigrant activities in two Orthodox parishes that are located in Helsinki and Turku. Issues such as organizational support, religious education and transnational connections are presented. Based on contemporary research on religion and immigration, the article aims to highlight the speci? c role of language in immigrant organizations, and it argues that more attention should be given to it as a speci? c factor.

  13. Productivity Analysis of Public and Private Airports: A Causal Investigation

    Science.gov (United States)

    Vasigh, Bijan; Gorjidooz, Javad

    2007-01-01

    Around the world, airports are being viewed as enterprises, rather than public services, which are expected to be managed efficiently and provide passengers with courteous customer services. Governments are, increasingly, turning to the private sectors for their efficiency in managing the operation, financing, and development, as well as providing security for airports. Operational and financial performance evaluation has become increasingly important to airport operators due to recent trends in airport privatization. Assessing performance allows the airport operators to plan for human resources and capital investment as efficiently as possible. Productivity measurements may be used as comparisons and guidelines in strategic planning, in the internal analysis of operational efficiency and effectiveness, and in assessing the competitive position of an airport in transportation industry. The primary purpose of this paper is to investigate the operational and financial efficiencies of 22 major airports in the United States and Europe. These airports are divided into three groups based on private ownership (7 British Airport Authority airports), public ownership (8 major United States airports), and a mix of private and public ownership (7 major European Union airports. The detail ownership structures of these airports are presented in Appendix A. Total factor productivity (TFP) model was utilized to measure airport performance in terms of financial and operational efficiencies and to develop a benchmarking tool to identify the areas of strength and weakness. A regression model was then employed to measure the relationship between TFP and ownership structure. Finally a Granger causality test was performed to determine whether ownership structure is a Granger cause of TFP. The results of the analysis presented in this paper demonstrate that there is not a significant relationship between airport TFP and ownership structure. Airport productivity and efficiency is

  14. Fish farming and otters in Finland

    Directory of Open Access Journals (Sweden)

    Skarén U.

    1990-02-01

    Full Text Available The results of a questionnaire sent to all fishfarmers in Finland are presented; 45% replied. There appear to be good otter populations in Finland. Frequency and amount of damage to stocks is discussed. An electric fence system that has been found useful in excluding otters from fish farms is described. Only a few farmers consider otters a grave pest. The major threat to otters in Finland seems to be traffic accidents as car numbers increase. Further information is needed to confirm the findings, and to ensure confusion with mink does not occur.

  15. Creating an import network China to Finland

    OpenAIRE

    Toijanen, Jarkko

    2016-01-01

    This thesis is about the creation of a network of imports from China to Finland. The theoretical part deals with trade relations between Finland and China. The aim is to create a picture of the different characteristics of Chinese business culture. The empirical part is done in project form, here I have a job to create an import network from China to Finland and for this purpose, have created the TJ-Tech Company. I combine theoretical and empirical background research when finding out the bas...

  16. ALTENER - Biomass event in Finland

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-12-31

    The publication contains the lectures held in the Biomass event in Finland. The event was divided into two sessions: Fuel production and handling, and Co-combustion and gasification sessions. Both sessions consisted of lectures and the business forum during which the companies involved in the research presented themselves and their research and their equipment. The fuel production and handling session consisted of following lectures and business presentations: AFB-NETT - business opportunities for European biomass industry; Wood waste in Europe; Wood fuel production technologies in EU- countries; new drying method for wood waste; Pellet - the best package for biofuel - a view from the Swedish pelletmarket; First biomass plant in Portugal with forest residue fuel; and the business forum of presentations: Swedish experiences of willow growing; Biomass handling technology; Chipset 536 C Harvester; KIC International. The Co-combustion and gasification session consisted of following lectures and presentations: Gasification technology - overview; Overview of co-combustion technology in Europe; Modern biomass combustion technology; Wood waste, peat and sludge combustion in Enso Kemi mills and UPM-Kymmene Rauma paper mill; Enhanced CFB combustion of wood chips, wood waste and straw in Vaexjoe in Sweden and Grenaa CHP plant in Denmark; Co-combustion of wood waste; Biomass gasification projects in India and Finland; Biomass CFB gasifier connected to a 350 MW{sub t}h steam boiler fired with coal and natural gas - THERMIE demonstration project in Lahti (FI); Biomass gasification for energy production, Noord Holland plant in Netherlands and Arbre Energy (UK); Gasification of biomass in fixed bed gasifiers, Wet cleaning and condensing heat recovery of flue gases; Combustion of wet biomass by underfeed grate boiler; Research on biomass and waste for energy; Engineering and consulting on energy (saving) projects; and Research and development on combustion of solid fuels

  17. Causal inference in econometrics

    CERN Document Server

    Kreinovich, Vladik; Sriboonchitta, Songsak

    2016-01-01

    This book is devoted to the analysis of causal inference which is one of the most difficult tasks in data analysis: when two phenomena are observed to be related, it is often difficult to decide whether one of them causally influences the other one, or whether these two phenomena have a common cause. This analysis is the main focus of this volume. To get a good understanding of the causal inference, it is important to have models of economic phenomena which are as accurate as possible. Because of this need, this volume also contains papers that use non-traditional economic models, such as fuzzy models and models obtained by using neural networks and data mining techniques. It also contains papers that apply different econometric models to analyze real-life economic dependencies.

  18. Causal graph dynamics

    CERN Document Server

    Arrighi, Pablo

    2012-01-01

    We generalize the theory of Cellular Automata to arbitrary, time-varying graphs. In other words we formalize, and prove theorems about, the intuitive idea of a labelled graph which evolves in time - but under the natural constraint that information can only ever be transmitted at a bounded speed, with respect to the distance given by the graph. The notion of translation-invariance is also generalized. The definition we provide for these `causal graph dynamics' is simple and axiomatic. The theorems we provide also show that it is robust. For instance, causal graph dynamics are stable under composition and under restriction to radius one. In the finite case some fundamental facts of Cellular Automata theory carry through: causal graph dynamics admit a characterization as continuous functions and they are stable under inversion. The provided examples suggest a wide range of applications of this mathematical object, from complex systems science to theoretical physics. Keywords: Dynamical networks, Boolean network...

  19. Causality, criticality, and reading words: distinct sources of fractal scaling in behavioral sequences.

    Science.gov (United States)

    Moscoso del Prado Martín, Fermín

    2011-07-01

    The finding of fractal scaling (FS) in behavioral sequences has raised a debate on whether FS is a pervasive property of the cognitive system or is the result of specific processes. Inferences about the origins of properties in time sequences are causal. That is, as opposed to correlational inferences reflecting instantaneous symmetrical relations, causal inferences concern asymmetric relations lagged in time. Here, I integrate Granger-causality with inferences about FS. Four simulations illustrate that causal analyses can isolate distinct FS sources, whereas correlational techniques cannot. I then analyze three simultaneous sequences of responses from a database of word-naming trials. I find that two, or perhaps three, distinct sources account for the presence of FS in these sequences, but FS is not a general property of the system. This suggests that FS arises due to the properties of a limited number of identifiable psychological and/or neural processes. Finally, I reanalyze a previously published dataset of acoustic frequency spectra using the new tools. The causality/criticality combination introduced here offers a new important perspective in the study of cognition. Copyright © 2011 Cognitive Science Society, Inc.

  20. Detecting dynamic causal inference in nonlinear two-phase fracture flow

    Science.gov (United States)

    Faybishenko, Boris

    2017-08-01

    Identifying dynamic causal inference involved in flow and transport processes in complex fractured-porous media is generally a challenging task, because nonlinear and chaotic variables may be positively coupled or correlated for some periods of time, but can then become spontaneously decoupled or non-correlated. In his 2002 paper (Faybishenko, 2002), the author performed a nonlinear dynamical and chaotic analysis of time-series data obtained from the fracture flow experiment conducted by Persoff and Pruess (1995), and, based on the visual examination of time series data, hypothesized that the observed pressure oscillations at both inlet and outlet edges of the fracture result from a superposition of both forward and return waves of pressure propagation through the fracture. In the current paper, the author explores an application of a combination of methods for detecting nonlinear chaotic dynamics behavior along with the multivariate Granger Causality (G-causality) time series test. Based on the G-causality test, the author infers that his hypothesis is correct, and presents a causation loop diagram of the spatial-temporal distribution of gas, liquid, and capillary pressures measured at the inlet and outlet of the fracture. The causal modeling approach can be used for the analysis of other hydrological processes, for example, infiltration and pumping tests in heterogeneous subsurface media, and climatic processes, for example, to find correlations between various meteorological parameters, such as temperature, solar radiation, barometric pressure, etc.

  1. Causal premise semantics.

    Science.gov (United States)

    Kaufmann, Stefan

    2013-08-01

    The rise of causality and the attendant graph-theoretic modeling tools in the study of counterfactual reasoning has had resounding effects in many areas of cognitive science, but it has thus far not permeated the mainstream in linguistic theory to a comparable degree. In this study I show that a version of the predominant framework for the formal semantic analysis of conditionals, Kratzer-style premise semantics, allows for a straightforward implementation of the crucial ideas and insights of Pearl-style causal networks. I spell out the details of such an implementation, focusing especially on the notions of intervention on a network and backtracking interpretations of counterfactuals.

  2. Complementarity, causality, and explanation

    CERN Document Server

    Losee, John

    2013-01-01

    Prior to the work of Niels Bohr, discussions on the relationship of cause and effect presupposed that successful causal attribution implies explanation. The success of quantum theory challenged this presupposition. In this succinct review of the history of these discussions, John Losee presents the philosophical background of debates over the cause-effect relation. He reviews the positions of Aristotle, René Descartes, Isaac Newton, David Hume, Immanuel Kant, and John Stuart Mill. He shows how nineteenth-century theories in physics and chemistry were informed by a dominant theory of causality

  3. Stock Markets and Economic Growth : A Causality Test = Hisse Senedi Pazarı ve Ekonomik Büyüme: Bir Nedensellik Testi

    Directory of Open Access Journals (Sweden)

    Alövsat MÜSLÜMOV

    2000-06-01

    Full Text Available This article examines causality relationships between stock markets and economic growth based on the time series data compiled from 20 countries for the years 1981 through 1994 . Sims' causality test based on Granger definition of causality was used . At first, panel data covering all countries over the entire analysis period were used to detect the direction of causation. Secondly, causal relations were investigated for each country, in isolation, using the respective time series data.Analysis based on the panel data revealed a two-way causation between stock market development and economic growth. Country analyses, on the other hand, could not lead to precise conclusions, but suggested a somewhat stronger link between stock market development and economic growth in developing countries.

  4. Temporal causality between house prices and output in the U.S.: a bootstrap rolling-window approach

    CSIR Research Space (South Africa)

    Nyakabawo, W

    2015-07-01

    Full Text Available and recessions in the U.S, as well as different market booms and busts, creating substantial volatility, that may provide different outcomes from other less-volatile periods (Iacoviello and Neri, 2010). We test the stability of the short- and long... Granger non- causality tests for a series of rolling-window sub-sample estimations. The subprime mortgage lending fiasco and the financial crisis sparked a price bubble and collapse in the housing market and the subsequent Great Recession. Many...

  5. University Mergers in Finland: Mediating Global Competition

    Science.gov (United States)

    Välimaa, Jussi; Aittola, Helena; Ursin, Jani

    2014-01-01

    University mergers have become a common strategy for increasing global competitiveness. In this chapter, the authors analyze the implementation of mergers in Finnish universities from the perspective of social justice as conceived within Finland and other Nordic countries.

  6. Changing attitudes in Finland towards FGM

    Directory of Open Access Journals (Sweden)

    Saido Mohamed

    2015-05-01

    Full Text Available Former refugee women are now working as professional educators among immigrant and refugee communities in Finland to tackle ignorance of the impact and extent of female genital mutilation/cutting.

  7. University Mergers in Finland: Mediating Global Competition

    Science.gov (United States)

    Välimaa, Jussi; Aittola, Helena; Ursin, Jani

    2014-01-01

    University mergers have become a common strategy for increasing global competitiveness. In this chapter, the authors analyze the implementation of mergers in Finnish universities from the perspective of social justice as conceived within Finland and other Nordic countries.

  8. Understanding Causal Coherence Relations

    NARCIS (Netherlands)

    Mulder, G.

    2008-01-01

    The research reported in this dissertation focuses on the cognitive processes and representations involved in understanding causal coherence relations in text. Coherence relations are the meaning relations between the information units in the text, such as Cause-Consequence. These relations can be m

  9. Causal Responsibility and Counterfactuals

    Science.gov (United States)

    Lagnado, David A.; Gerstenberg, Tobias; Zultan, Ro'i

    2013-01-01

    How do people attribute responsibility in situations where the contributions of multiple agents combine to produce a joint outcome? The prevalence of over-determination in such cases makes this a difficult problem for counterfactual theories of causal responsibility. In this article, we explore a general framework for assigning responsibility in…

  10. Causality: Physics and Philosophy

    Science.gov (United States)

    Chatterjee, Atanu

    2013-01-01

    Nature is a complex causal network exhibiting diverse forms and species. These forms or rather systems are physically open, structurally complex and naturally adaptive. They interact with the surrounding media by operating a positive-feedback loop through which, they adapt, organize and self-organize themselves in response to the ever-changing…

  11. Explaining through causal mechanisms

    NARCIS (Netherlands)

    Biesbroek, Robbert; Dupuis, Johann; Wellstead, Adam

    2017-01-01

    This paper synthesizes and builds on recent critiques of the resilience literature; namely that the field has largely been unsuccessful in capturing the complexity of governance processes, in particular cause–effects relationships. We demonstrate that absence of a causal model is reflected in the

  12. Modelling tree biomasses in Finland

    Energy Technology Data Exchange (ETDEWEB)

    Repola, J.

    2013-06-01

    Biomass equations for above- and below-ground tree components of Scots pine (Pinus sylvestris L), Norway spruce (Picea abies [L.] Karst) and birch (Betula pendula Roth and Betula pubescens Ehrh.) were compiled using empirical material from a total of 102 stands. These stands (44 Scots pine, 34 Norway spruce and 24 birch stands) were located mainly on mineral soil sites representing a large part of Finland. The biomass models were based on data measured from 1648 sample trees, comprising 908 pine, 613 spruce and 127 birch trees. Biomass equations were derived for the total above-ground biomass and for the individual tree components: stem wood, stem bark, living and dead branches, needles, stump, and roots, as dependent variables. Three multivariate models with different numbers of independent variables for above-ground biomass and one for below-ground biomass were constructed. Variables that are normally measured in forest inventories were used as independent variables. The simplest model formulations, multivariate models (1) were mainly based on tree diameter and height as independent variables. In more elaborated multivariate models, (2) and (3), additional commonly measured tree variables such as age, crown length, bark thickness and radial growth rate were added. Tree biomass modelling includes consecutive phases, which cause unreliability in the prediction of biomass. First, biomasses of sample trees should be determined reliably to decrease the statistical errors caused by sub-sampling. In this study, methods to improve the accuracy of stem biomass estimates of the sample trees were developed. In addition, the reliability of the method applied to estimate sample-tree crown biomass was tested, and no systematic error was detected. Second, the whole information content of data should be utilized in order to achieve reliable parameter estimates and applicable and flexible model structure. In the modelling approach, the basic assumption was that the biomasses of

  13. Disrupted causal connectivity in mesial temporal lobe epilepsy.

    Directory of Open Access Journals (Sweden)

    Gong-Jun Ji

    Full Text Available Although mesial temporal lobe epilepsy (mTLE is characterized by the pathological changes in mesial temporal lobe, function alteration was also found in extratemporal regions. Our aim is to investigate the information flow between the epileptogenic zone (EZ and other brain regions. Resting-state functional magnetic resonance imaging (RS-fMRI data were recorded from 23 patients with left mTLE and matched controls. We first identified the potential EZ using the amplitude of low-frequency fluctuation (ALFF of RS-fMRI signal, then performed voxel-wise Granger causality analysis between EZ and the whole brain. Relative to controls, patients demonstrated decreased driving effect from EZ to thalamus and basal ganglia, and increased feedback. Additionally, we found an altered causal relation between EZ and cortical networks (default mode network, limbic system, visual network and executive control network. The influence from EZ to right precuneus and brainstem negatively correlated with disease duration, whereas that from the right hippocampus, fusiform cortex, and lentiform nucleus to EZ showed positive correlation. These findings demonstrate widespread brain regions showing abnormal functional interaction with EZ. In addition, increased ALFF in EZ was positively correlated with the increased driving effect on EZ in patients, but not in controls. This finding suggests that the initiation of epileptic activity depends not only on EZ itself, but also on the activity emerging in large-scale macroscopic brain networks. Overall, this study suggests that the causal topological organization is disrupted in mTLE, providing valuable information to understand the pathophysiology of this disorder.

  14. Causal diagrams for physical models

    CERN Document Server

    Kinsler, Paul

    2015-01-01

    I present a scheme of drawing causal diagrams based on physically motivated mathematical models expressed in terms of temporal differential equations. They provide a means of better understanding the processes and causal relationships contained within such systems.

  15. Libraries in Finland Establish Consortia

    Directory of Open Access Journals (Sweden)

    Esko Häkli

    2001-07-01

    Full Text Available I will discuss the development of organized consortia, which are based on a charter or a written contract. I will also deal with some issues related to the organization of the consortia. I would already here like to stress, that if a consortium wants to achieve results it, in addition to a charter or a contract, also needs an executive body that carries out the work and makes sure that the plans and decisions are not only prepared but also put into practice. One of the main weaknesses of many cooperative arrangements between libraries has been the absence of a common executive not only taking care of the practicalities but also safeguarding the continuity. A committee can never fulfill the tasks of an executive body because running a consortium successfully requires much more effort than what is normally anticipated. In Finland the National Library has been given the task to enhance the cooperation between the research libraries of the country and to support their consortia . According to the National Library Strategy (adopted in November 1999 the Library is functioning as a common resource of the country’s research libraries. In this capacity it has been instrumental in creating the comprehensive consortia described below and is also responsible for running their daily business. It is possible that an arrangement of this kind is more typical for a small country than for a bigger one.

  16. Information causality and noisy computations

    Energy Technology Data Exchange (ETDEWEB)

    Hsu, Li-Yi [Department of Physics, Chung Yuan Christian University, Chung-li 32023, Taiwan (China); Yu, I-Ching; Lin, Feng-Li [Department of Physics, National Taiwan Normal University, Taipei 116, Taiwan (China)

    2011-10-15

    We reformulate the information causality in a more general framework by adopting the results of signal propagation and computation in a noisy circuit. In our framework, the information causality leads to a broad class of Tsirelson inequalities. This fact allows us to subject information causality to experimental scrutiny. A no-go theorem for reliable nonlocal computation is also derived. Information causality prevents any physical circuit from performing reliable computations.

  17. Reindeer Herders in Finland: Pulled to Community-based Entrepreneurship & Pushed to Individualistic Firms'

    OpenAIRE

    Dana, Leo; Riseth, Jan Age

    2011-01-01

    Content analysis of interviews conducted with reindeer herders ‒ referred to as reindeer husbandry entrepreneurs, by the Reindeer Herders’ Association ‒ from two ethnic communities in Finland reveals that participants who identified themselves as ethnic Finns viewed their self-employment as an individualistic form of entrepreneurship and they focused their discussion on matters related to financial capital and profit. In contrast, Sámi respondents claimed that the causal varia...

  18. Spectral Geometry and Causality

    CERN Document Server

    Kopf, T

    1996-01-01

    For a physical interpretation of a theory of quantum gravity, it is necessary to recover classical spacetime, at least approximately. However, quantum gravity may eventually provide classical spacetimes by giving spectral data similar to those appearing in noncommutative geometry, rather than by giving directly a spacetime manifold. It is shown that a globally hyperbolic Lorentzian manifold can be given by spectral data. A new phenomenon in the context of spectral geometry is observed: causal relationships. The employment of the causal relationships of spectral data is shown to lead to a highly efficient description of Lorentzian manifolds, indicating the possible usefulness of this approach. Connections to free quantum field theory are discussed for both motivation and physical interpretation. It is conjectured that the necessary spectral data can be generically obtained from an effective field theory having the fundamental structures of generalized quantum mechanics: a decoherence functional and a choice of...

  19. Does sunspot numbers cause global temperatures? A reconsideration using non-parametric causality tests

    Science.gov (United States)

    Hassani, Hossein; Huang, Xu; Gupta, Rangan; Ghodsi, Mansi

    2016-10-01

    In a recent paper, Gupta et al., (2015), analyzed whether sunspot numbers cause global temperatures based on monthly data covering the period 1880:1-2013:9. The authors find that standard time domain Granger causality test fails to reject the null hypothesis that sunspot numbers do not cause global temperatures for both full and sub-samples, namely 1880:1-1936:2, ​1936:3-1986:11 and 1986:12-2013:9 (identified based on tests of structural breaks). However, frequency domain causality test detects predictability for the full-sample at short (2-2.6 months) cycle lengths, but not the sub-samples. But since, full-sample causality cannot be relied upon due to structural breaks, Gupta et al., (2015) conclude that the evidence of causality running from sunspot numbers to global temperatures is weak and inconclusive. Given the importance of the issue of global warming, our current paper aims to revisit this issue of whether sunspot numbers cause global temperatures, using the same data set and sub-samples used by Gupta et al., (2015), based on an nonparametric Singular Spectrum Analysis (SSA)-based causality test. Based on this test, we however, show that sunspot numbers have predictive ability for global temperatures for the three sub-samples, over and above the full-sample. Thus, generally speaking, our non-parametric SSA-based causality test outperformed both time domain and frequency domain causality tests and highlighted that sunspot numbers have always been important in predicting global temperatures.

  20. Quantum information causality

    OpenAIRE

    Pitalúa-García, Damián

    2012-01-01

    How much information can a transmitted physical system fundamentally communicate? We introduce the principle of quantum information causality, which states the maximum amount of quantum information that a quantum system can communicate as a function of its dimension, independently of any previously shared quantum physical resources. We present a new quantum information task, whose success probability is upper bounded by the new principle, and show that an optimal strategy to perform it combin...

  1. Causality between time series

    CERN Document Server

    Liang, X San

    2014-01-01

    Given two time series, can one tell, in a rigorous and quantitative way, the cause and effect between them? Based on a recently rigorized physical notion namely information flow, we arrive at a concise formula and give this challenging question, which is of wide concern in different disciplines, a positive answer. Here causality is measured by the time rate of change of information flowing from one series, say, X2, to another, X1. The measure is asymmetric between the two parties and, particularly, if the process underlying X1 does not depend on X2, then the resulting causality from X2 to X1 vanishes. The formula is tight in form, involving only the commonly used statistics, sample covariances. It has been validated with touchstone series purportedly generated with one-way causality. It has also been applied to the investigation of real world problems; an example presented here is the cause-effect relation between two climate modes, El Ni\\~no and Indian Ocean Dipole, which have been linked to the hazards in f...

  2. Dynamic causal modelling revisited.

    Science.gov (United States)

    Friston, K J; Preller, Katrin H; Mathys, Chris; Cagnan, Hayriye; Heinzle, Jakob; Razi, Adeel; Zeidman, Peter

    2017-02-17

    This paper revisits the dynamic causal modelling of fMRI timeseries by replacing the usual (Taylor) approximation to neuronal dynamics with a neural mass model of the canonical microcircuit. This provides a generative or dynamic causal model of laminar specific responses that can generate haemodynamic and electrophysiological measurements. In principle, this allows the fusion of haemodynamic and (event related or induced) electrophysiological responses. Furthermore, it enables Bayesian model comparison of competing hypotheses about physiologically plausible synaptic effects; for example, does attentional modulation act on superficial or deep pyramidal cells - or both? In this technical note, we describe the resulting dynamic causal model and provide an illustrative application to the attention to visual motion dataset used in previous papers. Our focus here is on how to answer long-standing questions in fMRI; for example, do haemodynamic responses reflect extrinsic (afferent) input from distant cortical regions, or do they reflect intrinsic (recurrent) neuronal activity? To what extent do inhibitory interneurons contribute to neurovascular coupling? What is the relationship between haemodynamic responses and the frequency of induced neuronal activity? This paper does not pretend to answer these questions; rather it shows how they can be addressed using neural mass models of fMRI timeseries. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  3. 75 FR 73035 - Purified Carboxymethylcellulose From Finland; Notice of Final Results of Antidumping Duty...

    Science.gov (United States)

    2010-11-29

    ... International Trade Administration Purified Carboxymethylcellulose From Finland; Notice of Final Results of... order on purified carboxymethylcellulose from Finland. See Purified Carboxymethylcellulose from Finland... order covering purified carboxymethylcellulose from Finland. See Preliminary Results. The...

  4. Structure and Connectivity Analysis of Financial Complex System Based on G-Causality Network

    Science.gov (United States)

    Xu, Chuan-Ming; Yan, Yan; Zhu, Xiao-Wu; Li, Xiao-Teng; Chen, Xiao-Song

    2013-11-01

    The recent financial crisis highlights the inherent weaknesses of the financial market. To explore the mechanism that maintains the financial market as a system, we study the interactions of U.S. financial market from the network perspective. Applied with conditional Granger causality network analysis, network density, in-degree and out-degree rankings are important indicators to analyze the conditional causal relationships among financial agents, and further to assess the stability of U.S. financial systems. It is found that the topological structure of G-causality network in U.S. financial market changed in different stages over the last decade, especially during the recent global financial crisis. Network density of the G-causality model is much higher during the period of 2007-2009 crisis stage, and it reaches the peak value in 2008, the most turbulent time in the crisis. Ranked by in-degrees and out-degrees, insurance companies are listed in the top of 68 financial institutions during the crisis. They act as the hubs which are more easily influenced by other financial institutions and simultaneously influence others during the global financial disturbance.

  5. Electricity consumption and economic growth in South Africa. A trivariate causality test

    Energy Technology Data Exchange (ETDEWEB)

    Odhiambo, Nicholas M. [Economics Department, University of South Africa (UNISA), P.O. Box 392, UNISA, 0003, Pretoria (South Africa)

    2009-09-15

    In this paper we examine the causal relationship between electricity consumption and economic growth in South Africa. We incorporate the employment rate as an intermittent variable in the bivariate model between electricity consumption and economic growth - thereby creating a simple trivariate causality framework. Our empirical results show that there is a distinct bidirectional causality between electricity consumption and economic growth in South Africa. In addition, the results show that employment in South Africa Granger-causes economic growth. The results apply irrespective of whether the causality is estimated in the short-run or in the long-run formulation. The study, therefore, recommends that policies geared towards the expansion of the electricity infrastructure should be intensified in South Africa in order to cope with the increasing demand exerted by the country's strong economic growth and rapid industrialisation programme. This will certainly enable the country to avoid unprecedented power outages similar to those experienced in the country in mid-January 2008. (author)

  6. Introduction to the periglacial environment in Finland

    Directory of Open Access Journals (Sweden)

    Seppälä, M.

    1997-12-01

    Full Text Available An overview is presented of the periglacial characteristics of climate and landforms in Finland. Mean annual air temperature (MAAT in Finland ranges from +5.5 to -3°C, and frost sums in most parts of the country are large enough for active seasonal frost. Local conditions are more important in the formation of frost features than the overly general mean values of air temperature, however. Snow depth is the critical factor for most frost features, and permafrost is observed only in northern parts of the country, where thin snow cover supports frost activity. A brief description of features indicating frost activity is presented. Palsas, pounus, and string mires are peat landforms designed by frost. Fell slopes exhibit additional features of talus, slush flows and gelifluction lobes and terraces. Frost heave and contraction cracking are characteristic features occuring even in fields in southern Finland. Active frost-sorted patterned grounds are common in northern Finland, especially at the bottoms of shallow, seasonally dry ponds. Ground water close to the surface is essential for the formation of most frost features. Special forms of both aeolian and fluvial activity are part of the periglacial environment in Finland. Snow drift and deflation of sand surfaces formed by glaciofluvial processes during deglaciation are part of the periglacial environment in Lapland. Drastic spring floods with ice dams formed in river channels are typical for northern rivers. Proposals for further studies are made at the end of the paper.

  7. The Fourth Way in Finland

    Directory of Open Access Journals (Sweden)

    Vesa Iitti

    2008-01-01

    Full Text Available This article focuses on the general history of the Fourth Way in Finland. The Fourth Way, or simply ‘the Work’, began as a Greco-Armenian man named Georges Ivanovich Gurdjieff (1866?–1949 gathered groups of pupils in St Petersburg and Moscow in 1912. To these groups, Gurdjieff started to teach what he had learned and synthesized between ca 1896 and 1912 during his travels on spiritual search of Egypt, Crete, Sumeria, Assyria, the Holy Land, Mecca, Ethiopia, Sudan, India, Afghanistan, the northern valleys of Siberia, and Tibet. Neither Gurdjieff nor any of his disciples called themselves a church, a sect, or anything alike, but referred to themselves simply as ‘the Work’, or as ‘the Fourth Way’. The name ‘the Fourth Way’ originates in a Gurdjieffian view that there are essentially three traditional ways of spiritual work: those of a monk, a fakir, and a yogi. These ways do not literally refer to the activities of a monk, a fakir, and a yogi, but to similar types of spiritual work emphasizing exercise of emotion, body, or mind. Gurdjieff’s teaching is a blend of various influences that include Suf­ism, orthodox Christianity, Buddhism, Kabbalah, and general elem­ents of various occult teachings of both the East and the West. Gurdjieff’s teaching is a blend of various influences that include Suf­ism, orthodox Christianity, Buddhism, Kabbalah, and general elem­ents of various occult teachings of both the East and the West. It is a unique combination of cosmology, psychology, theory of evolution, and overall theory and practise aiming to help individ­uals in their efforts towards what is called ‘self-remembering’.

  8. Revisiting Causality in Markov Chains

    CERN Document Server

    Shojaee, Abbas

    2016-01-01

    Identifying causal relationships is a key premise of scientific research. The growth of observational data in different disciplines along with the availability of machine learning methods offers the possibility of using an empirical approach to identifying potential causal relationships, to deepen our understandings of causal behavior and to build theories accordingly. Conventional methods of causality inference from observational data require a considerable length of time series data to capture cause-effect relationship. We find that potential causal relationships can be inferred from the composition of one step transition rates to and from an event. Also known as Markov chain, one step transition rates are a commonly available resource in different scientific disciplines. Here we introduce a simple, effective and computationally efficient method that we termed 'Causality Inference using Composition of Transitions CICT' to reveal causal structure with high accuracy. We characterize the differences in causes,...

  9. Quantum information causality.

    Science.gov (United States)

    Pitalúa-García, Damián

    2013-05-24

    How much information can a transmitted physical system fundamentally communicate? We introduce the principle of quantum information causality, which states the maximum amount of quantum information that a quantum system can communicate as a function of its dimension, independently of any previously shared quantum physical resources. We present a new quantum information task, whose success probability is upper bounded by the new principle, and show that an optimal strategy to perform it combines the quantum teleportation and superdense coding protocols with a task that has classical inputs.

  10. Entropy of Causal Horizons

    CERN Document Server

    Howard, Eric M

    2016-01-01

    We analyze spacetimes with horizons and study the thermodynamic aspects of causal horizons, suggesting that the resemblance between gravitational and thermodynamic systems has a deeper quantum mechanical origin. We find that the observer dependence of such horizons is a direct consequence of associating a temperature and entropy to a spacetime. The geometrical picture of a horizon acting as a one-way membrane for information flow can be accepted as a natural interpretation of assigning a quantum field theory to a spacetime with boundary, ultimately leading to a close connection with thermodynamics.

  11. Importing coconut oil from Vietnam to Finland

    OpenAIRE

    2016-01-01

    The main goal of this Bachelor’s thesis is to clarify the coconut oil production chain and importing process for it into Finland and some others EU countries. The benefits of coconut oil products for food industry are included, which is popular in Finland because of its healthy advantages. Moreover, the benefit of using coconut oil as beauty products is mentioned as one good point which is now trendy in Asia but not yet popular in Europe. In this thesis, the knowledge and information is ...

  12. El milagro educativo finlandés

    OpenAIRE

    Gabaldón Estevan, Daniel

    2015-01-01

    El modelo de enseñanza finlandés se ha convertido en un referente internacional de primer orden catapultado por el recurrente éxito en los informes del Programa Internacional para la Evaluación de Estudiantes (PISA) de la Organización para la Cooperación y el Desarrollo Económicos (OCDE). La atracción por el modelo de enseñanza finlandés afecta a tanto a académicos y administradores extranjeros del ámbito educativo, algunos de los cuales incluso visitan las universidades finlandesas para cono...

  13. Fossil fuel support mechanisms in Finland

    Energy Technology Data Exchange (ETDEWEB)

    Lampinen, Ari

    2013-10-15

    Fossil fuel subsidies and other state support for fossil fuels are forbidden by the Kyoto Protocol and other international treaties. However, they are still commonly used. This publication presents and analyses diverse state support mechanisms for fossil fuels in Finland in 2003-2010. Total of 38 support mechanisms are covered in quantitative analysis and some other mechanisms are mentioned qualitatively only. For some mechanisms the study includes a longer historical perspective. This is the case for tax subsidies for crude oil based traffic fuels that have been maintained in Finland since 1965.

  14. Quantum Fields on Causal Sets

    CERN Document Server

    Johnston, Steven

    2010-01-01

    Causal set theory provides a model of discrete spacetime in which spacetime events are represented by elements of a causal set---a locally finite, partially ordered set in which the partial order represents the causal relationships between events. The work presented here describes a model for matter on a causal set, specifically a theory of quantum scalar fields on a causal set spacetime background. The work starts with a discrete path integral model for particles on a causal set. Here quantum mechanical amplitudes are assigned to trajectories within the causal set. By summing these over all trajectories between two spacetime events we obtain a causal set particle propagator. With a suitable choice of amplitudes this is shown to agree (in an appropriate sense) with the retarded propagator for the Klein-Gordon equation in Minkowski spacetime. This causal set propagator is then used to define a causal set analogue of the Pauli-Jordan function that appears in continuum quantum field theories. A quantum scalar fi...

  15. Causality and Micro-Causality in Curved Spacetime

    OpenAIRE

    Hollowood, Timothy J.; Shore, Graham M.

    2007-01-01

    We consider how causality and micro-causality are realised in QED in curved spacetime. The photon propagator is found to exhibit novel non-analytic behaviour due to vacuum polarization, which invalidates the Kramers-Kronig dispersion relation and calls into question the validity of micro-causality in curved spacetime. This non-analyticity is ultimately related to the generic focusing nature of congruences of geodesics in curved spacetime, as implied by the null energy condition, and the exist...

  16. The relationships between Shanghai stock market and CNY/USD exchange rate: New evidence based on cross-correlation analysis, structural cointegration and nonlinear causality test

    Science.gov (United States)

    Liu, Li; Wan, Jieqiu

    2012-12-01

    This paper explores the co-movement of Shanghai stock market and China Yuan (CNY) exchange rates. First, we find that stock price and exchange rate are significantly cross-correlated. Second, employing a cointegration test allowing for a structural break, we find that the Shanghai Composite Index (SCI) is not cointegrated with the exchange rate of CNY/USD. The so-called “cointegration” found in previous studies is just caused by the shock of the recent financial crisis. Third, using linear and nonlinear Granger causality tests, we find no causality between stock prices and exchange rates during the period before the recent financial crisis. After the financial crisis, a unidirectional causality behavior running from exchange rates to stock index is present.

  17. Causal events enter awareness faster than non-causal events

    Science.gov (United States)

    Wagemans, Johan; de-Wit, Lee

    2017-01-01

    Philosophers have long argued that causality cannot be directly observed but requires a conscious inference (Hume, 1967). Albert Michotte however developed numerous visual phenomena in which people seemed to perceive causality akin to primary visual properties like colour or motion (Michotte, 1946). Michotte claimed that the perception of causality did not require a conscious, deliberate inference but, working over 70 years ago, he did not have access to the experimental methods to test this claim. Here we employ Continuous Flash Suppression (CFS)—an interocular suppression technique to render stimuli invisible (Tsuchiya & Koch, 2005)—to test whether causal events enter awareness faster than non-causal events. We presented observers with ‘causal’ and ‘non-causal’ events, and found consistent evidence that participants become aware of causal events more rapidly than non-causal events. Our results suggest that, whilst causality must be inferred from sensory evidence, this inference might be computed at low levels of perceptual processing, and does not depend on a deliberative conscious evaluation of the stimulus. This work therefore supports Michotte’s contention that, like colour or motion, causality is an immediate property of our perception of the world. PMID:28149698

  18. Dynamic causal modelling.

    Science.gov (United States)

    Friston, K J; Harrison, L; Penny, W

    2003-08-01

    In this paper we present an approach to the identification of nonlinear input-state-output systems. By using a bilinear approximation to the dynamics of interactions among states, the parameters of the implicit causal model reduce to three sets. These comprise (1) parameters that mediate the influence of extrinsic inputs on the states, (2) parameters that mediate intrinsic coupling among the states, and (3) [bilinear] parameters that allow the inputs to modulate that coupling. Identification proceeds in a Bayesian framework given known, deterministic inputs and the observed responses of the system. We developed this approach for the analysis of effective connectivity using experimentally designed inputs and fMRI responses. In this context, the coupling parameters correspond to effective connectivity and the bilinear parameters reflect the changes in connectivity induced by inputs. The ensuing framework allows one to characterise fMRI experiments, conceptually, as an experimental manipulation of integration among brain regions (by contextual or trial-free inputs, like time or attentional set) that is revealed using evoked responses (to perturbations or trial-bound inputs, like stimuli). As with previous analyses of effective connectivity, the focus is on experimentally induced changes in coupling (cf., psychophysiologic interactions). However, unlike previous approaches in neuroimaging, the causal model ascribes responses to designed deterministic inputs, as opposed to treating inputs as unknown and stochastic.

  19. Sugihara causality analysis of scalp EEG for detection of early Alzheimer's disease

    Directory of Open Access Journals (Sweden)

    Joseph C. McBride

    2015-01-01

    Full Text Available Recently, Sugihara proposed an innovative causality concept, which, in contrast to statistical predictability in Granger sense, characterizes underlying deterministic causation of the system. This work exploits Sugihara causality analysis to develop novel EEG biomarkers for discriminating normal aging from mild cognitive impairment (MCI and early Alzheimer's disease (AD. The hypothesis of this work is that scalp EEG based causality measurements have different distributions for different cognitive groups and hence the causality measurements can be used to distinguish between NC, MCI, and AD participants. The current results are based on 30-channel resting EEG records from 48 age-matched participants (mean age 75.7 years — 15 normal controls (NCs, 16 MCI, and 17 early-stage AD. First, a reconstruction model is developed for each EEG channel, which predicts the signal in the current channel using data of the other 29 channels. The reconstruction model of the target channel is trained using NC, MCI, or AD records to generate an NC-, MCI-, or AD-specific model, respectively. To avoid over fitting, the training is based on the leave-one-out principle. Sugihara causality between the channels is described by a quality score based on comparison between the reconstructed signal and the original signal. The quality scores are studied for their potential as biomarkers to distinguish between the different cognitive groups. First, the dimension of the quality scores is reduced to two principal components. Then, a three-way classification based on the principal components is conducted. Accuracies of 95.8%, 95.8%, and 97.9% are achieved for resting eyes open, counting eyes closed, and resting eyes closed protocols, respectively. This work presents a novel application of Sugihara causality analysis to capture characteristic changes in EEG activity due to cognitive deficits. The developed method has excellent potential as individualized biomarkers in the

  20. Sugihara causality analysis of scalp EEG for detection of early Alzheimer's disease.

    Science.gov (United States)

    McBride, Joseph C; Zhao, Xiaopeng; Munro, Nancy B; Jicha, Gregory A; Schmitt, Frederick A; Kryscio, Richard J; Smith, Charles D; Jiang, Yang

    2015-01-01

    Recently, Sugihara proposed an innovative causality concept, which, in contrast to statistical predictability in Granger sense, characterizes underlying deterministic causation of the system. This work exploits Sugihara causality analysis to develop novel EEG biomarkers for discriminating normal aging from mild cognitive impairment (MCI) and early Alzheimer's disease (AD). The hypothesis of this work is that scalp EEG based causality measurements have different distributions for different cognitive groups and hence the causality measurements can be used to distinguish between NC, MCI, and AD participants. The current results are based on 30-channel resting EEG records from 48 age-matched participants (mean age 75.7 years) - 15 normal controls (NCs), 16 MCI, and 17 early-stage AD. First, a reconstruction model is developed for each EEG channel, which predicts the signal in the current channel using data of the other 29 channels. The reconstruction model of the target channel is trained using NC, MCI, or AD records to generate an NC-, MCI-, or AD-specific model, respectively. To avoid over fitting, the training is based on the leave-one-out principle. Sugihara causality between the channels is described by a quality score based on comparison between the reconstructed signal and the original signal. The quality scores are studied for their potential as biomarkers to distinguish between the different cognitive groups. First, the dimension of the quality scores is reduced to two principal components. Then, a three-way classification based on the principal components is conducted. Accuracies of 95.8%, 95.8%, and 97.9% are achieved for resting eyes open, counting eyes closed, and resting eyes closed protocols, respectively. This work presents a novel application of Sugihara causality analysis to capture characteristic changes in EEG activity due to cognitive deficits. The developed method has excellent potential as individualized biomarkers in the detection of

  1. A causality between fund performance and stock market

    Science.gov (United States)

    Kim, Ho-Yong; Kwon, Okyu; Oh, Gabjin

    2016-02-01

    We investigate whether the characteristic fund performance indicators (FPI), such as the fund return, the Net asset value (NAV) and the cash flow, are correlated with the asset price movement using information flows estimated by the Granger causality test. First, we find that the information flow of FPI is most sensitive to extreme events of the Korean stock market, which include negative events such as the sub-prime crisis and the impact of QE (quantitative easing) by the US subprime and Europe financial crisis as well as the positive events of the golden period of Korean Composite Stock Price Index (KOSPI), except for the fund cash flow. Second, both the fund return and the NAV exhibit significant correlations with the KOSPI, whereas the cash flow is not correlated with the stock market. This result suggests that the information resulting from the ability of the fund manager should influence stock market. Finally, during market crisis period, information flows between FPI and the Korean stock market are significantly positively correlated with the market volatility.

  2. Causal inference in public health.

    Science.gov (United States)

    Glass, Thomas A; Goodman, Steven N; Hernán, Miguel A; Samet, Jonathan M

    2013-01-01

    Causal inference has a central role in public health; the determination that an association is causal indicates the possibility for intervention. We review and comment on the long-used guidelines for interpreting evidence as supporting a causal association and contrast them with the potential outcomes framework that encourages thinking in terms of causes that are interventions. We argue that in public health this framework is more suitable, providing an estimate of an action's consequences rather than the less precise notion of a risk factor's causal effect. A variety of modern statistical methods adopt this approach. When an intervention cannot be specified, causal relations can still exist, but how to intervene to change the outcome will be unclear. In application, the often-complex structure of causal processes needs to be acknowledged and appropriate data collected to study them. These newer approaches need to be brought to bear on the increasingly complex public health challenges of our globalized world.

  3. Experimental test of nonlocal causality.

    Science.gov (United States)

    Ringbauer, Martin; Giarmatzi, Christina; Chaves, Rafael; Costa, Fabio; White, Andrew G; Fedrizzi, Alessandro

    2016-08-01

    Explaining observations in terms of causes and effects is central to empirical science. However, correlations between entangled quantum particles seem to defy such an explanation. This implies that some of the fundamental assumptions of causal explanations have to give way. We consider a relaxation of one of these assumptions, Bell's local causality, by allowing outcome dependence: a direct causal influence between the outcomes of measurements of remote parties. We use interventional data from a photonic experiment to bound the strength of this causal influence in a two-party Bell scenario, and observational data from a Bell-type inequality test for the considered models. Our results demonstrate the incompatibility of quantum mechanics with a broad class of nonlocal causal models, which includes Bell-local models as a special case. Recovering a classical causal picture of quantum correlations thus requires an even more radical modification of our classical notion of cause and effect.

  4. Experimental test of nonlocal causality

    Science.gov (United States)

    Ringbauer, Martin; Giarmatzi, Christina; Chaves, Rafael; Costa, Fabio; White, Andrew G.; Fedrizzi, Alessandro

    2016-01-01

    Explaining observations in terms of causes and effects is central to empirical science. However, correlations between entangled quantum particles seem to defy such an explanation. This implies that some of the fundamental assumptions of causal explanations have to give way. We consider a relaxation of one of these assumptions, Bell’s local causality, by allowing outcome dependence: a direct causal influence between the outcomes of measurements of remote parties. We use interventional data from a photonic experiment to bound the strength of this causal influence in a two-party Bell scenario, and observational data from a Bell-type inequality test for the considered models. Our results demonstrate the incompatibility of quantum mechanics with a broad class of nonlocal causal models, which includes Bell-local models as a special case. Recovering a classical causal picture of quantum correlations thus requires an even more radical modification of our classical notion of cause and effect. PMID:27532045

  5. Causal inference based on counterfactuals

    Directory of Open Access Journals (Sweden)

    Höfler M

    2005-09-01

    Full Text Available Abstract Background The counterfactual or potential outcome model has become increasingly standard for causal inference in epidemiological and medical studies. Discussion This paper provides an overview on the counterfactual and related approaches. A variety of conceptual as well as practical issues when estimating causal effects are reviewed. These include causal interactions, imperfect experiments, adjustment for confounding, time-varying exposures, competing risks and the probability of causation. It is argued that the counterfactual model of causal effects captures the main aspects of causality in health sciences and relates to many statistical procedures. Summary Counterfactuals are the basis of causal inference in medicine and epidemiology. Nevertheless, the estimation of counterfactual differences pose several difficulties, primarily in observational studies. These problems, however, reflect fundamental barriers only when learning from observations, and this does not invalidate the counterfactual concept.

  6. Causal evolution of wave packets

    CERN Document Server

    Eckstein, Michał

    2016-01-01

    Drawing from the optimal transport theory adapted to the relativistic setting we formulate the principle of a causal flow of probability and apply it in the wave packet formalism. We demonstrate that whereas the Dirac system is causal, the relativistic-Schr\\"odinger Hamiltonian impels a superluminal evolution of probabilities. We quantify the causality breakdown in the latter system and argue that, in contrast to the popular viewpoint, it is not related to the localisation properties of the states.

  7. Model-free causality analysis of cardiovascular variability detects the amelioration of autonomic control in Parkinson's disease patients undergoing mechanical stimulation.

    Science.gov (United States)

    Bassani, Tito; Bari, Vlasta; Marchi, Andrea; Tassin, Stefano; Dalla Vecchia, Laura; Canesi, Margherita; Barbic, Franca; Furlan, Raffaello; Porta, Alberto

    2014-07-01

    We tested the hypothesis that causality analysis, applied to the spontaneous beat-to-beat variability of heart period (HP) and systolic arterial pressure (SAP), can identify the improvement of autonomic control linked to plantar mechanical stimulation in patients with Parkinson's disease (PD). A causality index, measuring the strength of the association from SAP to HP variability, and derived according to the Granger paradigm (i.e. SAP causes HP if the inclusion of SAP into the set of signals utilized to describe cardiovascular interactions improves the prediction of HP series), was calculated using both linear model-based (MB) and nonlinear model-free (MF) approaches. Univariate HP and SAP variability indices in time and frequency domains, and bivariate descriptors of the HP-SAP variability interactions were computed as well. We studied ten PD patients (age range: 57-78 years; Hoehn-Yahr scale: 2-3; six males, four females) without orthostatic hypotension or symptoms of orthostatic intolerance and 'on-time' according to their habitual pharmacological treatment. PD patients underwent recordings at rest in a supine position and during a head-up tilt before, and 24 h after, mechanical stimulation was applied to the plantar surface of both feet. The MF causality analysis indicated a greater involvement of baroreflex in regulating HP-SAP variability interactions after mechanical stimulation. Remarkably, MB causality and more traditional univariate or bivariate techniques could not detect changes in cardiovascular regulation after mechanical stimulation, thus stressing the importance of accounting for nonlinear dynamics in PD patients. Due to the higher statistical power of MF causality we suggest its exploitation to monitor the baroreflex control improvement in PD patients, and we encourage the clinical application of the Granger causality approach to evaluate the modification of the autonomic control in relation to the application of a pharmacological treatment, a

  8. Relationship of causal effects in a causal chain and related inference

    Institute of Scientific and Technical Information of China (English)

    GENG Zhi; HE Yangbo; WANG Xueli

    2004-01-01

    This paper discusses the relationship among the total causal effect and local causal effects in a causal chain and identifiability of causal effects. We show a transmission relationship of causal effects in a causal chain. According to the relationship, we give an approach to eliminating confounding bias through controlling for intermediate variables in a causal chain.

  9. Causality Statistical Perspectives and Applications

    CERN Document Server

    Berzuini, Carlo; Bernardinell, Luisa

    2012-01-01

    A state of the art volume on statistical causality Causality: Statistical Perspectives and Applications presents a wide-ranging collection of seminal contributions by renowned experts in the field, providing a thorough treatment of all aspects of statistical causality. It covers the various formalisms in current use, methods for applying them to specific problems, and the special requirements of a range of examples from medicine, biology and economics to political science. This book:Provides a clear account and comparison of formal languages, concepts and models for statistical causality. Addr

  10. Research on Spoken Interaction in Finland.

    Science.gov (United States)

    Hakulinen, Auli; Sorjonen, Marja-Leena

    1993-01-01

    Topics addressed in this review include ethnology and traditional dialect study, philology, linguistic conversion analysis, and interaction within the social sciences. Finland's size affects these research activities and research on spoken interaction is shifting to group projects with a common focus. (Contains 68 references.) (JP)

  11. Mathematics Lessons from Finland and Sweden

    Science.gov (United States)

    Seaberg, Rebecca L.

    2015-01-01

    In many ways, mathematics classrooms in Finland and Sweden are very similar to what would be considered traditional classrooms in the United States. Classes begin with checking homework and questions, followed by the teacher giving instruction in the new material, and end with students working on their new assignment. There are also interesting…

  12. Deep drilling for geothermal energy in Finland

    Science.gov (United States)

    Kukkonen, Ilmo

    2016-04-01

    There is a societal request to find renewable CO2-free energy resources. One of the biggest such resources is provided by geothermal energy. In addition to shallow ground heat already extensively used in Finland, deep geothermal energy provides an alternative so far not exploited. Temperatures are high at depth, but the challenge is, how to mine the heat? In this presentation, the geological and geophysical conditions for deep geothermal energy production in Finland are discussed as well as challenges for drilling and conditions at depth for geothermal energy production. Finland is located on ancient bedrock with much lower temperatures than geologically younger volcanically and tectonically active areas. In order to reach sufficiently high temperatures drilling to depths of several kilometres are needed. Further, mining of the heat with, e.g., the principle of Enhanced Geothermal System (EGS) requires high hydraulic conductivity for efficient circulation of fluid in natural or artificial fractures of the rock. There are many issues that must be solved and/or improved: Drilling technology, the EGS concept, rock stress and hydraulic fracturing, scale formation, induced seismicity and ground movements, possible microbial activity, etc. An industry-funded pilot project currently in progress in southern Finland is shortly introduced.

  13. A Review of Telemedicine Services in Finland

    DEFF Research Database (Denmark)

    Khatri, Vikramajeet; Peterson, Carrie Beth; Kyriazakos, Sofoklis

    2011-01-01

    Telemedicine is gaining popularity due to the provision of ubiquitous health care services that is a fundamental need for every socialized society. In this paper, telemedicine services in Finland are discussed, as well as how they came into existence, how they are funded, evaluated, and what are ...

  14. From Finland to Kyrgyzstan: A Changing Landscape

    Science.gov (United States)

    Schleicher, Andreas K. R.

    2009-01-01

    In the most recent Programme for International Student Assessment of science learning, the equivalent of six school years separate the achievement of 15-year-olds in Finland, the best-performing country, from their counterparts in Kyrgyzstan, a former Soviet republic. Still more than a school year lies between the neighboring countries Canada,…

  15. Alternative energies. Keeping cool in Helsinki, Finland

    Energy Technology Data Exchange (ETDEWEB)

    Gatermann, R.

    2009-09-15

    For more than fifty years the combination of power generation with district heating has been the norm in Helsinki, Finland. A few years ago Helsinki Energy decided to integrate district cooling into the system, with great success. It showed that Helsinki is an excellent example of how the efficient use of fossil fuels can be environmentally friendly.

  16. How Finland Serves Gifted and Talented Pupils

    Science.gov (United States)

    Tirri, Kirsi; Kuusisto, Elina

    2013-01-01

    The purpose of this article is to provide an overview of the ways gifted and talented pupils are served in Finland. The trend toward individualism and freedom of choice as well as national policy affecting gifted education are discussed. Empirical research on Finnish teachers' attitudes toward gifted education with respect to the national…

  17. The Professional Educator: Lessons from Finland

    Science.gov (United States)

    Sahlberg, Pasi

    2011-01-01

    Since Finland emerged in 2000 as the top-scoring Organisation for Economic Co-operation and Development (OECD) nation on the Programme for International Student Assessment (PISA), researchers have been pouring into the country to study the so-called "Finnish miracle." How did a country with an undistinguished education system in the…

  18. Children's Early Numeracy in Finland and Iran

    Science.gov (United States)

    Aunio, Pirjo; Korhonen, Johan; Bashash, Laaya; Khoshbakht, Fariba

    2014-01-01

    This research investigates similarities and differences in young children's early numeracy skills related to age, nationality and gender. The participants were five- to seven-year-old children from Finland and Iran. Early numeracy was investigated by using tasks measuring number-related relational skills (e.g. comparison, one-to-one…

  19. Cointegration and causality analysis of dynamic linkage between stock market and equity mutual funds in Australia

    Directory of Open Access Journals (Sweden)

    Sasipa Pojanavatee

    2014-12-01

    Full Text Available The existing literature finds conflicting results on the magnitude of price linkages between equity mutual funds and the stock market. The study contends that in an optimal lagged model, the expectations of future prices using knowledge of past price behaviour in a particular equity mutual fund category will improve forecasts of prices of other equity mutual fund categories and the stock market index. The evidence shows that the long-run pricing of equity mutual funds is cointegrated with the stock market index. In the short run, the results indicate that some equity mutual fund categories possess both long-run and short-run exogeneity with the stock market. Therefore, the short-run dynamic indicates short-run Granger causal links running between different equity mutual fund categories.

  20. Structural Equations and Causal Explanations: Some Challenges for Causal SEM

    Science.gov (United States)

    Markus, Keith A.

    2010-01-01

    One common application of structural equation modeling (SEM) involves expressing and empirically investigating causal explanations. Nonetheless, several aspects of causal explanation that have an impact on behavioral science methodology remain poorly understood. It remains unclear whether applications of SEM should attempt to provide complete…

  1. The Cradle of Causal Reasoning: Newborns' Preference for Physical Causality

    Science.gov (United States)

    Mascalzoni, Elena; Regolin, Lucia; Vallortigara, Giorgio; Simion, Francesca

    2013-01-01

    Perception of mechanical (i.e. physical) causality, in terms of a cause-effect relationship between two motion events, appears to be a powerful mechanism in our daily experience. In spite of a growing interest in the earliest causal representations, the role of experience in the origin of this sensitivity is still a matter of dispute. Here, we…

  2. The Cradle of Causal Reasoning: Newborns' Preference for Physical Causality

    Science.gov (United States)

    Mascalzoni, Elena; Regolin, Lucia; Vallortigara, Giorgio; Simion, Francesca

    2013-01-01

    Perception of mechanical (i.e. physical) causality, in terms of a cause-effect relationship between two motion events, appears to be a powerful mechanism in our daily experience. In spite of a growing interest in the earliest causal representations, the role of experience in the origin of this sensitivity is still a matter of dispute. Here, we…

  3. Identifiability of causal effect for a simple causal model

    Institute of Scientific and Technical Information of China (English)

    郑忠国; 张艳艳; 童行伟

    2002-01-01

    Counterfactual model is put forward to discuss the causal inference in the directed acyclic graph and its corresponding identifiability is thus studied with the ancillary information based on conditional independence. It is shown that the assumption of ignorability can be expanded to the assumption of replaceability,under which the causal efiects are identifiable.

  4. Inferring deterministic causal relations

    CERN Document Server

    Daniusis, Povilas; Mooij, Joris; Zscheischler, Jakob; Steudel, Bastian; Zhang, Kun; Schoelkopf, Bernhard

    2012-01-01

    We consider two variables that are related to each other by an invertible function. While it has previously been shown that the dependence structure of the noise can provide hints to determine which of the two variables is the cause, we presently show that even in the deterministic (noise-free) case, there are asymmetries that can be exploited for causal inference. Our method is based on the idea that if the function and the probability density of the cause are chosen independently, then the distribution of the effect will, in a certain sense, depend on the function. We provide a theoretical analysis of this method, showing that it also works in the low noise regime, and link it to information geometry. We report strong empirical results on various real-world data sets from different domains.

  5. COINTEGRATION AND CAUSALITY BETWEEN TURKISH, IMPORTS AND GDP: A STRUCTURAL ANALYSIS

    Directory of Open Access Journals (Sweden)

    Cagri Levent Uslu

    2016-04-01

    Full Text Available The aim of this paper is to reveal the relation between imports and growth rate in Turkey for the period between the first quarter of 1998 and last quarter of 2014. The touchstone in Turkish economy is the January 24 regulations of 1980. The import led growth strategy of the Turkish economy switched to export led growth strategy after this date. It is an indisputable fact that trade openness triggered to the economic growth progress of Turkey. Yet, the issue should be further investigated. It is being argued by both scholars and politicians that the high growth rates in the mentioned period is achieved by importing raw materials and intermediate goods, thus, growth in Turkish economy has to be accompanied by the increase in imports and thus increase in trade deficit and current account deficit. In the literature, the relations between GDP growth and exports are intensively investigated, however, the relation between the second component of international trade, imports, and GDP growth did not attract that much attention. The main objective of this study is to reveal the presence and direction of Granger causality between Turkish Imports and GDP. The model to be employed in Granger causality (i.e. VAR vs. VECM depends on whether the variables under question are stationary and/or co integrated. In testing the unit roots, we have followed the Augmented Dickey-Fuller (Dickey and Fuller, 1979 test which eventually became the standard practice in unit root testing. Next, to find the number of co integrating vectors Johansen Maximum Likelihood (Johansen and Juselius, 1990 test is employed.

  6. Spatio-temporal interaction between absorbing aerosols and temperature: Correlation and causality based approach

    Science.gov (United States)

    Dave, P.; Bhushan, M.; Venkataraman, C.

    2016-12-01

    Indian subcontinent, in particular, the Indo-gangetic plain (IGP) has witnessed large temperature anomalies (Ratnam et al., 2016) along with high emission of absorbing aerosols (AA) (Gazala, et al., 2005). The anomalous high temperature observed over this region may bear a relationship with high AA emissions. Different studies have been conducted to understand AA and temperature relationships (Turco et al., 1983; Hansen et al., 1997, 2005; Seinfeld 2008; Ramanathan et al. 2010b; Ban-Weiss et al., 2012). It was found that when the AA was injected in the lower- mid troposphere the surface air temperature increases while injection of AA at higher troposphere-lower stratosphere surface temperature decreases. These studies used simulation based results to establish link between AA and temperature (Hansen et al., 1997, 2005; Ban-Weiss et al., 2012). The current work focuses on identifying the causal influence of AA on temperature using observational and re-analysis data over Indian subcontinent using cross correlation (CCs) and Granger causality (GC) (Granger, 1969). Aerosol index (AI) from TOMS-OMI was used as index for AA while ERA-interim reanalysis data was used for temperature at varying altitude. Period of study was March-April-May-June (MAMJ) for years 1979-2015. CCs were calculated for all the atmospheric layers. In each layer nearby and distant pixels (>500 kms) with high CCs were identified using clustering technique. It was found that that AI and Temperature shows statistically significant cross-correlations for co-located and distant pixels and more prominently over IGP. The CCs fades away with higher altitudes. CCs analysis was followed by GC analysis to identify the lag over which AI can influence the Temperature. GC also supported the findings of CCs analysis. It is an early attempt to link persisting large temperature anomalies with absorbing aerosols and may help in identifying the role of absorbing aerosol in causing heat waves.

  7. The causal nexus between carbon dioxide emissions and agricultural ecosystem-an econometric approach.

    Science.gov (United States)

    Asumadu-Sarkodie, Samuel; Owusu, Phebe Asantewaa

    2017-01-01

    Achieving a long-term food security and preventing hunger include a better nutrition through sustainable systems of production, distribution, and consumption. Nonetheless, the quest for an alternative to increasing global food supply to meet the growing demand has led to the use of poor agricultural practices that promote climate change. Given the contribution of the agricultural ecosystem towards greenhouse gas (GHG) emissions, this study investigated the causal nexus between carbon dioxide emissions and agricultural ecosystem by employing a data spanning from 1961 to 2012. Evidence from long-run elasticity shows that a 1 % increase in the area of rice paddy harvested will increase carbon dioxide emissions by 1.49 %, a 1 % increase in biomass-burned crop residues will increase carbon dioxide emissions by 1.00 %, a 1 % increase in cereal production will increase carbon dioxide emissions by 1.38 %, and a 1 % increase in agricultural machinery will decrease carbon dioxide emissions by 0.09 % in the long run. There was a bidirectional causality between carbon dioxide emissions, cereal production, and biomass-burned crop residues. The Granger causality shows that the agricultural ecosystem in Ghana is sensitive to climate change vulnerability.

  8. Causality between stock price and GDP in Turkey: An ARDL Bounds Testing Approach

    Directory of Open Access Journals (Sweden)

    Turgut Tursoy

    2016-12-01

    Full Text Available The study investigates the dynamic relationship between stock prices and GDP in Turkey using quarterly data from 1989Q2-2014Q2. The study investigated the interrelationship between the variables via auto regressive distributive lag (ARDL framework and ECM to analyse the existence of a long-run equilibrium relationship between gross domestic product and stock prices. The results provide strong evidence that both the stock prices and GDP are strongly cointegrated in the long-run. The empirical estimation indicated a significantly positive relationship between GDP and stock prices. The robustness of the ARDL model was confirmed by using Johansen and Juselius’s cointegration test (1990. The Granger causality test results indicate a long-run bidirectional causality between stock prices and GDP, and also a uni-directional causality from GDP to stock prices in the short-run. Both the stock prices and the economic growth are directly linked with each other. The reliability and validity of our estimations are confirmed by the diagnostics and the CUSUM test.

  9. Aviation Demand and Economic Growth in the Czech Republic: Cointegration Estimation and Causality Analysis

    Directory of Open Access Journals (Sweden)

    Bilal Mehmood

    2014-03-01

    Full Text Available The main purpose of the paper is to empirically examine the aviation-led growth hypothesis for the Czech Republic by testing causality between aviation and economic growth. We resort to econometric tests such as unit root tests and test of cointegration purposed by Johansen (1988. Fully Modified OLS, Dynamic OLS and Conical Cointegration Regression are used to estimate the cointegration equation for time span of 42 years from 1970 to 2012. Empirical results reveal the existence of cointegration between aviation demand and economic growth. Graphic methods such as Cholesky impulse response function (both accumulated and non-accumulated and variance decomposition have also been applied to render the analysis rigorous. The positive contribution of aviation demand to economic growth is similar in all three estimation techniques of cointegration equation. Finally, Granger causality test is also applied to find the direction of causal relationship. Findings help in lime-lighting the importance of aviation industry in economic growth for a developing country like the Czech Republic.

  10. Energy Consumption and Economic Growth in Vietnam: Threshold Cointegration and Causality Analysis

    Directory of Open Access Journals (Sweden)

    BINH Thanh PHUNG

    2011-01-01

    Full Text Available This study investigates the energy consumption-growth nexus in Vietnam. The causal relationship between the logarithm of per capita energy consumption (LPCEC and the logarithm of per capita GDP (LPCGDP during the 1976-2010 period is examined using the threshold cointegration and vector error correction models for Granger causality tests. The estimation results indicate that the LPCEC and LPCGDP for Vietnam are cointegrated and that there is a strong uni-directional causality running from LPCGDP to LPCEC, but not vice versa. It is also found that the effect of LPCGDP on LPCEC in Vietnam is time-varying (i.e. significantly different between before and after the structural breakpoint, 1992. The research results strongly support the neoclassical perspective that energy consumption is not a limiting factor to economic growth in Vietnam. Accordingly, an important policy implication resulting from this analysis is that government can pursue the conservation energy policies that aim at curtailing energy use for environmental friendly development purposes without creating severe effects on economic growth. In future, the energy should be efficiently allocated into more productive sectors of the economy.

  11. Re-thinking local causality

    NARCIS (Netherlands)

    Friederich, Simon

    2015-01-01

    There is widespread belief in a tension between quantum theory and special relativity, motivated by the idea that quantum theory violates J. S. Bell's criterion of local causality, which is meant to implement the causal structure of relativistic space-time. This paper argues that if one takes the es

  12. Expert Causal Reasoning and Explanation.

    Science.gov (United States)

    Kuipers, Benjamin

    The relationship between cognitive psychologists and researchers in artificial intelligence carries substantial benefits for both. An ongoing investigation in causal reasoning in medical problem solving systems illustrates this interaction. This paper traces a dialectic of sorts in which three different types of causal resaoning for medical…

  13. Introduction to causal dynamical triangulations

    DEFF Research Database (Denmark)

    Görlich, Andrzej

    2013-01-01

    The method of causal dynamical triangulations is a non-perturbative and background-independent approach to quantum theory of gravity. In this review we present recent results obtained within the four dimensional model of causal dynamical triangulations. We describe the phase structure of the mode...

  14. Causal Inference and Developmental Psychology

    Science.gov (United States)

    Foster, E. Michael

    2010-01-01

    Causal inference is of central importance to developmental psychology. Many key questions in the field revolve around improving the lives of children and their families. These include identifying risk factors that if manipulated in some way would foster child development. Such a task inherently involves causal inference: One wants to know whether…

  15. Theory-Based Causal Induction

    Science.gov (United States)

    Griffiths, Thomas L.; Tenenbaum, Joshua B.

    2009-01-01

    Inducing causal relationships from observations is a classic problem in scientific inference, statistics, and machine learning. It is also a central part of human learning, and a task that people perform remarkably well given its notorious difficulties. People can learn causal structure in various settings, from diverse forms of data: observations…

  16. Causal Attributions of Shy Subjects.

    Science.gov (United States)

    Teglasi, Hedwig; Hoffman, Mary Ann

    1982-01-01

    Causal attributions of shy students (N=36) were compared with those of a comparison group of students (N=36) in ten situations. Significant differences between the two groups emerged when explaining outcomes of situations considered to be problematic for shy individuals. Causal attributions may reflect realistic and situation-specific…

  17. Re-thinking local causality

    NARCIS (Netherlands)

    Friederich, Simon

    2015-01-01

    There is widespread belief in a tension between quantum theory and special relativity, motivated by the idea that quantum theory violates J. S. Bell's criterion of local causality, which is meant to implement the causal structure of relativistic space-time. This paper argues that if one takes the es

  18. Causal Inference and Developmental Psychology

    Science.gov (United States)

    Foster, E. Michael

    2010-01-01

    Causal inference is of central importance to developmental psychology. Many key questions in the field revolve around improving the lives of children and their families. These include identifying risk factors that if manipulated in some way would foster child development. Such a task inherently involves causal inference: One wants to know whether…

  19. Neural Correlates of Causal Power Judgments

    Directory of Open Access Journals (Sweden)

    Denise Dellarosa Cummins

    2014-12-01

    Full Text Available Causal inference is a fundamental component of cognition and perception. Probabilistic theories of causal judgment (most notably causal Bayes networks derive causal judgments using metrics that integrate contingency information. But human estimates typically diverge from these normative predictions. This is because human causal power judgments are typically strongly influenced by beliefs concerning underlying causal mechanisms, and because of the way knowledge is retrieved from human memory during the judgment process. Neuroimaging studies indicate that the brain distinguishes causal events from mere covariation, and between perceived and inferred causality. Areas involved in error prediction are also activated, implying automatic activation of possible exception cases during causal decision-making.

  20. On causality of extreme events

    Directory of Open Access Journals (Sweden)

    Massimiliano Zanin

    2016-06-01

    Full Text Available Multiple metrics have been developed to detect causality relations between data describing the elements constituting complex systems, all of them considering their evolution through time. Here we propose a metric able to detect causality within static data sets, by analysing how extreme events in one element correspond to the appearance of extreme events in a second one. The metric is able to detect non-linear causalities; to analyse both cross-sectional and longitudinal data sets; and to discriminate between real causalities and correlations caused by confounding factors. We validate the metric through synthetic data, dynamical and chaotic systems, and data representing the human brain activity in a cognitive task. We further show how the proposed metric is able to outperform classical causality metrics, provided non-linear relationships are present and large enough data sets are available.

  1. On causality of extreme events

    Science.gov (United States)

    2016-01-01

    Multiple metrics have been developed to detect causality relations between data describing the elements constituting complex systems, all of them considering their evolution through time. Here we propose a metric able to detect causality within static data sets, by analysing how extreme events in one element correspond to the appearance of extreme events in a second one. The metric is able to detect non-linear causalities; to analyse both cross-sectional and longitudinal data sets; and to discriminate between real causalities and correlations caused by confounding factors. We validate the metric through synthetic data, dynamical and chaotic systems, and data representing the human brain activity in a cognitive task. We further show how the proposed metric is able to outperform classical causality metrics, provided non-linear relationships are present and large enough data sets are available. PMID:27330866

  2. Early History of Oral Contraceptive Pill in Finland: The Diffusion of the New Contraceptive and Fertility Patterns

    Directory of Open Access Journals (Sweden)

    Aura Pasila

    2011-01-01

    Full Text Available The 1960s is often characterized as a decade of outstanding social and demographic changes in Western societies. The introduction of the contraceptive pill is assumed to have contributed to these changes. Yet the social as well as the demographic significance of the pill is ambiguous. This article has two aims: 1 to describe the early history of the pill in Finland in the 1960s and in the early 1970s and 2 to explore relationships between fertility and the pill. Surveys, pharmaceutical market data, and estimations are used to depict the diffusion of the pill. Based on calculated user percentages, the pill was adopted neither instantly nor extremely widely in Finland during the period under study. The results show that the diffusion coincided with fertility decline and other changes in fertility patterns. However, a causal connection of any kind cannot be established due to a lack of sufficient data.

  3. CausalTrail: Testing hypothesis using causal Bayesian networks.

    Science.gov (United States)

    Stöckel, Daniel; Schmidt, Florian; Trampert, Patrick; Lenhof, Hans-Peter

    2015-01-01

    Summary Causal Bayesian Networks are a special class of Bayesian networks in which the hierarchy directly encodes the causal relationships between the variables. This allows to compute the effect of interventions, which are external changes to the system, caused by e.g. gene knockouts or an administered drug. Whereas numerous packages for constructing causal Bayesian networks are available, hardly any program targeted at downstream analysis exists. In this paper we present CausalTrail, a tool for performing reasoning on causal Bayesian networks using the do-calculus. CausalTrail's features include multiple data import methods, a flexible query language for formulating hypotheses, as well as an intuitive graphical user interface. The program is able to account for missing data and thus can be readily applied in multi-omics settings where it is common that not all measurements are performed for all samples. Availability and Implementation CausalTrail is implemented in C++ using the Boost and Qt5 libraries. It can be obtained from https://github.com/dstoeckel/causaltrail.

  4. Local Activity and Causal Connectivity in Children with Benign Epilepsy with Centrotemporal Spikes.

    Directory of Open Access Journals (Sweden)

    Yun Wu

    Full Text Available The aim of the current study was to localize the epileptic focus and characterize its causal relation with other brain regions, to understand the cognitive deficits in children with benign childhood epilepsy with centrotemporal spikes (BECTS. Resting-state functional magnetic resonance imaging (fMRI was performed in 37 children with BECTS and 25 children matched for age, sex and educational achievement. We identified the potential epileptogenic zone (EZ by comparing the amplitude of low frequency fluctuation (ALFF of spontaneous blood oxygenation level dependent fMRI signals between the groups. Granger causality analysis was applied to explore the causal effect between EZ and the whole brain. Compared with controls, children with BECTS had significantly increased ALFF in the right postcentral gyrus and bilateral calcarine, and decreased ALFF in the left anterior cingulate cortex, bilateral putaman/caudate, and left cerebellum. ALFF values in the putaman/caudate were positively correlated with verbal IQ scores in patients. The ALFF values in cerebellum and performance IQ scores were negatively correlated in patients. These results suggest that ALFF disturbances in the putaman/caudate and cerebellum play an important role in BECTS cognitive dysfunction. Compared with controls, the patients showed increased driving effect from the EZ to the right medial frontal cortex and posterior cingulate cortex and decreased causal effects from the EZ to left inferior frontal gyrus. The causal effect of the left inferior frontal gyrus negatively correlated with disease duration, which suggests a relation between the epileptiform activity and language impairment. All together, these findings provide additional insight into the neurophysiological mechanisms of epilepitogenisis and cognitive dysfunction associated with BECTS.

  5. Clear message for causality

    Energy Technology Data Exchange (ETDEWEB)

    Steinberg, Aephraim M. [Institute for Experimental Physics, University of Vienna, Vienna (Austria)

    2003-12-01

    Experiment confirms that information cannot be transmitted faster than the speed of light. Ever since Einstein stated that nothing can travel faster than light, physicists have delighted in finding exceptions. One after another, observations of such 'superluminal' propagation have been made. However, while some image or pattern- such as the motion of a spotlight projected on a distant wall - might have appeared to travel faster than light, it seemed that there was no way to use the superluminal effect to transmit energy or information. In recent years, the superluminal propagation of light pulses through certain media has led to renewed controversy. In 1995, for example, Guenther Nimtz of the University of Cologne encoded Mozart's 40th Symphony on a microwave beam, which he claimed to have transmitted at a speed faster than light. Others maintain that such a violation of Einstein's speed limit would wreak havoc on our most fundamental ideas about causality, allowing an effect to precede its cause. Relativity teaches us that sending a signal faster than light would be equivalent to sending it backwards in time. (U.K.)

  6. History, causality, and sexology.

    Science.gov (United States)

    Money, John

    2003-08-01

    In 1896, Krafft-Ebing published Psychopathia Sexualis. Popularly defined as hereditary weakness or taintedness in the family pedigree, degeneracy was called upon as a causal explanation for perversions of the sexual instinct. Although Krafft-Ebing accepted Karl Ulrichs proposal that homosexuality could be innate and probably located in the brain, he paid little attention to neuropathological sexology. Alfred Binet challenged Krafft-Ebing's orthodoxy by explaining fetishism in terms of associative learning, to which Krafft-Ebing's response was that only those with a hereditary taint would be vulnerable. Thus did the venerable nature-nurture antithesis maintain its rhetoric, even to the present day. Krafft-Ebing died too soon to meet the Freudian challenge of endopsychic determinism, and too soon also to encounter the idea of a developmental multivariate outcome of what I have termed the lovemap. Like other brain maps, for example the languagemap, the lovemap requires an intact human brain in which to develop. The personalized content of the lovemap has access to the brain by way of the special senses.

  7. On the causal links between health indicator, output, combustible renewables and waste consumption, rail transport, and CO2 emissions: the case of Tunisia.

    Science.gov (United States)

    Ben Jebli, Mehdi

    2016-08-01

    This study employs the autoregressive distributed lag (ARDL) approach and Granger causality test to investigate the short- and long-run relationships between health indicator, real GDP, combustible renewables and waste consumption, rail transport, and carbon dioxide (CO2) emissions for the case of Tunisia, spanning the period of 1990-2011. The empirical findings suggest that the Fisher statistic of the Wald test confirm the existence of a long-run relationship between the variables. Moreover, the long-run estimated elasticities of the ARDL model provide that output and combustible renewables and waste consumption have a positive and statistically significant impact on health situation, while CO2 emissions and rail transport both contribute to the decrease of health indicator. Granger causality results affirm that, in the short-run, there is a unidirectional causality running from real GDP to health, a unidirectional causality from health to combustible renewables and waste consumption, and a unidirectional causality from all variables to CO2 emissions. In the long-run, all the computed error correction terms are significant and confirm the existence of long-run association among the variables. Our recommendations for the Tunisian policymakers are as follows: (i) exploiting wastes and renewable fuels can be a good strategy to eliminate pollution caused by emissions and subsequently improve health quality, (ii) the use of renewable energy as a main source for national rail transport is an effective strategy for public health, (iii) renewable energy investment projects are beneficial plans for the country as this contributes to the growth of its own economy and reduce energy dependence, and (iii) more renewable energy consumption leads not only to decrease pollution but also to stimulate health situation because of the increase of doctors and nurses numbers.

  8. Business models of heat entrepreneurship in Finland

    Energy Technology Data Exchange (ETDEWEB)

    Okkonen, Lasse [North Karelia University of Applied Sciences, Yliopistokatu 6, FI-80100 Joensuu (Finland); Suhonen, Niko [University of Eastern Finland, Department of Law, P.O. Box 111, FI-80101 Joensuu (Finland)

    2010-07-15

    This paper presents the business models of small-scale heat energy production in Finland. Firstly, the development of heat entrepreneurship in the country is presented, including the remarkable growth of small and medium size enterprises (SMEs) in the last 15 years. Secondly, the concept of business model (business architecture of product/service flows and earning logics) is modified to the framework of wood heat production. The business model concept, and its sub-concepts, is applied in a brief review of current heat energy businesses in Finland. We arrive at a business model of heat entrepreneurships that are public companies/utilities, public-private partnerships, private companies and cooperatives, Energy Saving Company (ESCO), network model of large enterprise and franchising. Descriptive cases of these models are presented. Finally, the paper concludes with a discussion on the applicability of the business models in different operational environments and geographical contexts. (author)

  9. Causal Selection and Counterfactual Reasoning

    Directory of Open Access Journals (Sweden)

    William Jiménez-Leal

    2013-01-01

    Full Text Available El trabajo defiende la posición según la cual el pensamiento contrafactual depende de nuestra representación causal del mundo y, en este sentido, argumenta que existe una estrecha relación entre el razonamiento causal y el contrafactual. Se lleva a cabo una crítica a la teoría de la disociación de juicios de Mandel (Mandel, 2003b, que defiende la independencia funcional entre el proceso de selección causal y el razonamiento contrafactual en el contexto de la selección causal. En los experimentos realizados se manipularon algunos elementos de la semántica de la tarea con el fin de ilustrar aquellos casos en los que no se da la disociación entre el razonamiento causal y el contrafactual. En el Experimento 1, el nivel de descripción del evento objetivo se manipuló en una tarea de generación de listas y evaluación. El Experimento 2 replicó los hallazgos del Experimento 1 utilizando un sistema de codificación alternativo, mientras que el Experimento 3 realizó lo mismo utilizando un formato de respuesta alternativo. Los resultados de los experimentos apoyan la concepción del entendimiento causal propuesta por los modelos mentales causales.

  10. Special requirements of aquaponics in Finland

    OpenAIRE

    Soppela, Olli

    2016-01-01

    This thesis brings together observations about special features that should be taken into consideration when designing the technical aspects of aquaponics practices and production units in Finland. Market demands, water purification and facility temperature control methods; sources of healthy feed and the needs for artificial lighting vary significantly around the globe. The unique combination of climate conditions, legislation and zoological conditions should be taken into consideration whe...

  11. Discrete causal theory emergent spacetime and the causal metric hypothesis

    CERN Document Server

    Dribus, Benjamin F

    2017-01-01

    This book evaluates and suggests potentially critical improvements to causal set theory, one of the best-motivated approaches to the outstanding problems of fundamental physics. Spacetime structure is of central importance to physics beyond general relativity and the standard model. The causal metric hypothesis treats causal relations as the basis of this structure. The book develops the consequences of this hypothesis under the assumption of a fundamental scale, with smooth spacetime geometry viewed as emergent. This approach resembles causal set theory, but differs in important ways; for example, the relative viewpoint, emphasizing relations between pairs of events, and relationships between pairs of histories, is central. The book culminates in a dynamical law for quantum spacetime, derived via generalized path summation.

  12. Classical planning and causal implicatures

    DEFF Research Database (Denmark)

    Blackburn, Patrick Rowan; Benotti, Luciana

    to generate clarification requests"; as a result we can model task-oriented dialogue as an interactive process locally structured by negotiation of the underlying task. We give several examples of Frolog-human dialog, discuss the limitations imposed by the classical planning paradigm, and indicate......In this paper we motivate and describe a dialogue manager (called Frolog) which uses classical planning to infer causal implicatures. A causal implicature is a type of Gricean relation implicature, a highly context dependent form of inference. As we shall see, causal implicatures are important...

  13. Classical planning and causal implicatures

    DEFF Research Database (Denmark)

    Blackburn, Patrick Rowan; Benotti, Luciana

    In this paper we motivate and describe a dialogue manager (called Frolog) which uses classical planning to infer causal implicatures. A causal implicature is a type of Gricean relation implicature, a highly context dependent form of inference. As we shall see, causal implicatures are important...... to generate clarification requests"; as a result we can model task-oriented dialogue as an interactive process locally structured by negotiation of the underlying task. We give several examples of Frolog-human dialog, discuss the limitations imposed by the classical planning paradigm, and indicate...

  14. The esoteric milieu in Finland today

    Directory of Open Access Journals (Sweden)

    Jussi Sohlberg

    2008-01-01

    Full Text Available As in the other Scandinavian countries, so in Finland an exceptionally high percentage of the population belongs to a religious community. Today, about 82 per cent of Finns are members of the Evangelical Lutheran Church. However, the picture of the Finnish religious and spiritual landscape is more complex than it may at first appear. The project ‘Religions in Finland’ was started in 2003. The project is a joint-effort of the Church Research Institute and the Research Network for the Study of New Religious Movements. The aim is to create an electronic database for describing, mapping and analysing religious associations and communities in Finland (active ones and also those that no longer exist. In August 2007 there were 777 communities and organizations listed in the database. They are classified into ten categories representing religious traditions according to their historical and cultural background. There are 29 organizations classified under the category Western esotericism. This article presents a general overview of the major and recently founded esoteric groups in Finland, most of which are registered associations.

  15. Sylvatic Trichinella spp. infection in Finland.

    Science.gov (United States)

    Airas, Niina; Saari, Seppo; Mikkonen, Taina; Virtala, Anna-Maija; Pellikka, Jani; Oksanen, Antti; Isomursu, Marja; Kilpelä, Seija-Sisko; Lim, Chae W; Sukura, Antti

    2010-02-01

    Although human infections caused by Trichinella sp. have not been reported in Finland for several decades and Trichinella sp. infection in pork has become virtually extinct in the last decade, sylvatic Trichinella spp. infection is still highly prevalent in Finland. Muscle digestion of 2,483 carnivorous wild animals from 9 host species during 1999-2005 showed 617 positive animals (24.8%). Molecular identification from 328 larval isolates revealed 4 different endemic Trichinella species, i.e., T. nativa, T. spiralis, T. britovi, and T. pseudospiralis. Seven percent of the infected animals carried mixed infections. Trichinella nativa was the most common species (74%), but T. spiralis was identified in 12%, T. britovi in 6%, and T. pseudospiralis in 1% of the animals. Host species showed different sample prevalence and Trichinella species distribution. Geographical distribution also varied, with the southern part of the country having significantly higher percentages than the northern part. Infection density was dependent on both the infecting Trichinella species and the host species. Trichinella spiralis was discovered in areas with no known domestic infection cases, indicating that it can also occur in the sylvatic cycle. Raccoon dogs and red foxes are the most important reservoir animals for T. spiralis , as well as for the sylvatic Trichinella species in Finland.

  16. Growing power. Bioenergy technology from Finland

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-12-01

    Finland tops the statistics for the industrialised world in the utilisation of bioenergy. In 1995 bioenergy, including energy generated with peat and pulping black liquor, accounted for over 20 per cent of the total energy consumption. Biomass is the primary energy source for 18 per cent of electricity consumed in Finland. It is the declared goal of the government to increase the use of bioenergy by a minimum of 25 per cent (1.5 million toe) by the year 2005. Research and development plays a central role in the promotion of an expanded use of bioenergy in Finland. The aim is to identify and develop technologies for establishing and sustaining economically, environmentally and socially viable bioenergy niches in the energy system. This publication deals with the fuel supply chain from forest to plant, local fuels efficiently utilised, Biomass in combined heat and power production, Fluidised bed boilers for biomass. Efficient combustion-low omissions, Biomass co-fired, Co-combustion based on gasification, The art of burning wet fuels, Heating boiler conversion from oil to biomass, Attractive space heating, Advanced technologies - more power out of biomass, and Research and Development. The publication consists of technical and applications of plants, too

  17. Empowerment Experiences of Kenyan Mothers living in Finland

    OpenAIRE

    Ndungu, Lucy

    2010-01-01

    ABSTRACT Ndungu Lucy. Empowerment experiences of Kenyan mothers living in Finland. Järvenpää, Spring 2010, 41 p., 2 appendices. Diaconia University of Applied Sciences, Diak South, Järvenpää Unit, Degree programme in Social Services. (UAS) The research was carried out in Helsinki area in Finland and it is based on Kenyan mothers' experiences. The aim of the study is to gain from opportunities Kenyan mothers attain in Finland, as empowerment tools to change Kenyans living standar...

  18. On causality of extreme events

    CERN Document Server

    Zanin, Massimiliano

    2016-01-01

    Multiple metrics have been developed to detect causality relations between data describing the elements constituting complex systems, all of them considering their evolution through time. Here we propose a metric able to detect causality within static data sets, by analysing how extreme events in one element correspond to the appearance of extreme events in a second one. The metric is able to detect both linear and non-linear causalities; to analyse both cross-sectional and longitudinal data sets; and to discriminate between real causalities and correlations caused by confounding factors. We validate the metric through synthetic data, dynamical and chaotic systems, and data representing the human brain activity in a cognitive task.

  19. Causal categories: relativistically interacting processes

    CERN Document Server

    Coecke, Bob

    2011-01-01

    A symmetric monoidal category naturally arises as the mathematical structure that organizes physical systems, processes, and composition thereof, both sequentially and in parallel. This structure admits a purely graphical calculus. This paper is concerned with the encoding of a fixed causal structure within a symmetric monoidal category: causal dependencies will correspond to topological connectedness in the graphical language. We show that correlations, either classical or quantum, force terminality of the tensor unit. We also show that well-definedness of the concept of a global state forces the monoidal product to be only partially defined, which in turn results in a relativistic covariance theorem. Except for these assumptions, at no stage do we assume anything more than purely compositional symmetric-monoidal categorical structure. We cast these two structural results in terms of a mathematical entity, which we call a `causal category'. We provide methods of constructing causal categories, and we study t...

  20. Fluctuations in Relativistic Causal Hydrodynamics

    CERN Document Server

    Kumar, Avdhesh; Mishra, Ananta P

    2013-01-01

    The formalism to calculate the hydrodynamics fluctuation using the quasi-stationary fluctuation theory of Onsager to the relativistic Navier-Stokes hydrodynamics is already known. In this work we calculate hydrodynamic fluctuations in relativistic causal theory of Muller, Israel and Stewart and other related causal hydrodynamic theories. We show that expressions for the Onsager coefficients and the correlation functions have form similar to the ones obtained by using Navier-Stokes equation. However, temporal evolution of the correlation functions obtained using MIS and the other causal theories can be significantly different than the correlation functions obtained using the Navier-Stokes equation. Finally, as an illustrative example, we explicitly plot the correlation functions obtained using the causal-hydrodynamics theories and compare them with correlation functions obtained by earlier authors using the expanding boost-invariant (Bjorken) flows.

  1. Boundary Terms for Causal Sets

    CERN Document Server

    Buck, Michel; Jubb, Ian; Surya, Sumati

    2015-01-01

    We propose a family of boundary terms for the action of a causal set with a spacelike boundary. We show that in the continuum limit one recovers the Gibbons-Hawking-York boundary term in the mean. We also calculate the continuum limit of the mean causal set action for an Alexandrov interval in flat spacetime. We find that it is equal to the volume of the codimension-2 intersection of the two light-cone boundaries of the interval.

  2. Causality constraints on TMD PDF

    CERN Document Server

    Efremov, A V

    2013-01-01

    In this short note, we discuss constraints on the transverse momentum dependent factorization formulae coming from the causality properties for the hadronic tensor. We show that the range of definition of the TMD PDFs in the transverse coordinate plane is wider that it is allowed by the causality. It indicates the presents of the large compensating corrections for the TMD PDF factorization theorem and/or overestimation of the transverse component dependence of TMD PDF.

  3. Correlation Measure Equivalence in Dynamic Causal Structures

    CERN Document Server

    Gyongyosi, Laszlo

    2016-01-01

    We prove an equivalence transformation between the correlation measure functions of the causally-unbiased quantum gravity space and the causally-biased standard space. The theory of quantum gravity fuses the dynamic (nonfixed) causal structure of general relativity and the quantum uncertainty of quantum mechanics. In a quantum gravity space, the events are causally nonseparable and all time bias vanishes, which makes it no possible to use the standard causally-biased entropy and the correlation measure functions. Since a corrected causally-unbiased entropy function leads to an undefined, obscure mathematical structure, in our approach the correction is made in the data representation of the causally-unbiased space. We prove that the standard causally-biased entropy function with a data correction can be used to identify correlations in dynamic causal structures. As a corollary, all mathematical properties of the causally-biased correlation measure functions are preserved in the causally-unbiased space. The eq...

  4. An introduction to causal inference.

    Science.gov (United States)

    Pearl, Judea

    2010-02-26

    This paper summarizes recent advances in causal inference and underscores the paradigmatic shifts that must be undertaken in moving from traditional statistical analysis to causal analysis of multivariate data. Special emphasis is placed on the assumptions that underlie all causal inferences, the languages used in formulating those assumptions, the conditional nature of all causal and counterfactual claims, and the methods that have been developed for the assessment of such claims. These advances are illustrated using a general theory of causation based on the Structural Causal Model (SCM) described in Pearl (2000a), which subsumes and unifies other approaches to causation, and provides a coherent mathematical foundation for the analysis of causes and counterfactuals. In particular, the paper surveys the development of mathematical tools for inferring (from a combination of data and assumptions) answers to three types of causal queries: those about (1) the effects of potential interventions, (2) probabilities of counterfactuals, and (3) direct and indirect effects (also known as "mediation"). Finally, the paper defines the formal and conceptual relationships between the structural and potential-outcome frameworks and presents tools for a symbiotic analysis that uses the strong features of both. The tools are demonstrated in the analyses of mediation, causes of effects, and probabilities of causation.

  5. 75 FR 57815 - Purified Carboxymethylcellulose From Finland, Mexico, Netherlands, and Sweden

    Science.gov (United States)

    2010-09-22

    ... COMMISSION Purified Carboxymethylcellulose From Finland, Mexico, Netherlands, and Sweden AGENCY: United... antidumping duty orders on purified carboxymethylcellulose from Finland, Mexico, Netherlands, and Sweden... antidumping duty orders on purified carboxymethylcellulose from Finland, Mexico, Netherlands, and Sweden...

  6. 75 FR 61700 - Purified Carboxymethylcellulose From Finland, the Netherlands, and Sweden: Final Results of the...

    Science.gov (United States)

    2010-10-06

    ... International Trade Administration Purified Carboxymethylcellulose From Finland, the Netherlands, and Sweden... purified carboxymethylcellulose (CMC) from, inter alia, Finland, the Netherlands, and Sweden, pursuant to... (120-day) sunset reviews of the Finland, the Netherlands, and Sweden antidumping duty orders...

  7. 76 FR 29191 - Purified Carboxymethylcellulose From Finland and the Netherlands: Continuation of Antidumping...

    Science.gov (United States)

    2011-05-20

    ... International Trade Administration Purified Carboxymethylcellulose From Finland and the Netherlands... from Finland and the Netherlands would likely lead to continuation or recurrence of dumping and... orders on purified carboxymethylcellulose (purified CMC) from Finland and the Netherlands. See Notice...

  8. Causality and Tense - two temporal structure builders

    NARCIS (Netherlands)

    Oversteegen, E.

    2005-01-01

    By force of causes precede effects, causality contributes to the temporal meaning of discourse. In case of semantic causal relations, this contribution is straightforward, but in case of epistemic causal relations, it is not. In order to gain insight into the semantics of epistemic causal relations,

  9. Relationship between daylength and suicide in Finland

    Directory of Open Access Journals (Sweden)

    Lönnqvist Jouko

    2011-09-01

    Full Text Available Abstract Background Many previous studies have documented seasonal variation in suicides globally. We re-assessed the seasonal variation of suicides in Finland and tried to relate it to the seasonal variation in daylength and ambient temperature and in the discrepancy between local time and solar time. Methods The daily data of all suicides from 1969 to 2003 in Finland (N = 43,393 were available. The calendar year was divided into twelve periods according to the length of daylight and the routinely changing time difference between sun time and official time. The daily mean of suicide mortality was calculated for each of these periods and the 95% confidence intervals of the daily means were used to evaluate the statistical significance of the means. In addition, daily changes in sunshine hours and mean temperature were compared to the daily means of suicide mortality in two locations during these afore mentioned periods. Results A significant peak of the daily mean value of suicide mortality occurred in Finland between May 15th and July 25th, a period that lies symmetrically around the solstice. Concerning the suicide mortality among men in the northern location (Oulu, the peak was postponed as compared with the southern location (Helsinki. The daily variation in temperature or in sunshine did not have significant association with suicide mortality in these two locations. Conclusions The period with the longest length of the day associated with the increased suicide mortality. Furthermore, since the peak of suicide mortality seems to manifest later during the year in the north, some other physical or biological signals, besides the variation in daylight, may be involved. In order to have novel means for suicide prevention, the assessment of susceptibility to the circadian misalignment might help.

  10. Geochemical baseline studies of soil in Finland

    Science.gov (United States)

    Pihlaja, Jouni

    2017-04-01

    The soil element concentrations regionally vary a lot in Finland. Mostly this is caused by the different bedrock types, which are reflected in the soil qualities. Geological Survey of Finland (GTK) is carrying out geochemical baseline studies in Finland. In the previous phase, the research is focusing on urban areas and mine environments. The information can, for example, be used to determine the need for soil remediation, to assess environmental impacts or to measure the natural state of soil in industrial areas or mine districts. The field work is done by taking soil samples, typically at depth between 0-10 cm. Sampling sites are chosen to represent the most vulnerable areas when thinking of human impacts by possible toxic soil element contents: playgrounds, day-care centers, schools, parks and residential areas. In the mine districts the samples are taken from the areas locating outside the airborne dust effected areas. Element contents of the soil samples are then analyzed with ICP-AES and ICP-MS, Hg with CV-AAS. The results of the geochemical baseline studies are published in the Finnish national geochemical baseline database (TAPIR). The geochemical baseline map service is free for all users via internet browser. Through this map service it is possible to calculate regional soil baseline values using geochemical data stored in the map service database. Baseline data for 17 elements in total is provided in the map service and it can be viewed on the GTK's web pages (http://gtkdata.gtk.fi/Tapir/indexEN.html).

  11. ExternE National Implementation Finland

    Energy Technology Data Exchange (ETDEWEB)

    Pingoud, K.; Maelkki, H.; Wihersaari, M.; Pirilae, P. [VTT Energy, Espoo (Finland); Hongisto, M. [Imatran Voima Oy, Vantaa (Finland); Siitonen, S. [Ekono Energy Ltd, Espoo (Finland); Johansson, M. [Finnish Environment Institute, Helsinki (Finland)

    1999-07-01

    ExternE National Implementation is a continuation of the ExternE Project, funded in part by the European Commission's Joule III Programme. This study is the result of the ExternE National Implementation Project for Finland. Three fuel cycles were selected for the Finnish study: coal, peat and wood-derived biomass, which together are responsible for about 40% of total electricity generation in Finland and about 75% of the non-nuclear fuel based generation. The estimated external costs or damages were dominated by the global warming (GW) impacts in the coal and peat fuel cycles, but knowledge of the true GW impacts is still uncertain. From among other impacts that were valued in monetary terms the human health damages due to airborne emissions dominated in all the three fuel cycles. Monetary valuation for ecosystem impacts is not possible using the ExternE methodology at present. The Meri-Pori power station representing the coal fuel cycle is one of the world's cleanest and most efficient coal-fired power plants with a condensing turbine. The coal is imported mainly from Poland. The estimated health damages were about 4 mECU/kWh, crop damages an order of magnitude lower and damages caused to building materials two orders of magnitude lower. The power stations of the peat and biomass fuel cycles are of CHP type, generating electricity and heat for the district heating systems of two cities. Their fuels are of domestic origin. The estimated health damages allocated to electricity generation were about 5 and 6 mECU/kWh, respectively. The estimates were case-specific and thus an generalisation of the results to the whole electricity generation in Finland is unrealistic. Despite the uncertainties and limitations of the methodology, it is a promising tool in the comparison of similar kinds of fuel cycles, new power plants and pollution abatement technologies and different plant locations with each other. (orig.)

  12. Causal Stability Conditions for General Relativistic Spacetimes

    CERN Document Server

    Howard, E M

    2016-01-01

    A brief overview of some open questions in general relativity with important consequences for causality theory is presented, aiming to a better understanding of the causal structure of the spacetime. Special attention is accorded to the problem of fundamental causal stability conditions. Several questions are raised and some of the potential consequences of recent results regarding the causality problem in general relativity are presented. A key question is whether causality violating regions are locally allowed. The new concept of almost stable causality is introduced; meanwhile, related conditions and criteria for the stability and almost stability of the causal structure are discussed.

  13. Freemasonry and its social position in Finland

    Directory of Open Access Journals (Sweden)

    Nils G. Holm

    2008-01-01

    Full Text Available Freemasonry, with its roots in the seventeenth century, has had to suffer insults and some­times even attacks from society. In this article the author looks more closely at Free­masonry in Finland, where it first appeared in the mid-eighteenth century, in the light of the suspicion and negative treatment it had to suffer. The deprecatory attitude of individuals and various social organisations towards Freemasonry varied over time, but there was often an underlying suspicion among the general public. This was expressed in the form of legends and folk tales of a more or less dramatic nature.

  14. Silica, silicosis and cancer in Finland.

    Science.gov (United States)

    Partanen, T; Jaakkola, J; Tossavainen, A

    1995-01-01

    Approximately 100 000 Finnish workers are currently employed in jobs and tasks that may involve exposure to airborne silica dust. The major industries involved are mining and quarrying; production of glass, ceramics, bricks and other building materials; metal industry, particularly iron and steel founding; and construction. Over 1500 cases of silicosis have occurred in Finland since 1935. Tuberculosis has been a frequent complication of silicosis. Results of studies from several countries strongly suggest that silica dust also causes lung cancer. The results of the relevant Finnish epidemiologic and industrial hygiene studies addressing cancer risk and exposure to quartz dust are summarized.

  15. Parenting educational styles in Slovenia and Finland

    OpenAIRE

    Sevčnikar, Kaja

    2015-01-01

    In everyday life the subject of parenting and child upbringing is often discussed among people who find themselves in the role of parents, babysitters and grandparents striving for best results (Peček Čuk and Lesar, 2009). My thesis focuses on parenting styles of mothers and fathers in Slovenia and in Finland. In the first, theoretical part, I have explained the concepts of socialization and parenting. I have defined the meaning of the term family and different family types. I have also c...

  16. The salience network causally influences default mode network activity during moral reasoning

    Science.gov (United States)

    Wilson, Stephen M.; D’Esposito, Mark; Kayser, Andrew S.; Grossman, Scott N.; Poorzand, Pardis; Seeley, William W.; Miller, Bruce L.; Rankin, Katherine P.

    2013-01-01

    Large-scale brain networks are integral to the coordination of human behaviour, and their anatomy provides insights into the clinical presentation and progression of neurodegenerative illnesses such as Alzheimer’s disease, which targets the default mode network, and behavioural variant frontotemporal dementia, which targets a more anterior salience network. Although the default mode network is recruited when healthy subjects deliberate about ‘personal’ moral dilemmas, patients with Alzheimer’s disease give normal responses to these dilemmas whereas patients with behavioural variant frontotemporal dementia give abnormal responses to these dilemmas. We hypothesized that this apparent discrepancy between activation- and patient-based studies of moral reasoning might reflect a modulatory role for the salience network in regulating default mode network activation. Using functional magnetic resonance imaging to characterize network activity of patients with behavioural variant frontotemporal dementia and healthy control subjects, we present four converging lines of evidence supporting a causal influence from the salience network to the default mode network during moral reasoning. First, as previously reported, the default mode network is recruited when healthy subjects deliberate about ‘personal’ moral dilemmas, but patients with behavioural variant frontotemporal dementia producing atrophy in the salience network give abnormally utilitarian responses to these dilemmas. Second, patients with behavioural variant frontotemporal dementia have reduced recruitment of the default mode network compared with healthy control subjects when deliberating about these dilemmas. Third, a Granger causality analysis of functional neuroimaging data from healthy control subjects demonstrates directed functional connectivity from nodes of the salience network to nodes of the default mode network during moral reasoning. Fourth, this Granger causal influence is diminished in

  17. Contaminated water caused the first outbreak of giardiasis in Finland, 2007: a descriptive study.

    Science.gov (United States)

    Rimhanen-Finne, Ruska; Hänninen, Marja-Liisa; Vuento, Risto; Laine, Janne; Jokiranta, T Sakari; Snellman, Marja; Pitkänen, Tarja; Miettinen, Ilkka; Kuusi, Markku

    2010-08-01

    The severe sewage contamination of a drinking water distribution network affected inhabitants in the town of Nokia, Finland in November 2007-February 2008. One of the pathogens found in patient and environmental samples was Giardia, which for the first time was detected as the causal agent of an outbreak in Finland. To describe the existence and the importance of Giardia infections related to this outbreak, we described characteristics of the giardiasis cases and calculated the incidence of giardiasis as well as the frequency of positive Giardia tests both before and during the outbreak. Persons reported to the Finnish Infectious Disease Registry (FIDR) with Giardia infections were interviewed. The number of persons tested for Giardia was obtained from the Centre for Laboratory Medicine at the Tampere University Hospital. The investigations provided strong evidence that Giardia infections in Nokia resulted from the contaminated water. The proportion of persons testing positive for Giardia and the incidence of giardiasis multiplied during the outbreak. To improve outbreak management, national guidelines on testing environmental samples for Giardia should be developed, and further resources should be allocated to both clinical and environmental laboratories that perform parasitological analyses.

  18. Human causal discovery from observational data.

    OpenAIRE

    1996-01-01

    Utilizing Bayesian belief networks as a model of causality, we examined medical students' ability to discover causal relationships from observational data. Nine sets of patient cases were generated from relatively simple causal belief networks by stochastic simulation. Twenty participants examined the data sets and attempted to discover the underlying causal relationships. Performance was poor in general, except at discovering the absence of a causal relationship. This work supports the poten...

  19. The Geometry of Small Causal Cones

    CERN Document Server

    Jubb, Ian

    2016-01-01

    We derive a formula for the spacetime volume of a small causal cone. We use this formula within the context of causal set theory to construct causal set expressions for certain geometric quantities relating to a spacetime with a spacelike hypersurface. We also consider a scalar field on the causal set, and obtain causal set expressions relating to its normal derivatives with respect to the hypersurface.

  20. Youth Suicide Trends in Finland, 1969-2008

    Science.gov (United States)

    Lahti, Anniina; Rasanen, Pirkko; Riala, Kaisa; Keranen, Sirpa; Hakko, Helina

    2011-01-01

    Background: There are only a few recent studies on secular trends in child and adolescent suicides. We examine here trends in rates and methods of suicide among young people in Finland, where suicide rates at these ages are among the highest in the world. Methods: The data, obtained from Statistics Finland, consisted of all suicides (n = 901)…

  1. Folkeskolen kan lære af Finland

    DEFF Research Database (Denmark)

    Andersen, Frans Ørsted

    2010-01-01

    Kronikken er en kommentar til den aktuelle danske debat om skolelukninger og -sammenlægninger - med udsyn til USA og Finland......Kronikken er en kommentar til den aktuelle danske debat om skolelukninger og -sammenlægninger - med udsyn til USA og Finland...

  2. Brug af alternativ isolering i Finland og Sverige

    DEFF Research Database (Denmark)

    Hansen, Ernst Jan de Place

    2001-01-01

    Resume af rapport om anvendelse af alternative isoleringsmaterialer i Finland og Sverige, udarbejdet af SBI under Energistyrelsens udviklingsprogram "Miljø- og arbejdsmiljøvenlig isolering".......Resume af rapport om anvendelse af alternative isoleringsmaterialer i Finland og Sverige, udarbejdet af SBI under Energistyrelsens udviklingsprogram "Miljø- og arbejdsmiljøvenlig isolering"....

  3. The Discourse on Multicultural Education in Finland: Education for Whom?

    Science.gov (United States)

    Holm, Gunilla; Londen, Monica

    2010-01-01

    Finland is experiencing increased immigration and therefore increased cultural diversity in its schools. This paper examines the multicultural education discourse in Finland by analysing the national and municipal curricula for the comprehensive school, educational policy documents and teacher education curricula. The focus is on how multicultural…

  4. Monetary Policy, Inflation and Economic Growth in Pakistan: Exploring the Co-integration and Causality Relationships

    Directory of Open Access Journals (Sweden)

    Imran Sharif Chaudhry

    2012-12-01

    Full Text Available This paper investigates the long run and short run relationships of monetary policy, inflation and economic growth in Pakistan using co-integration and causality analysis during the period 0f 1972-2010. A large number of empirical studies on the relationshipsof monetary policy and inflation are available and most of these have analyzed the effectiveness of monetary policy in controlling inflation in Pakistan. The present study fills the gap in the literature by analyzing the nexus of monetary policy, inflation andgrowth in Pakistan. The results indicate that credit to private sector, the variable of financial depth, real exchange rate and budget deficit are found elastic and significant variables to influence the real GDP in Pakistan. The pair-wise Granger Causality results suggest that real GDP and real exchange rate are causing to each other bi-directionally. The real GDP also do cause financial depth (M2GD, domestic credit (CREDIT and budget deficit (BDEF uni-directionally. The real exchange rate is also causing thefinancial depth and budget deficit variables. The results are consistent with the empirical literature.

  5. Leadership in orchestra emerges from the causal relationships of movement kinematics.

    Directory of Open Access Journals (Sweden)

    Alessandro D'Ausilio

    Full Text Available Non-verbal communication enables efficient transfer of information among people. In this context, classic orchestras are a remarkable instance of interaction and communication aimed at a common aesthetic goal: musicians train for years in order to acquire and share a non-linguistic framework for sensorimotor communication. To this end, we recorded violinists' and conductors' movement kinematics during execution of Mozart pieces, searching for causal relationships among musicians by using the Granger Causality method (GC. We show that the increase of conductor-to-musicians influence, together with the reduction of musician-to-musician coordination (an index of successful leadership goes in parallel with quality of execution, as assessed by musical experts' judgments. Rigorous quantification of sensorimotor communication efficacy has always been complicated and affected by rather vague qualitative methodologies. Here we propose that the analysis of motor behavior provides a potentially interesting tool to approach the rather intangible concept of aesthetic quality of music and visual communication efficacy.

  6. Bounds test approach to cointegration and causality between nuclear energy consumption and economic growth in India

    Energy Technology Data Exchange (ETDEWEB)

    Wolde-Rufael, Yemane

    2010-01-15

    This paper attempts to examine the dynamic relationship between economic growth, nuclear energy consumption, labor and capital for India for the period 1969-2006. Applying the bounds test approach to cointegration developed by we find that there was a short- and a long-run relationship between nuclear energy consumption and economic growth. Using four long-run estimators we also found that nuclear energy consumption has a positive and a statistically significant impact on India's economic growth. Further, applying the approach to Granger causality and the variance decomposition approach developed by, we found a positive and a significant uni-directional causality running from nuclear energy consumption to economic growth without feedback. This implies that economic growth in India is dependent on nuclear energy consumption where a decrease in nuclear energy consumption may lead to a decrease in real income. For a fast growing energy-dependent economy this may have far-reaching implications for economic growth. India's economic growth can be frustrated if energy conservation measures are undertaken without due regard to the negative impact they have on economic growth. (author)

  7. La inversión extranjera directa y las exportaciones en tailandia. pruebas de causalidad de granger y equilibrio general

    OpenAIRE

    2010-01-01

    Los autores investigan la causalidad entre inversión directa y las exportaciones en el caso de Tailandia, un país caracterizado por un rapido crecimiento económico y de exportaciones, y por sus entradas de capital extranjero relativamente importantes. Sus resultados en prueba de causalidad de Granger contradicen los resultados de un estudio de equilibrio general, utilizando datos sobre la inversión japonesa en Tailandia. Los autores apuntan al riesgo de utilizar una sola metodología y sugiere...

  8. Causality and Primordial Tensor Modes

    CERN Document Server

    Baumann, Daniel

    2009-01-01

    We introduce the real space correlation function of $B$-mode polarization of the cosmic microwave background (CMB) as a probe of superhorizon tensor perturbations created by inflation. By causality, any non-inflationary mechanism for gravitational wave production after reheating, like global phase transitions or cosmic strings, must have vanishing correlations for angular separations greater than the angle subtended by the particle horizon at recombination, i.e. $\\theta \\gtrsim 2^\\circ$. Since ordinary $B$-modes are defined non-locally in terms of the Stokes parameters $Q$ and $U$ and therefore don't have to respect causality, special care is taken to define `causal $\\tilde B$-modes' for the analysis. We compute the real space $\\tilde B$-mode correlation function for inflation and discuss its detectability on superhorizon scales where it provides an unambiguous test of inflationary gravitational waves. The correct identification of inflationary tensor modes is crucial since it relates directly to the energy s...

  9. Relativistic causality and clockless circuits

    CERN Document Server

    Matherat, Philippe; 10.1145/2043643.2043650

    2011-01-01

    Time plays a crucial role in the performance of computing systems. The accurate modelling of logical devices, and of their physical implementations, requires an appropriate representation of time and of all properties that depend on this notion. The need for a proper model, particularly acute in the design of clockless delay-insensitive (DI) circuits, leads one to reconsider the classical descriptions of time and of the resulting order and causal relations satisfied by logical operations. This questioning meets the criticisms of classical spacetime formulated by Einstein when founding relativity theory and is answered by relativistic conceptions of time and causality. Applying this approach to clockless circuits and considering the trace formalism, we rewrite Udding's rules which characterize communications between DI components. We exhibit their intrinsic relation with relativistic causality. For that purpose, we introduce relativistic generalizations of traces, called R-traces, which provide a pertinent des...

  10. Causal analysis of academic performance.

    Science.gov (United States)

    Rao, D C; Morton, N E; Elston, R C; Yee, S

    1977-03-01

    Maximum likelihood methods are presented to test for the relations between causes and effects in linear path diagrams, without assuming that estimates of causes are free of error. Causal analysis is illustrated by published data of the Equal Educational Opportunity Survey, which show that American schools do not significantly modify socioeconomic differences in academic performance and that little of the observed racial difference in academic performance is causal. For two races differing by 15 IQ points, the differential if social class were randomized would be only about 3 points. The principle is stressed that a racial effect in a causal system may be environmental and that its etiology can be studied only by analysis of family resemblance in hybrid populations.

  11. Causal reasoning with mental models.

    Science.gov (United States)

    Khemlani, Sangeet S; Barbey, Aron K; Johnson-Laird, Philip N

    2014-01-01

    This paper outlines the model-based theory of causal reasoning. It postulates that the core meanings of causal assertions are deterministic and refer to temporally-ordered sets of possibilities: A causes B to occur means that given A, B occurs, whereas A enables B to occur means that given A, it is possible for B to occur. The paper shows how mental models represent such assertions, and how these models underlie deductive, inductive, and abductive reasoning yielding explanations. It reviews evidence both to corroborate the theory and to account for phenomena sometimes taken to be incompatible with it. Finally, it reviews neuroscience evidence indicating that mental models for causal inference are implemented within lateral prefrontal cortex.

  12. Causal reasoning with mental models

    Directory of Open Access Journals (Sweden)

    Sangeet eKhemlani

    2014-10-01

    Full Text Available This paper outlines the model-based theory of causal reasoning. It postulates that the core meanings of causal assertions are deterministic and refer to temporally-ordered sets of possibilities: A causes B to occur means that given A, B occurs, whereas A enables B to occur means that given A, it is possible for B to occur. The paper shows how mental models represent such assertions, and how these models underlie deductive, inductive, and abductive reasoning yielding explanations. It reviews evidence both to corroborate the theory and to account for phenomena sometimes taken to be incompatible with it. Finally, it reviews neuroscience evidence indicating that mental models for causal inference are implemented within lateral prefrontal cortex.

  13. Statistics, Causality and Bell's theorem

    CERN Document Server

    Gill, Richard D

    2012-01-01

    Bell's (1964) theorem is popularly supposed to establish the non-locality of quantum physics as a mathematical-physical theory. Building from this, observed violation of Bell's inequality in experiments such as that of Aspect and coworkers (1982) is popularly supposed to provide empirical proof of non-locality in the real world. This paper reviews recent work on Bell's theorem, linking it to issues in causality as understood by statisticians. The paper starts with a new proof of a strong (finite sample) version of Bell's theorem which relies only on elementary arithmetic and (counting) probability. This proof underscores the fact that Bell's theorem tells us that quantum theory is incompatible with the conjunction of three cherished and formerly uncontroversial physical principles, nicknamed here locality, realism, and freedom. The first, locality, is obviously connected to causality: causal influences need time to propagate spatially. Less obviously, the other two principles, realism and freedom, are also fo...

  14. Gravitation, Causality, and Quantum Consistency

    CERN Document Server

    Hertzberg, Mark P

    2016-01-01

    We examine the role of consistency with causality and quantum mechanics in determining the properties of gravitation. We begin by constructing two different classes of interacting theories of massless spin 2 particles -- gravitons. One involves coupling the graviton with the lowest number of derivatives to matter, the other involves coupling the graviton with higher derivatives to matter, making use of the linearized Riemann tensor. The first class requires an infinite tower of terms for consistency, which is known to lead uniquely to general relativity. The second class only requires a finite number of terms for consistency, which appears as a new class of theories of massless spin 2. We recap the causal consistency of general relativity and show how this fails in the second class for the special case of coupling to photons, exploiting related calculations in the literature. In an upcoming publication [1] this result is generalized to a much broader set of theories. Then, as a causal modification of general ...

  15. Causal Models for Risk Management

    Directory of Open Access Journals (Sweden)

    Neysis Hernández Díaz

    2013-12-01

    Full Text Available In this work a study about the process of risk management in major schools in the world. The project management tools worldwide highlights the need to redefine risk management processes. From the information obtained it is proposed the use of causal models for risk analysis based on information from the project or company, say risks and the influence thereof on the costs, human capital and project requirements and detect the damages of a number of tasks without tribute to the development of the project. A study on the use of causal models as knowledge representation techniques causal, among which are the Fuzzy Cognitive Maps (DCM and Bayesian networks, with the most favorable MCD technique to use because it allows modeling the risk information witho ut having a knowledge base either itemize.

  16. Introductive remarks on causal inference

    Directory of Open Access Journals (Sweden)

    Silvana A. Romio

    2013-05-01

    Full Text Available One of the more challenging issues in epidemiological research is being able to provide an unbiased estimate of the causal exposure-disease effect, to assess the possible etiological mechanisms and the implication for public health. A major source of bias is confounding, which can spuriously create or mask the causal relationship. In the last ten years, methodological research has been developed to better de_ne the concept of causation in epidemiology and some important achievements have resulted in new statistical models. In this review, we aim to show how a technique the well known by statisticians, i.e. standardization, can be seen as a method to estimate causal e_ects, equivalent under certain conditions to the inverse probability treatment weight procedure.

  17. Fuel peat utilisation in Finland: resource use and emissions

    Energy Technology Data Exchange (ETDEWEB)

    Leijting, J.

    1999-11-01

    The aim of the study was to inventorize the emissions and other stressors caused by fuel peat use in Finland. The life cycle approach was used to organise and compile the burdens associated with the fuel peat utilisation sector in the years 1994 and 1995. Fuel peat accounts for about 6.5 % of the total primary energy production in Finland. The study showed that most emissions out into the air occur during combustion of peat in energy plants. The emissions account for about 13 - 14 % of the CO{sub 2} emissions released by fossil fuel utilisation in Finland, for 12 % of the SO{sub 2} for 8 % of the N{sub 2}O and approximately 4 % of the NOR emissions released by anthropogenic sources in Finland. Phosphorus releases into waters contributes for about 0.2 % while nitrogen releases account for 0.3 % in the total anthropogenic discharge in Finland. (orig.) 88 refs.

  18. The development of climatic scenarios for Finland

    Energy Technology Data Exchange (ETDEWEB)

    Carter, T.; Tuomenvirta, H. [Finnish Meteorological Inst., Helsinki (Finland); Posch, M. [National Inst. of Public Health and the Environment, Bilthoven (Netherlands)

    1996-12-31

    One of the main objectives of the Finnish Research Programme on Climate Change (SILMU) has been to assess the possible impacts of future changes in climate due to the enhanced greenhouse effect on natural systems and human activities in Finland. In order to address this objective, it was first necessary to specify the types of climate changes to be expected in the Finnish region. Estimates of future climate are conventionally obtained using numerical models, which simulate the evolution of the future climate in response to radiative forcing due to changes in the composition of the atmosphere (i.e. of greenhouse gases and aerosols). However, there are large uncertainties in the model estimates because current knowledge and understanding of atmospheric processes remains incomplete. Since accurate predictions of climate change are not available, an alternative approach is to develop scenarios. These are plausible projections which reflect the best estimates to the future conditions but at the same time embrace the likely uncertainties attached to these estimates. In order to obtain expert opinion on the most appropriate methods of providing scenarios for SILMU, an International Workshop was organised in 1993. The recommendations of the Workshop formed the basis of the present project, initiated in 1994, to develop standard climatic scenarios for Finland

  19. Chernobyl fallout and cancer incidence in Finland.

    Science.gov (United States)

    Auvinen, Anssi; Seppä, Karri; Pasanen, Kari; Kurttio, Päivi; Patama, Toni; Pukkala, Eero; Heinävaara, Sirpa; Arvela, Hannu; Verkasalo, Pia; Hakulinen, Timo

    2014-05-01

    Twenty-five years have passed since the Chernobyl accident, but its health consequences remain to be well established. Finland was one of the most heavily affected countries by the radioactive fallout outside the former Soviet Union. We analyzed the relation of the estimated external radiation exposure from the fallout to cancer incidence in Finland in 1988-2007. The study cohort comprised all ∼ 3.8 million Finns who had lived in the same dwelling for 12 months following the accident (May 1986-April 1987). Radiation exposure was estimated using data from an extensive mobile dose rate survey. Cancer incidence data were obtained for the cohort divided into four exposure categories (the lowest with the first-year committed dose effect was observed for men, or other cancer sites. Our analysis of a large cohort over two decades did not reveal an increase in cancer incidence following the Chernobyl accident, with the possible exception of colon cancer among women. The largely null findings are consistent with extrapolation from previous studies suggesting that the effect is likely to remain too small to be empirically detectable and of little public health impact.

  20. Electricity statistics for Finland 1997; Saehkoetilasto 1997

    Energy Technology Data Exchange (ETDEWEB)

    Kangas, H.; Savolainen, T. [Adato Energia Oy, Helsinki (Finland)

    1998-12-01

    Until 1995 the electrical statistics information has according to the law about electric utilities and facilities been collected and handled by the Electrical Inspectorate. In 1996 the work was done by the Finnish Electricity Association and it was commissioned by the Ministry of Trade and Industry. Since 1996 the collection and handling of the information is based on the Electricity Market Act. The information is mainly submitted by the producers and distributors of electricity and processed since 1997 in Adato Energia Oy owned jointly by Finnish Energy Industries Federation, Finnish District Heating Association and Finnish Electricity Association. This action is based on a mutual contract of the Statistics Finland, Adato Energia Oy, Finnish Energy Industries Federation and Finnish Electricity Association. The Electricity Statistics for Finland 1997 contains several summaries about the consumption and the production. There is also summaries about the networks, the effects of electricity, the capacities of electricity, the fuels used in production and the dwellings heated by electric power. Like before a list of names, addresses, persons and telephone numbers is available. Additionally a list comprising the power consumption in all Finnish communes and a glossary in three languages (Finnish, Swedish and English) are included

  1. History of cosmic ray research in Finland

    Science.gov (United States)

    Usoskin, I. G.; Valtonen, E.; Vainio, R.; Tanskanen, P. J.; Aurela, A. M.

    2009-11-01

    The history of cosmic ray research in Finland can be traced back to the end of 1950s, when first ground-based cosmic ray measurements started in Turku. The first cosmic ray station was founded in Oulu in 1964 performing measurements of cosmic rays by a muon telescope, which was later complemented by a neutron monitor. Since the 1990s, several research centers and universities, such as The Finnish Meteorological Institute, Helsinki University of Technology, University of Oulu, University of Turku and University of Helsinki have been involved in space science projects, such as SOHO, AMS, Cluster, Cassini, BepiColombo, etc. At the same time, ground-based cosmic ray measurements have reached a new level, including a fully automatic on-line database in Oulu and a new muon measuring underground site in Pyhäsalmi. Research groups in Helsinki, Oulu and Turku have also extensive experience in theoretical investigations of different aspects of cosmic ray physics. Cosmic ray research has a 50-year long history in Finland, covering a wide range from basic long-running ground-based observations to high-technology space-borne instrumentation and sophisticated theoretical studies. Several generations of researchers have been involved in the study ensuring transfer of experience and building the recognized Finnish research school of cosmic ray studies.

  2. On Causality in Dynamical Systems

    CERN Document Server

    Harnack, Daniel

    2016-01-01

    Identification of causal links is fundamental for the analysis of complex systems. In dynamical systems, however, nonlinear interactions may hamper separability of subsystems which poses a challenge for attempts to determine the directions and strengths of their mutual influences. We found that asymmetric causal influences between parts of a dynamical system lead to characteristic distortions in the mappings between the attractor manifolds reconstructed from respective local observables. These distortions can be measured in a model-free, data-driven manner. This approach extends basic intuitions about cause-effect relations to deterministic dynamical systems and suggests a mathematically well defined explanation of results obtained from previous methods based on state space reconstruction.

  3. Cohomology with causally restricted supports

    CERN Document Server

    Khavkine, Igor

    2014-01-01

    De Rham cohomology with spacelike compact and timelike compact supports has recently been noticed to be of importance for understanding the structure of classical and quantum field theories on curved spacetimes. We compute these cohomology groups for globally hyperbolic spacetimes in terms of their standard de Rham cohomologies. The calculation exploits the fact that the de Rham-d'Alambert wave operator can be extended to a chain map that is homotopic to zero and that its causal Green function fits into a convenient exact sequence. This method extends also to the Calabi (or Killing-Riemann-Bianchi) complex and possibly other differential complexes. We also discuss generalized causal structures and functoriality.

  4. Kolmogorov Complexity, Causality And Spin

    CERN Document Server

    Shayda, Dara O

    2012-01-01

    A novel topological and computational method for 'motion' is described. Motion is constrained by inequalities in terms of Kolmogorov Complexity. Causality is obtained as the output of a high-pass filter, passing through only high values of Kolmogorov Complexity. Motion under the electromagnetic field described with immediate relationship with Subscript[G, 2] Holonomy group and its corresponding dense free 2-subgroup. Similar to Causality, Spin emerges as an immediate and inevitable consequence of high values of Kolmogorov Complexity. Consequently, the physical laws are nothing but a low-pass filter for small values of Kolmogorov Complexity.

  5. Information thermodynamics on causal networks.

    Science.gov (United States)

    Ito, Sosuke; Sagawa, Takahiro

    2013-11-01

    We study nonequilibrium thermodynamics of complex information flows induced by interactions between multiple fluctuating systems. Characterizing nonequilibrium dynamics by causal networks (i.e., Bayesian networks), we obtain novel generalizations of the second law of thermodynamics and the fluctuation theorem, which include an informational quantity characterized by the topology of the causal network. Our result implies that the entropy production in a single system in the presence of multiple other systems is bounded by the information flow between these systems. We demonstrate our general result by a simple model of biochemical adaptation.

  6. Local Causality, Probability and Explanation

    CERN Document Server

    Healey, Richard A

    2016-01-01

    In papers published in the 25 years following his famous 1964 proof John Bell refined and reformulated his views on locality and causality. Although his formulations of local causality were in terms of probability, he had little to say about that notion. But assumptions about probability are implicit in his arguments and conclusions. Probability does not conform to these assumptions when quantum mechanics is applied to account for the particular correlations Bell argues are locally inexplicable. This account involves no superluminal action and there is even a sense in which it is local, but it is in tension with the requirement that the direct causes and effects of events are nearby.

  7. Causality and micro-causality in curved spacetime

    Energy Technology Data Exchange (ETDEWEB)

    Hollowood, Timothy J. [Department of Physics, University of Wales Swansea, Swansea, SA2 8PP (United Kingdom)], E-mail: t.hollowood@swansea.ac.uk; Shore, Graham M. [Department of Physics, University of Wales Swansea, Swansea, SA2 8PP (United Kingdom)], E-mail: g.m.shore@swansea.ac.uk

    2007-10-25

    We consider how causality and micro-causality are realised in QED in curved spacetime. The photon propagator is found to exhibit novel non-analytic behaviour due to vacuum polarization, which invalidates the Kramers-Kronig dispersion relation and calls into question the validity of micro-causality in curved spacetime. This non-analyticity is ultimately related to the generic focusing nature of congruences of geodesics in curved spacetime, as implied by the null energy condition, and the existence of conjugate points. These results arise from a calculation of the complete non-perturbative frequency dependence of the vacuum polarization tensor in QED, using novel world-line path integral methods together with the Penrose plane-wave limit of spacetime in the neighbourhood of a null geodesic. The refractive index of curved spacetime is shown to exhibit superluminal phase velocities, dispersion, absorption (due to {gamma}{yields}e{sup +}e{sup -}) and bi-refringence, but we demonstrate that the wavefront velocity (the high-frequency limit of the phase velocity) is indeed c, thereby guaranteeing that causality itself is respected.

  8. The effects of tobacco sales promotion on initiation of smoking--experiences from Finland and Norway.

    Science.gov (United States)

    Rimpelä, M K; Aarø, L E; Rimpelä, A H

    1993-01-01

    Norway and Finland were among the first countries to adopt a total ban on tobacco sales promotion. Such legislation came into force in Norway and Finland in 1975 and 1978 respectively. These two countries are sometimes referred to as illustrations that such legislation has been successfully used as a means to reduce tobacco consumption. Tobacco industry spokesmen seem to interpret available evidence in the opposite way and maintain that the prohibition has not contributed to reducing the use of tobacco. Among the publications referred to and misused by tobacco industry spokesmen are publications from the authors of the present report. The effects of a ban on advertising can only be properly examined after describing a reasonable conceptual model. Such a model has to take into account (i) other social and cultural predictors of smoking, (ii) tobacco sales promotion in the contexts of all other mass communication, (iii) control measures other than a ban, and (iv) the degree of success in implementing the ban on advertising. Like any other kind of mass communication tobacco advertising influences the individual in a rather complex way. Behaviour change may be regarded as the outcome of an interpersonal and intrapersonal process. Social science research on tobacco advertising and the effects of banning such advertising has a short history, most studies having been carried out in the late 1980s. After examining available evidence related to the effects of tobacco advertising on the smoking habits of adolescents we conclude as follows: the few scientifically valid reports available today give both theoretical and empirical evidence for a causal relationship. Tobacco sales promotion seems both to promote and to reinforce smoking among young people. The dynamic tobacco market represented by children and adolescents is probably the main target of tobacco sales promotion. In Finland, there have been few studies explicitly addressing the causal links between tobacco sales

  9. Causal Categories: Relativistically Interacting Processes

    Science.gov (United States)

    Coecke, Bob; Lal, Raymond

    2013-04-01

    A symmetric monoidal category naturally arises as the mathematical structure that organizes physical systems, processes, and composition thereof, both sequentially and in parallel. This structure admits a purely graphical calculus. This paper is concerned with the encoding of a fixed causal structure within a symmetric monoidal category: causal dependencies will correspond to topological connectedness in the graphical language. We show that correlations, either classical or quantum, force terminality of the tensor unit. We also show that well-definedness of the concept of a global state forces the monoidal product to be only partially defined, which in turn results in a relativistic covariance theorem. Except for these assumptions, at no stage do we assume anything more than purely compositional symmetric-monoidal categorical structure. We cast these two structural results in terms of a mathematical entity, which we call a causal category. We provide methods of constructing causal categories, and we study the consequences of these methods for the general framework of categorical quantum mechanics.

  10. Causality problem in Economic Science

    Directory of Open Access Journals (Sweden)

    JOSÉ LUIS RETOLAZA

    2007-12-01

    Full Text Available The main point of the paper is the problem of the economy to be consider like a science in the most strict term of the concept. In the first step we are going to tackle a presentation about what we understand by science to subsequently present some of the fallacies which have bring certain scepticism about the scientific character of the investigation in economy, to know: 1 The differences between hard and weak sciences -physics and social; 2 The differences between paradigm, —positivist and phenomenological— 3 The differences between physic causalityand historic causality. In the second step we are going to talk about two fundamental problems which are questioned: 1 the confusion between ontology and gnoseology and, 2 the erroneous concept of causality that commonly is used. In the last step of the paper we are going over the recent models of «causal explanation» and we suggest the probabilistic casualty development next with a more elaborated models of causal explanation, like a way to conjugate the scientific severity with the possibility to tackle complex economic realities.

  11. Causal feedbacks in climate change

    NARCIS (Netherlands)

    Nes, van E.H.; Scheffer, M.; Brovkin, V.; Lenton, T.M.; Ye, H.; Deyle, E.; Sugihara, G.

    2015-01-01

    The statistical association between temperature and greenhouse gases over glacial cycles is well documented1, but causality behind this correlation remains difficult to extract directly from the data. A time lag of CO2 behind Antarctic temperature—originally thought to hint at a driving role for tem

  12. Causal Behaviour on Carter spacetime

    CERN Document Server

    Blanco, Oihane F

    2015-01-01

    In this work we will focus on the causal character of Carter Spacetime (see B. Carter, Causal structure in space-time, Gen. Rel. Grav. 1 4 337-406, 1971). The importance of this spacetime is the following: for the causally best well behaved spacetimes (the globally hyperbolic ones), there are several characterizations or alternative definitions. In some cases, it has been shown that some of the causal properties required in these characterizations can be weakened. But Carter spacetime provides a counterexample for an impossible relaxation in one of them. We studied the possibility of Carter spacetime to be a counterexample for impossible lessening in another characterization, based on the previous results. In particular, we will prove that the time-separation or Lorentzian distance between two chosen points in Carter spacetime is infinite. Although this spacetime turned out not to be the counterexample we were looking for, the found result is interesting per se and provides ideas for alternate approaches to t...

  13. An Introduction to Causal Inference

    Science.gov (United States)

    2009-11-02

    legitimize causal inference, has removed causation from its natural habitat, and distorted its face beyond recognition. This exclusivist attitude is...In contrast, when the mediation problem is approached from an exclusivist potential-outcome viewpoint, void of the structural guidance of Eq. (28

  14. Breaking the arrows of causality

    DEFF Research Database (Denmark)

    Valsiner, Jaan

    2014-01-01

    Theoretical models of catalysis have proven to bring with them major breakthroughs in chemistry and biology, from the 1830s onward. It can be argued that the scientific status of chemistry has become established through the move from causal to catalytic models. Likewise, the central explanatory...

  15. Learning a Theory of Causality

    Science.gov (United States)

    Goodman, Noah D.; Ullman, Tomer D.; Tenenbaum, Joshua B.

    2011-01-01

    The very early appearance of abstract knowledge is often taken as evidence for innateness. We explore the relative learning speeds of abstract and specific knowledge within a Bayesian framework and the role for innate structure. We focus on knowledge about causality, seen as a domain-general intuitive theory, and ask whether this knowledge can be…

  16. Free Fermions on causal sets

    CERN Document Server

    Noldus, Johan

    2013-01-01

    We construct a Dirac theory on causal sets; a key element in the construction being that the causet must be regarded as emergent in an appropriate sense too. We further notice that mixed norm spaces appear in the construction allowing for negative norm particles and "ghosts".

  17. Research of Causal Relations between Components of Foreign Trade and Economic Performance of the Region, Country and World

    Directory of Open Access Journals (Sweden)

    Frolov Sergey M.

    2016-02-01

    Full Text Available Causal relations between components of the region foreign trade turnover and indicators, which characterize the economic situation of the region, country and the world, have been studied. 3 groups of indicators, which can have an impact on the region export-import activity, were formed by the degree of the covered influence level: the level of region, country and world. All the selected indicators were tested for causality by Granger test. As a result of the study it has been found that the export of Sumy region is directly affected by the volume of industrial production, inflation rate in Ukraine and the world price for wheat. The export of services is affected by the volume of extended credits, income of the population per person, the world prices for corn and wheat. Causality has also been determined between the import of goods in Sumy region and indicators of extended credits, turnover of retail trade and wholesale trade of enterprises. As regards the import of services, the influence was recorded from the side of the official exchange rate of hryvnia to the US dollar and the price index of industrial producers. The prospect of further research in this direction is expansion of the set of indicators characterizing the economic activity of the region, country and the world. The further research can contribute to building up the export-import potential of the region.

  18. Carbon dioxide emissions, GDP, energy use, and population growth: a multivariate and causality analysis for Ghana, 1971-2013.

    Science.gov (United States)

    Asumadu-Sarkodie, Samuel; Owusu, Phebe Asantewaa

    2016-07-01

    In this study, the relationship between carbon dioxide emissions, GDP, energy use, and population growth in Ghana was investigated from 1971 to 2013 by comparing the vector error correction model (VECM) and the autoregressive distributed lag (ARDL). Prior to testing for Granger causality based on VECM, the study tested for unit roots, Johansen's multivariate co-integration and performed a variance decomposition analysis using Cholesky's technique. Evidence from the variance decomposition shows that 21 % of future shocks in carbon dioxide emissions are due to fluctuations in energy use, 8 % of future shocks are due to fluctuations in GDP, and 6 % of future shocks are due to fluctuations in population. There was evidence of bidirectional causality running from energy use to GDP and a unidirectional causality running from carbon dioxide emissions to energy use, carbon dioxide emissions to GDP, carbon dioxide emissions to population, and population to energy use. Evidence from the long-run elasticities shows that a 1 % increase in population in Ghana will increase carbon dioxide emissions by 1.72 %. There was evidence of short-run equilibrium relationship running from energy use to carbon dioxide emissions and GDP to carbon dioxide emissions. As a policy implication, the addition of renewable energy and clean energy technologies into Ghana's energy mix can help mitigate climate change and its impact in the future.

  19. Spatial-Temporal Synchrophasor Data Characterization and Analytics in Smart Grid Fault Detection, Identification, and Impact Causal Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, Huaiguang; Dai, Xiaoxiao; Gao, David Wenzhong; Zhang, Jun Jason; Zhang, Yingchen; Muljadi, Eduard

    2016-09-01

    An approach of big data characterization for smart grids (SGs) and its applications in fault detection, identification, and causal impact analysis is proposed in this paper, which aims to provide substantial data volume reduction while keeping comprehensive information from synchrophasor measurements in spatial and temporal domains. Especially, based on secondary voltage control (SVC) and local SG observation algorithm, a two-layer dynamic optimal synchrophasor measurement devices selection algorithm (OSMDSA) is proposed to determine SVC zones, their corresponding pilot buses, and the optimal synchrophasor measurement devices. Combining the two-layer dynamic OSMDSA and matching pursuit decomposition, the synchrophasor data is completely characterized in the spatial-temporal domain. To demonstrate the effectiveness of the proposed characterization approach, SG situational awareness is investigated based on hidden Markov model based fault detection and identification using the spatial-temporal characteristics generated from the reduced data. To identify the major impact buses, the weighted Granger causality for SGs is proposed to investigate the causal relationship of buses during system disturbance. The IEEE 39-bus system and IEEE 118-bus system are employed to validate and evaluate the proposed approach.

  20. The argumentative impact of causal relations

    DEFF Research Database (Denmark)

    Nielsen, Anne Ellerup

    1996-01-01

    such as causality, explanation and justification. In certain types of discourse, causal relations also imply an intentional element. This paper describes the way in which the semantic and pragmatic functions of causal markers can be accounted for in terms of linguistic and rhetorical theories of argumentation.......The semantic relations between and within utterances are marked by the use of connectors and adverbials. One type of semantic relations is causal relations expressed by causal markers such as because, therefore, so, for, etc. Some of these markers cover different types of causal relations...

  1. Entanglement, holography and causal diamonds

    Science.gov (United States)

    de Boer, Jan; Haehl, Felix M.; Heller, Michal P.; Myers, Robert C.

    2016-08-01

    We argue that the degrees of freedom in a d-dimensional CFT can be reorganized in an insightful way by studying observables on the moduli space of causal diamonds (or equivalently, the space of pairs of timelike separated points). This 2 d-dimensional space naturally captures some of the fundamental nonlocality and causal structure inherent in the entanglement of CFT states. For any primary CFT operator, we construct an observable on this space, which is defined by smearing the associated one-point function over causal diamonds. Known examples of such quantities are the entanglement entropy of vacuum excitations and its higher spin generalizations. We show that in holographic CFTs, these observables are given by suitably defined integrals of dual bulk fields over the corresponding Ryu-Takayanagi minimal surfaces. Furthermore, we explain connections to the operator product expansion and the first law of entanglemententropy from this unifying point of view. We demonstrate that for small perturbations of the vacuum, our observables obey linear two-derivative equations of motion on the space of causal diamonds. In two dimensions, the latter is given by a product of two copies of a two-dimensional de Sitter space. For a class of universal states, we show that the entanglement entropy and its spin-three generalization obey nonlinear equations of motion with local interactions on this moduli space, which can be identified with Liouville and Toda equations, respectively. This suggests the possibility of extending the definition of our new observables beyond the linear level more generally and in such a way that they give rise to new dynamically interacting theories on the moduli space of causal diamonds. Various challenges one has to face in order to implement this idea are discussed.

  2. Causal inference in obesity research.

    Science.gov (United States)

    Franks, P W; Atabaki-Pasdar, N

    2017-03-01

    Obesity is a risk factor for a plethora of severe morbidities and premature death. Most supporting evidence comes from observational studies that are prone to chance, bias and confounding. Even data on the protective effects of weight loss from randomized controlled trials will be susceptible to confounding and bias if treatment assignment cannot be masked, which is usually the case with lifestyle and surgical interventions. Thus, whilst obesity is widely considered the major modifiable risk factor for many chronic diseases, its causes and consequences are often difficult to determine. Addressing this is important, as the prevention and treatment of any disease requires that interventions focus on causal risk factors. Disease prediction, although not dependent on knowing the causes, is nevertheless enhanced by such knowledge. Here, we provide an overview of some of the barriers to causal inference in obesity research and discuss analytical approaches, such as Mendelian randomization, that can help to overcome these obstacles. In a systematic review of the literature in this field, we found: (i) probable causal relationships between adiposity and bone health/disease, cancers (colorectal, lung and kidney cancers), cardiometabolic traits (blood pressure, fasting insulin, inflammatory markers and lipids), uric acid concentrations, coronary heart disease and venous thrombosis (in the presence of pulmonary embolism), (ii) possible causal relationships between adiposity and gray matter volume, depression and common mental disorders, oesophageal cancer, macroalbuminuria, end-stage renal disease, diabetic kidney disease, nuclear cataract and gall stone disease, and (iii) no evidence for causal relationships between adiposity and Alzheimer's disease, pancreatic cancer, venous thrombosis (in the absence of pulmonary embolism), liver function and periodontitis.

  3. [Mental health in Chile and Finland: Challenges and lessons].

    Science.gov (United States)

    Retamal C, Pedro; Markkula, Niina; Peña, Sebastián

    2016-07-01

    This article analyses and compares the epidemiology of mental disorders and relevant public policies in Chile and Finland. In Chile, a specific mental health law is still lacking. While both countries highlight the role of primary care, Finland places more emphasis on participation and recovery of service users. Comprehensive mental health policies from Finland, such as a successful suicide prevention program, are presented. Both countries have similar prevalence of mental disorders, high alcohol consumption and high suicide rates. In Chile, the percentage of total disease burden due to psychiatric disorders is 13% and in Finland 14%. However, the resources to address these issues are very different. Finland spends 4.5% of its health budget on mental health, while in Chile the percentage is 2.2%. This results in differences in human resources and service provision. Finland has five times more psychiatric outpatient visits, four times more psychiatrists, triple antidepressant use and twice more clinical guidelines for different psychiatric conditions. In conclusion, both countries have similar challenges but differing realities. This may help to identify gaps and potential solutions for public health challenges in Chile. Finland’s experience demonstrates the importance of political will and long-term vision in the construction of mental health policies.

  4. 中国近百年地面温度变化自然因子的因果链分析%The Causal Chain Analysis of Natural Factors for China Sur face Temperature Variation during the Recent 100 Years

    Institute of Scientific and Technical Information of China (English)

    朱玉祥; 赵亮

    2014-01-01

    采用格兰杰(Granger)因果检验法,从自然因素的角度,即从天文因子(太阳黑子数SSN)和地球运动因子(地极移动X方向和Y方向)的角度,对我国近百年地面温度(TC)的变化进行了归因分析。所得结果如下:滞后1~11年内, SSN都不是TC的Granger原因;对于TC和极移X方向,当滞后6年时信度最高,此时极移X方向是TC的Granger原因(87%信度)。研究结果可能暗示,极移X方向的变化可能会导致6年后中国地面气温的变化。%The attribution analysis of China surface temperature(TC) in the recent 100 years is done from the angle of the astronomical factor(sunspot number, SSN) and the earth movement factor(polar shift x direction and y direction ) by using Granger causality test. The results are as follows:(1) SSN is not the Granger cause of TC in all of 1 to 11 years lags;(2) when the lag is 6 years, conifdence is the highest, at this time polar shift x direction is the Granger cause of TC (87%conifdence);(3) when the lag is 12 years, TC is the Granger cause of the polar shift y direction, the conifdence is 86%. The research results of the paper suggest that the change of polar shift x direction possibly results in the change of TC, and the change of TC possibly inlfuences the change of the polar shift y direction.

  5. Trends in occupational hygiene in Finland.

    Science.gov (United States)

    Pääkkönen, Rauno; Koponen, Milja

    2017-04-13

    The aim of this work is to evaluate and describe the current status of, and prospects for, the future of occupational hygiene in Finland. The main sources of information include a seminar held in the annual meeting of Finnish Occupational Hygiene Society and interviews with different stakeholders. Nanotechnology and other new materials, changing work environments, circular economy including green jobs, new medical methods and advances of construction methods were recognized as future challenges. Future work opportunities for occupational hygiene experts included exposure assessments in indoor air surveys, private consulting and entrepreneurship in general, international activities and product safety issues. Unclear topics needing more attention in the future were thought to be in new exposures, sensitive persons, combined effects, skin exposures and applicability of personal protective equipment. Occupational hygiene should broaden its view; occupational hygienists should have to cooperate with other specialists and grasp new challenges.

  6. Research News from Norway, Sweden, and Finland

    Directory of Open Access Journals (Sweden)

    Sven Skjenneberg

    1986-06-01

    Full Text Available Norge: 1 Forskningsavd ved Reindriftsadministrasjonen. 2 Avd. for arktisk biologi, Univ. i Tromsø 3 Viltforskningen ved DN, Trondheim 4 Institutt for biologi og geologi, Univ. i Tromsø 5 Institutt for husdyrnæring, Norges landbrukshøgskole 6 Institutt for zoologi, Norges landbrukshøgskole 7 Stipendiat Norges landbruksvit. forskningsråd 8 Statens veterinære laboratorium i Nord-Norge Sverige: 1 Renförsöksavdelningen, Sveriges lantbruksuniversitet 2 Statens veterinärmedicinska anstalt 3 Statens naturvårdsverk Finland: 1 Vilt- och fiskeriforskningsinstitutet, Renforskning 2 Kaamanen försöksstation, Renägareföreningen 3 Veterinärmedicinska högskolan 4 Helsingfors universitets husdjursvetenskapliga institut 5 Kuopios och Uleåborgs universiteter 6 Helsingfors universitets geologiska institut 7 Jyväskyläs universitet 8 Lantbrukets forskningscentral

  7. Information sources in science and technology in Finland

    Science.gov (United States)

    Haarala, Arja-Riitta

    1994-01-01

    Finland poses some problems to be overcome in the field of scientific and technical information: a small user community which makes domestic systems costly; great distances within the country between users and suppliers of information; great distances to international data systems and large libraries abroad; and inadequate collections of scientific and technical information. The national bibliography Fennica includes all books and journals published in Finland. Data base services available in Finland include: reference data bases in science and technology; data banks for decision making such as statistical time series or legal proceedings; national bibliographies; and library catalogs.

  8. Chinese Jiaotong Universities Presidents Delegation Visits Russia and Finland

    Institute of Scientific and Technical Information of China (English)

    Hu; Yang

    2014-01-01

    <正>At the invitation of the Russian St.Petersburg State Transport University and the Regional State Administrative Agency for Eastern Finland,the Chinese Jiao tong Universities Presidents Delegation,led by CPAFFC Secretary General Li Xikui,visited Russia and Finland,to attend the First Forum of Chinese and Russian Transport Universities’Presidents and hold exchanges with local governments and universities of Finland from May 19 to 26.The forum was jointly initiated and organized by the CPAFFC and

  9. DYNAMICS OF MUTUAL FUNDS IN RELATION TO STOCK MARKET: A VECTOR AUTOREGRESSIVE CAUSALITY ANALYSIS

    Directory of Open Access Journals (Sweden)

    Md. Shahadath Hossain

    2013-01-01

    Full Text Available In Bangladesh, primary and secondary mutual fund markets behave in a completely different way, where initial public offering (IPO investors of mutual funds earn more than 250 percent rerun, whereas secondary market investors cannot even manage to cover the opportunity cost of their investment. There are few other abnormalities present in this market – unlike everywhere in the world, most of the mutual funds are closed-end (92 percent and closed-end mutual funds are barred to issue bonus or right shares. A total of 714 day’s observations, from January 2008 to December 2010, of four variables– DSE (Dhaka Stock Exchange general index return, DSE general index turnover, mutual funds’ return and mutual funds’ turnover– are utilized. Stationarity of the variables are tested with Augmented Dickey-Fuller (ADF unit root test and found that variables are in different order of integration. Long-term equilibrium relationships among the variables are tested with Johansen cointegration and it is found that DSE general index return and mutual funds’ return are cointegrated. Toda-Yamamoto (TY version of granger non-causality test is employed and bidirectional causality is found moving from DSE (Dhaka Stock Exchange general index turnover to DSE general index return, whereas unidirectional causality is found moving from mutual fund’s return to DSE general index return, mutual funds’ return to mutual funds turnover, and DSE general index turnover to mutual funds turnover. This finding helps to conclude that equity shares’ demand drives the mutual funds demand but even higher demand of mutual funds fails to raise its own price unless underlying value of the mutual funds changes.

  10. Designing Effective Supports for Causal Reasoning

    Science.gov (United States)

    Jonassen, David H.; Ionas, Ioan Gelu

    2008-01-01

    Causal reasoning represents one of the most basic and important cognitive processes that underpin all higher-order activities, such as conceptual understanding and problem solving. Hume called causality the "cement of the universe" [Hume (1739/2000). Causal reasoning is required for making predictions, drawing implications and inferences, and…

  11. Representing Personal Determinants in Causal Structures.

    Science.gov (United States)

    Bandura, Albert

    1984-01-01

    Responds to Staddon's critique of the author's earlier article and addresses issues raised by Staddon's (1984) alternative models of causality. The author argues that it is not the formalizability of causal processes that is the issue but whether cognitive determinants of behavior are reducible to past stimulus inputs in causal structures.…

  12. Designing Effective Supports for Causal Reasoning

    Science.gov (United States)

    Jonassen, David H.; Ionas, Ioan Gelu

    2008-01-01

    Causal reasoning represents one of the most basic and important cognitive processes that underpin all higher-order activities, such as conceptual understanding and problem solving. Hume called causality the "cement of the universe" [Hume (1739/2000). Causal reasoning is required for making predictions, drawing implications and…

  13. Exploring Individual Differences in Preschoolers' Causal Stance

    Science.gov (United States)

    Alvarez, Aubry; Booth, Amy E.

    2016-01-01

    Preschoolers, as a group, are highly attuned to causality, and this attunement is known to facilitate memory, learning, and problem solving. However, recent work reveals substantial individual variability in the strength of children's "causal stance," as demonstrated by their curiosity about and preference for new causal information. In…

  14. Causal inference in economics and marketing.

    Science.gov (United States)

    Varian, Hal R

    2016-07-05

    This is an elementary introduction to causal inference in economics written for readers familiar with machine learning methods. The critical step in any causal analysis is estimating the counterfactual-a prediction of what would have happened in the absence of the treatment. The powerful techniques used in machine learning may be useful for developing better estimates of the counterfactual, potentially improving causal inference.

  15. Expectations and Interpretations during Causal Learning

    Science.gov (United States)

    Luhmann, Christian C.; Ahn, Woo-kyoung

    2011-01-01

    In existing models of causal induction, 4 types of covariation information (i.e., presence/absence of an event followed by presence/absence of another event) always exert identical influences on causal strength judgments (e.g., joint presence of events always suggests a generative causal relationship). In contrast, we suggest that, due to…

  16. Velocity requirements for causality violation

    CERN Document Server

    Modanese, Giovanni

    2013-01-01

    It is known that the hypothetical existence of superluminal signals would imply the logical possibility of active causal violation: an observer in relative motion with respect to a primary source could in principle emit secondary superluminal signals (triggered by the primary ones) which go back in time and deactivate the primary source before the initial emission. This is a direct consequence of the structure of the Lorentz transformations, sometimes called "Regge-Tolman paradox". It is straightforward to find a formula for the velocity of the moving observer required to produce the causality violation. When applied to some recent claims of slight superluminal propagation, this formula yields a required velocity very close to the speed of light; this raises some doubts about the real physical observability of such violations. We re-compute this velocity requirement introducing a realistic delay between the reception of the primary signal and the emission of the secondary. It turns out that for -any- delay it...

  17. Painless causality in defect calculations

    CERN Document Server

    Cheung, C; Cheung, Charlotte; Magueijo, Joao

    1997-01-01

    Topological defects must respect causality, a statement leading to restrictive constraints on the power spectrum of the total cosmological perturbations they induce. Causality constraints have for long been known to require the presence of an under-density in the surrounding matter compensating the defect network on large scales. This so-called compensation can never be neglected and significantly complicates calculations in defect scenarios, eg. computing cosmic microwave background fluctuations. A quick and dirty way to implement the compensation are the so-called compensation fudge factors. Here we derive the complete photon-baryon-CDM backreaction effects in defect scenarios. The fudge factor comes out as an algebraic identity and so we drop the negative qualifier ``fudge''. The compensation scale is computed and physically interpreted. Secondary backreaction effects exist, and neglecting them constitutes the well-defined approximation scheme within which one should consider compensation factor calculatio...

  18. Confounding Equivalence in Causal Inference

    CERN Document Server

    Pearl, Judea

    2012-01-01

    The paper provides a simple test for deciding, from a given causal diagram, whether two sets of variables have the same bias-reducing potential under adjustment. The test re- quires that one of the following two condi- tions holds: either (1) both sets are admis- sible (i.e., satisfy the back-door criterion) or (2) the Markov boundaries surrounding the manipulated variable(s) are identical in both sets. Applications to covariate selection and model testing are discussed.

  19. Phenomenology of Causal Dynamical Triangulations

    CERN Document Server

    Mielczarek, Jakub

    2015-01-01

    The four dimensional Causal Dynamical Triangulations (CDT) approach to quantum gravity is already more than ten years old theory with numerous unprecedented predictions such as non-trivial phase structure of gravitational field and dimensional running. Here, we discuss possible empirical consequences of CDT derived based on the two features of the approach mentioned above. A possibility of using both astrophysical and cosmological observations to test CDT is discussed. We show that scenarios which can be ruled out at the empirical level exist.

  20. Causality and primordial tensor modes

    Energy Technology Data Exchange (ETDEWEB)

    Baumann, Daniel; Zaldarriaga, Matias, E-mail: dbaumann@physics.harvard.edu, E-mail: mzaldarriaga@cfa.harvard.edu [Department of Physics, Harvard University, 17 Oxford Street, Cambridge, MA 02138, U.S.A. and Center for Astrophysics, Harvard University, 60 Garden Street, Cambridge, MA 02138 (United States)

    2009-06-01

    We introduce the real space correlation function of B-mode polarization of the cosmic microwave background (CMB) as a probe of superhorizon tensor perturbations created by inflation. By causality, any non-inflationary mechanism for gravitational wave production after reheating, like global phase transitions or cosmic strings, must have vanishing correlations for angular separations greater than the angle subtended by the particle horizon at recombination, i.e. θ ∼> 2°. Since ordinary B-modes are defined non-locally in terms of the Stokes parameters Q and U and therefore don't have to respect causality, special care is taken to define 'causal B-tilde -modes' for the analysis. We compute the real space B-tilde -mode correlation function for inflation and discuss its detectability on superhorizon scales where it provides an unambiguous test of inflationary gravitational waves. The correct identification of inflationary tensor modes is crucial since it relates directly to the energy scale of inflation. Wrongly associating tensor modes from causal seeds with inflation would imply an incorrect inference of the energy scale of inflation. We find that the superhorizon B-tilde -mode signal is above cosmic variance for the angular range 2° < θ < 4° and is therefore in principle detectable. In practice, the signal will be challenging to measure since it requires accurately resolving the recombination peak of the B-mode power spectrum. However, a future CMB satellite (CMBPol), with noise level Δ{sub P} ≅ 1μK-arcmin and sufficient resolution to efficiently correct for lensing-induced B-modes, should be able to detect the signal at more than 3σ if the tensor-to-scalar ratio isn't smaller than r ≅ 0.01.