WorldWideScience

Sample records for risk rating agencies

  1. Global financial crisis, banking crisis and first country risk in the viewpoint of domestic risk rating agencies

    Directory of Open Access Journals (Sweden)

    Dr.Sc. Ingrid Shuli

    2012-06-01

    Full Text Available In a period of dire financial crisis, with which all countries seem to cope, it seemed interesting to analyse the assessment of the risk for our country, viewed from the vantage point of our domestic rating agencies, but also compared to assessments made to our country by international rating agencies, such as Moody’s rating agency, Standard & Poor rating agency, Fitch ratings agency etc. The objective of this study is to recognize indicators and factors affecting the risk assessment and rating of a country, and evaluate whether there has been an impact of the financial crisis faced by other countries in the rating given to Albanian by domestic and foreign agencies. We stopped at the history of earlier financial crisis development to understand bewtter what is happening in this financial crisis. We shall develop upon a wide existing literature, and a range of credible resources such as the IMF, the World Bank, the International Institute of Finance, Economic Intelligence Unit, and local official data sources, eg. The Bank of Albania and INSTAT.

  2. Rating agencies : Role and influence of their sovereign credit risk assessment in the Eurozone

    NARCIS (Netherlands)

    Eijffinger, S.C.W.

    2012-01-01

    In this article, the role of credit rating agencies (CRAs) during the 2010–11 EU sovereign debt crisis is assessed. It is concluded that rating agencies lag behind markets, that their business model is flawed, and that the lack of competition renders the big three CRAs with too strong a market

  3. Rating agencies: role and influence of their sovereign credit risk assessment in the Euro area

    OpenAIRE

    Sibert, Anne

    2012-01-01

    Credit ratings have a huge impact on the access to and costs of funding, regardless whether the rated entity is a private enterprise or a sovereign borrower. Since the beginning of the financial crisis there has been a vivid and controversial debate about methods, timing and procedures used by these agencies. In this compilation of five notes provided by members of the Monetary Expert Panel the role of the rating agencies and their influence on the euro area is discussed in more detail.

  4. Regulatory agencies and regulatory risk

    OpenAIRE

    Knieps, Günter; Weiß, Hans-Jörg

    2008-01-01

    The aim of this paper is to show that regulatory risk is due to the discretionary behaviour of regulatory agencies, caused by a too extensive regulatory mandate provided by the legislator. The normative point of reference and a behavioural model of regulatory agencies based on the positive theory of regulation are presented. Regulatory risk with regard to the future behaviour of regulatory agencies is modelled as the consequence of the ex ante uncertainty about the relative influence of inter...

  5. Predicting Agency Rating Migrations with Spread Implied Ratings

    OpenAIRE

    Jianming Kou; Dr Simone Varotto

    2005-01-01

    Investors traditionally rely on credit ratings to price debt instruments. However, rating agencies are known to be prudent in their approach to rating revisions, which results in delayed ratings adjustments to mutating credit conditions. For a large set of eurobonds we derive credit spread implied ratings and compare them with the ratings issued by rating agencies. Our results indicate that spread implied ratings often anticipate future movement of agency ratings and hence could help track cr...

  6. 76 FR 16570 - Interest Rate Risk

    Science.gov (United States)

    2011-03-24

    ... NATIONAL CREDIT UNION ADMINISTRATION 12 CFR Part 741 RIN 3133-AD66 Interest Rate Risk AGENCY... regulations to require Federally insured credit unions to have a written policy addressing interest rate risk... Risk Management for Credit Unions with Large Positions in Fixed Rate Mortgages; 06-CU-16 Inter-Agency...

  7. The Impact of the Rating Agencies' Through-the-cycle Methodology on Rating Dynamics

    NARCIS (Netherlands)

    Altman, E.I.; Rijken, H.A.

    2005-01-01

    Surveys on the use of agency credit ratings reveal that some investors believe that credit-rating agencies are relatively slow in adjusting their ratings. A well-accepted explanation for this perception on rating timeliness is the through-the-cycle methodology that agencies use. Through-the-cycle

  8. Management of interest rate risk

    Directory of Open Access Journals (Sweden)

    Šabović Šerif

    2014-01-01

    Full Text Available Interest rate risk is one of the biggest and most dangerous risks that a bank is exposed to. When a change of interest rates occurs, the incomes of a bank based on credits and securities endure significant changes. Banks resources also endure some changes. The change of interest rates changes the value of the assets and liabilities of the bank and it's net and investment worth . The change of interest rates also affects bank's balance sheet, income sheet statement and bank's share capital.

  9. The development trends of credit rating agencies activity in Russia

    Directory of Open Access Journals (Sweden)

    L. E. Galyaeva

    2016-01-01

    Full Text Available The process and the prospects of development of the rating industry in the country are examined in the article. The author analyzes the influence of sovereign Russian credit rating decrease by the world’s leading rating agencies at the beginning of 2015 on financial sector of the country. Politically motivated international credit rating agencies ratings hinder the development of the Russian financial system. That’s why particular attention is paid to the rejection of dependence on the international credit rating agencies ratings and the appearance of a new strong and powerful national credit agency on the Russian market. The problems concerned with speculative estimates of the Russian investment potential. The author points some possible ways to recover from the crisis by involving inner agencies instead of international ones. Special attention is devoted to the existent legislative modifications. Never the less, speaking about the prospects and the future of the leading agencies, it is significant that their work will be relevant in long term due to the increasing uncertainty of the external environment. Moreover the necessity of investing funds in different objects intensifies which leads to the investors and depositors needs of investing. The presented information may be interesting for further profound exploration of the issues, identify the range of problems to be solved by international ratings of the issuers and their securities. In addition, the information proposed in the article can be also served as a basis for further comparison of the activity of international and national agencies in terms of the services offered.

  10. Credit ratings and CEO risk-taking incentives

    NARCIS (Netherlands)

    Kuang, Y.; Qin, B.

    2013-01-01

    This study examines the sophistication of rating agencies in incorporating managerial risk-taking incentives into their credit risk evaluation. We measure risk-taking incentives using two proxies: the sensitivity of managerial wealth to stock return volatility (vega) and the sensitivity of

  11. Herding Behavior and Rating Convergence among Credit Rating Agencies : Evidence from the Subprime Crisis

    NARCIS (Netherlands)

    Lugo, Stefano; Croce, Annalisa; Faff, Robert

    2015-01-01

    This article examines how credit rating agencies (CRAs) react to rating decisions on mortgage-backed securities by rival agencies in the aftermath of the subprime crisis. While Fitch is on average the first mover, Moody’s and S&P perform more timely downgrades given a downgrade or a more severe

  12. Risk, ambiguity and sovereign rating

    OpenAIRE

    Di Caro, Paolo

    2014-01-01

    Decisions of investing in sovereign assets involve both risk and ambiguity. Ambiguity arises from unknown elements characterizing the value of a generic sovereign. In presence of ambiguity, ambiguity-averse investors are prone to pay for obtaining summary information such as ratings which reduces ambiguity. Ambiguity-neutral and ambiguity-averse investors, then, make decisions on the basis of different informative sources. By presenting a simple model of sovereign rating under ambiguity, thre...

  13. ROLE, INTERESTS AND CRITICS OF CREDIT RATING AGENCIES

    Directory of Open Access Journals (Sweden)

    Suzana Baresa

    2012-06-01

    Full Text Available Key role of credit rating agencies is reducing the asymmetry information about credit quality (of governments, business entities or securities between issuers and investors, and ensuring a common standard of measuring the creditworthiness. Credit rating agencies are engaged in the sale of opinions about creditworthiness in the form of an alphabetical letter or symbol, which represents a unique ranking. Their opinion is not a guarantee, but it largely dictates the costs and the profits in the financial markets. This work shows the influence of credit rating agencies to investors and publishers, and their role as market regulators. Conflict of interest is a fundamental problem, which is caused by their way of doing business, it arises from their two main objectives: profit and market regulation, which will be explored in the work. Looking back in history credit rating agencies often selected goal of making a profit at the cost of market regulation, therefore they have caused the collapse of the market, and founded themselves criticized by the public.

  14. Credit Rating Agencies, Financial Regulations and the Capital Markets

    NARCIS (Netherlands)

    K. Shahzad (Khurram)

    2013-01-01

    textabstractThis thesis studies the role of credit rating agencies (CRAs) in capital markets, and the effects of two important regulatory decisions that are taken to improve the quality of information available to the capital markets. In particular, this thesis examines a) the importance of credit

  15. 75 FR 13145 - SBA Lender Risk Rating System

    Science.gov (United States)

    2010-03-18

    ... SMALL BUSINESS ADMINISTRATION [Docket No. SBA-2010-0004] SBA Lender Risk Rating System AGENCY: Small Business Administration. ACTION: Notice; extension of comment period and correction. SUMMARY: On... of Credit Risk Management, U.S. Small Business Administration, 409 Third Street, SW., 8th Floor...

  16. Credit rating agencies – too big to fail?

    OpenAIRE

    Coors, Corinna

    2012-01-01

    This article examines the reforms introduced in the US and the EU to limit the power of credit rating agencies and address their organisational and structural problems that were exposed by the global financial crisis. It discusses the relevant provisions of the US Dodd-Frank Wall Street Reform and Consumer Protection Act 2010 and notes their current stage of implementation. Summarises the measures introduced by Regulation 513/2011.

  17. Interconnectivity among Assessments from Rating Agencies: Using Cluster and Correlation Analysis

    OpenAIRE

    Krejčíř, Jaroslav; Doubravsky, Karel; Dostál, Petr

    2014-01-01

    The aim of this paper is to determine whether there is a dependency among leading rating agencies assessments. Rating agencies are important part of global economy. Great attention has been paid to activities of rating agencies since 2007, when there was a financial crisis. One of the main causes of this crisis was identified credit rating agencies. This paper is focused on an existence of mutual interconnectivity among assessments from three leading rating agencies. The method used for this ...

  18. Credit rating agencies: who are they and do we need them? | Naik ...

    African Journals Online (AJOL)

    , hardly anything is known about credit rating agencies. In this matter-of-fact article, the authors lay bare the ABC's of rating agencies, how they operate and what informs the (sometimes death) sentences they pass on countries.

  19. Social Support and Personal Agency in At-Risk Mothers

    Directory of Open Access Journals (Sweden)

    María José Rodrigo

    2011-04-01

    Full Text Available This study investigated: a mothers´ use and satisfaction with informal and formal supports in at-risk psychosocial contexts, and b the relationships between satisfaction with help and the mothers´ perception of their role (personal agency. Self-report data about the use and satisfaction with sources of help, and levels of internal control, self-efficacy, couple agreement, role difficulty and motivation for change were obtained from 519 mothers referred by Social Services and 519 non-referred mothers. Results indicated that at-risk mothers relied less upon close informal support and more on formal support than non atrisk mothers. They were also more satisfied with the formal sources of support and had lower levels of personal agency. There were beneficial effects of satisfaction with informal help and school support on several aspects of personal agency for both groups. However, satisfaction with school and social services support had a detrimental effect on couple agreement in the at-risk group. Implications of the results for providing social support to at-risk families are discussed.

  20. The Determinants of Country Risk Ratings

    OpenAIRE

    Jean-Claude Cosset; Jean Roy

    1991-01-01

    The purpose of this paper is to replicate Euromoney's and Institutional Investor's country risk ratings on the basis of economic and political variables. The evidence reveals that country risk ratings respond to some of the variables suggested by the theory. In particular, both the level of per capita income and propensity to invest affect positively the rating of a country. In addition, high-ranking countries are less indebted than low-ranking countries. It also appears that the ability of t...

  1. Interconnectivity among Assessments from Rating Agencies: Using Cluster and Correlation Analysis

    Directory of Open Access Journals (Sweden)

    Jaroslav Krejčíř

    2014-09-01

    Full Text Available The aim of this paper is to determine whether there is a dependency among leading rating agencies assessments. Rating agencies are important part of global economy. Great attention has been paid to activities of rating agencies since 2007, when there was a financial crisis. One of the main causes of this crisis was identified credit rating agencies. This paper is focused on an existence of mutual interconnectivity among assessments from three leading rating agencies. The method used for this determines is based on cluster analysis and subsequently correlation analysis and the test of independence. Credit rating assessments of Greece and Spain were chosen to the determination of this mutual interconnectivity due to the fact that these countries are most talked euro­area countries. The significant dependence of the assessment from different rating agencies has been demonstrated.

  2. Currency Risk Management under Floating Rates

    Directory of Open Access Journals (Sweden)

    Nicu Duret

    2016-09-01

    Full Text Available As for the research into this subject, we find, therefore, that one of the most important indicators that quantify the international competitiveness is the exchange rate, together with other fundamental macroeconomic variables such as the size of the potential GDP, the equilibrium real exchange rate, gives a certain insight into the functioning of the fundamental macroeconomic mechanisms and their regulation. Commercial and financial operations imply relationships between partners from different currency countries or areas that involve conversion operations, of replacement of a currency to another. Exchange rate fluctuations of one currency create currency risk, to the extent that it is used to carry out international transactions. These operations are subjected to currency risk as exchange rates change frequently from one period to another and, on the other hand, speculations in the forex market influence the exchange rate by the interventions of those who perform them.

  3. 46 CFR 308.551 - War risk insurance clearing agency agreement for cargo, Form MA-321.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 8 2010-10-01 2010-10-01 false War risk insurance clearing agency agreement for cargo... EMERGENCY OPERATIONS WAR RISK INSURANCE War Risk Cargo Insurance Iv-General § 308.551 War risk insurance... American War Risk Agency or MARAD. ...

  4. 75 FR 16821 - Housing Finance Agency Risk-Sharing Program

    Science.gov (United States)

    2010-04-02

    ...The proposed information collection requirement described below has been submitted to the Office of Management and Budget (OMB) for review, as required by the Paperwork Reduction Act. The Department is soliciting public comments on the subject proposal. Section 542(c) of the Risk Sharing Program authorizes qualified Housing Finance Agencies (HFAs) to underwrite and process loans. HUD provides full mortgage insurance on affordable multifamily housing project processed by HFAs under this program. Qualified HFAs are vested with the maximum amount of processing responsibilities. By entering into Risk-Sharing Agreement with HUD, HFAs contract to reimburse HUD for a portion of the loss from any defaults that occur while HUD insurance is in force.

  5. Remarks on Interest Rate Risk Management

    Directory of Open Access Journals (Sweden)

    Elena-Violeta DRAGOI

    2016-12-01

    Full Text Available Bank interest and interest rate risk management is a contemporary subject and for socio-economic environment of Romania cause serious consequences in the level of economic development. The purpose of this research is to highlight the main indicator that measures the total cost of a loan, namely the annual percentage rate (APR, because if we refer to an interest rate lower, at first glance that loan seems more advantageous, but at a closer look, taking into account the commissions charged by the bank, we see that the loan is more expensive compared to another, whose interest rate is higher.

  6. On the spillover of exchange rate risk into default risk

    Directory of Open Access Journals (Sweden)

    Božović Miloš

    2009-01-01

    Full Text Available In order to reduce the exchange-rate risk, banks in emerging markets are typically denominating their loans in foreign currencies. However, in the event of a substantial depreciation of the local currency, the payment ability of a foreign-currency borrower may be reduced significantly, exposing the lender to additional default risk. This paper analyses how the exchange-rate risk of foreign currency loans spills over into default risk. We show that in an economy where foreign currency loans are a dominant source of financing economic activity, depreciation of the local currency establishes a negative feedback mechanism that leads to higher default probabilities, reduced credit supply, and reduced growth. This finding has some important implications that may be of special interest for regulators and market participants in emerging economies.

  7. 13 CFR 120.1015 - Risk Rating System.

    Science.gov (United States)

    2010-01-01

    ... 13 Business Credit and Assistance 1 2010-01-01 2010-01-01 false Risk Rating System. 120.1015 Section 120.1015 Business Credit and Assistance SMALL BUSINESS ADMINISTRATION BUSINESS LOANS Risk-Based Lender Oversight Supervision § 120.1015 Risk Rating System. (a) Risk Rating. SBA may assign a Risk Rating...

  8. VaR: Exchange Rate Risk and Jump Risk

    Directory of Open Access Journals (Sweden)

    Fen-Ying Chen

    2010-01-01

    Full Text Available Incorporating the Poisson jumps and exchange rate risk, this paper provides an analytical VaR to manage market risk of international portfolios over the subprime mortgage crisis. There are some properties in the model. First, different from past studies in portfolios valued only in one currency, this model considers portfolios not only with jumps but also with exchange rate risk, that is vital for investors in highly integrated global financial markets. Second, in general, the analytical VaR solution is more accurate than historical simulations in terms of backtesting and Christoffersen's independence test (1998 for small portfolios and large portfolios. In other words, the proposed model is reliable not only for a portfolio on specific stocks but also for a large portfolio. Third, the model can be regarded as the extension of that of Kupiec (1999 and Chen and Liao (2009.

  9. 76 FR 33028 - Agency Information Collection (Requirements for Interest Rate Reduction Refinancing Loans...

    Science.gov (United States)

    2011-06-07

    ... (Requirements for Interest Rate Reduction Refinancing Loans) Activity Under OMB Review AGENCY: Veterans Benefits...: Requirements for Interest Rate Reduction Refinancing Loans. OMB Control Number: 2900-0601. Type of Review..., insured, or direct loan with a new loan at a lower interest rate provided that the veteran still owns the...

  10. 41 CFR 102-80.50 - Are Federal agencies responsible for identifying/estimating risks and for appropriate risk...

    Science.gov (United States)

    2010-07-01

    ... Environmental Management Risks and Risk Reduction Strategies § 102-80.50 Are Federal agencies responsible for... identify and estimate safety and environmental management risks and appropriate risk reduction strategies... responsible for identifying/estimating risks and for appropriate risk reduction strategies? 102-80.50 Section...

  11. 7 CFR 2.44 - Administrator, Risk Management Agency and Manager, Federal Crop Insurance Corporation.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 1 2010-01-01 2010-01-01 false Administrator, Risk Management Agency and Manager... Secretary for Farm and Foreign Agricultural Services to the Administrator, Risk Management Agency, and... for the transaction of the business of the Federal Crop Insurance Corporation and the Risk Management...

  12. Do Credit Rating Agencies Add to the Dynamics of Emerging Market Crises?

    NARCIS (Netherlands)

    Kraussl, R.G.W.

    2005-01-01

    This study investigates the role of credit rating agencies in international financial markets. With an index of speculative market pressure it is analyzed whether sovereign ratings changes have an impact on the financial stability in emerging market economies. The event study analysis indicates that

  13. An abuse of risk assessment: how regulatory agencies improperly adopted LNT for cancer risk assessment.

    Science.gov (United States)

    Calabrese, Edward J

    2015-04-01

    The Genetics Panel of the National Academy of Sciences' Committee on Biological Effects of Atomic Radiation (BEAR) recommended the adoption of the linear dose-response model in 1956, abandoning the threshold dose-response for genetic risk assessments. This recommendation was quickly generalized to include somatic cells for cancer risk assessment and later was instrumental in the adoption of linearity for carcinogen risk assessment by the Environmental Protection Agency. The Genetics Panel failed to provide any scientific assessment to support this recommendation and refused to do so when later challenged by other leading scientists. Thus, the linearity model used in cancer risk assessment was based on ideology rather than science and originated with the recommendation of the NAS BEAR Committee Genetics Panel. Historical documentation in support of these conclusions is provided in the transcripts of the Panel meetings and in previously unexamined correspondence among Panel members.

  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DODGE COUNTY, WISCONSIN, USA - MIP Dodge Portion Upper Rock River Watershed RiskMap DFIRM Update

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk;...

  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, COLUMBIA COUNTY, WISCONSIN, USA - MIP Columbia Portion Baraboo River Watershed RiskMap DFIRM Update

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk;...

  16. Federal Workforce: Attrition Rates at Ex-Im Bank and Similar Agencies

    National Research Council Canada - National Science Library

    Hess, James

    1997-01-01

    The Ex-Im Bank's mission is to assist U.S. exporters by offering a wide range of financing at terms competitive with those of other governments' export financing agencies and absorbing risks that the private sector is reluctant to cover...

  17. 78 FR 52962 - 60-Day Notice of Proposed Information Collection: Housing Finance Agency Risk-Sharing Program

    Science.gov (United States)

    2013-08-27

    ... Information Collection: Housing Finance Agency Risk-Sharing Program AGENCY: Office of the Assistant Secretary... Finance Agency Risk- Sharing Program. OMB Approval Number: 2502-0500. Type of Request (i.e. new, revision... Secretary to implement risk sharing with State and local housing finance agencies (HFAs). Under this program...

  18. 76 FR 79379 - Risk-Based Capital Guidelines: Market Risk; Alternatives to Credit Ratings for Debt and...

    Science.gov (United States)

    2011-12-21

    ..., China, France, Germany, Hong Kong SAR, India, Indonesia, Italy, Japan, Korea, Luxembourg, Mexico, the..., the legislative history of section 939A focuses on the conflicts of interest of credit rating agencies... illustrates how CDS spreads and CRCs could be used together to assign specific risk-weighting factors. In...

  19. A rating for the risk; Ein Rating fuers Risiko

    Energy Technology Data Exchange (ETDEWEB)

    Faltermeier, Daniel [Meteocontrol GmbH, Augsburg (Germany). Technische Due Diligence PV

    2013-07-01

    The assessment of the quality and risks of the photovoltaics project plays an important role in the investment decision. Especially for very large projects, an extensive risk assessment of yield losses and technical tests are increasingly demanded by independent experts. A new method enables the evaluation of solar energy systems.

  20. Politically Induced Regulatory Risk and Independent Regulatory Agencies

    OpenAIRE

    Strausz, Roland

    2015-01-01

    Uncertainty in election outcomes generates politically induced regulatory risk. Political parties' risk attitudes towards such risk depend on a fluctuation effect that hurts both parties and an output--expansion effect that benefits at least one party. Notwithstanding the parties' risk attitudes, political parties have incentives to negotiate away all regulatory risk by pre-electoral bargaining. Efficient pre-electoral bargaining outcomes fully eliminate politically induced regulatory risk. P...

  1. Hedging endowment assurance products under interest rate and mortality risk

    NARCIS (Netherlands)

    Chen, A.; Mahayni, A.

    2007-01-01

    This paper analyzes how model misspecification associated with both interest rate and mortality risk influences hedging decisions of insurance companies. For this purpose, diverse risk management strategies which are riskminimizing when model risk is ignored come into consideration. The

  2. 12 CFR 615.5135 - Management of interest rate risk.

    Science.gov (United States)

    2010-01-01

    ... 12 Banks and Banking 6 2010-01-01 2010-01-01 false Management of interest rate risk. 615.5135... of interest rate risk. The board of directors of each Farm Credit Bank, bank for cooperatives, and agricultural credit bank shall develop and implement an interest rate risk management program as set forth in...

  3. Constrained relationship agency as the risk factor for intimate ...

    African Journals Online (AJOL)

    We used structural equation modelling to identify and measure constrained relationship agency (CRA) as a latent variable, and then tested the hypothesis that CRA plays a significant role in the pathway between IPV and transactional sex. After controlling for CRA, receiving more material goods from a sexual partner was ...

  4. Teachers Unions at Risk of Losing "Agency Fees"

    Science.gov (United States)

    Antonucci, Mike

    2016-01-01

    For 50 years, American education policy has often danced to the tune of labor realities. "Friedrichs v. California Teachers Association" is a case that awaits hearing by the U.S. Supreme Court that could dramatically change this picture. The case, if decided for the plaintiffs, could end the practice of "agency" fees--money…

  5. The Constitutive Element of Probabilistic Agency in Risk

    DEFF Research Database (Denmark)

    Merkelsen, Henrik

    2011-01-01

    Defining central concepts with accuracy is crucial to any scientific discipline. A recent debate over risk definitions in this journal illustrates the far reaching consequences of divergent definitions. Aven and Renn define risk as a social construct while Rosa defines risk as an ontological fact...

  6. 78 FR 65696 - 30-Day Notice of Proposed Information Collection: Housing Finance Agency Risk-Sharing Program

    Science.gov (United States)

    2013-11-01

    ... Information Collection: Housing Finance Agency Risk-Sharing Program AGENCY: Office of the Chief Information... Information Collection: Housing Finance Agency Risk- Sharing Program. OMB Approval Number: 2502-0500. Type of... housing finance agencies (HFAs). Under this program, HUD provides full mortgage insurance on multifamily...

  7. 78 FR 64145 - 30-Day Notice of Proposed Information Collection: Housing Finance Agency Risk-Sharing Program

    Science.gov (United States)

    2013-10-25

    ... Information Collection: Housing Finance Agency Risk-Sharing Program AGENCY: Office of the Chief Information... Title of Information Collection: Housing Finance Agency Risk- Sharing Program. OMB Approval Number: 2502... sharing with State and local housing finance agencies (HFAs). Under this program, HUD provides full...

  8. Interpretation and evaluation of the US Environmental Protection Agency ecological risk assessment guidelines

    CSIR Research Space (South Africa)

    Murray, K

    1999-10-01

    Full Text Available In order to facilitate a common understanding, on-going debate and increasing application of ecological risk assessment (ERA) in South Africa, the ERA process of the US Environmental Protection Agency (EPA) has been summarised and evaluated...

  9. Exchange rate policy under sovereign default risk

    OpenAIRE

    Schabert, Andreas

    2011-01-01

    We examine monetary policy options for a small open economy where sovereign default might occur due to intertemporal insolvency. Under interest rate policy and floating exchange rates the equilibrium is indetermined. Under a fixed exchange rate the equilibrium is uniquely determined and independent of sovereign default.

  10. Exchange rate risks and their impact upon the energy market

    Directory of Open Access Journals (Sweden)

    Abed Al-Zabidi

    2007-04-01

    Full Text Available The expansion of international business in Slovakia brought not only the opening of markets and expansion of enterprise possibilities but also an increase in the competition and new risks. One of such risks is also the exchange rate risk. The business that realizes a financial transaction exceeding borders of the state or derives his buying or selling prices in Slovak crowns from the foreign currency, is subjected to the exchange rate risks. The exchange rate risks are caused by volatility of exchange courses of Slovak crowns related to foreign currencies. The progress of exchange rates can considerably influence a real result of a transaction negatively; therefore it is important for enterprises to identify possible risks resulting from changes in exchange rates, so they could react accordingly.The proposed article is aimed at the explanation of basic techniques of minimizing exchange rate risks with the use of financial tools available on the financial market.

  11. The Juvenile Addiction Risk Rating: Development and Initial Psychometrics

    Science.gov (United States)

    Powell, Michael; Newgent, Rebecca A.

    2016-01-01

    This article describes the development and psychometrics of the Juvenile Addiction Risk Rating. The Juvenile Addiction Risk Rating is a brief screening of addiction potential based on 10 risk factors predictive of youth alcohol and drug-related problems that assists examiners in more accurate treatment planning when self-report information is…

  12. State ownership, agency conflict and effective tax rates: Evidence from China

    Directory of Open Access Journals (Sweden)

    Sun Jianfu

    2016-02-01

    Full Text Available Agency conflict between minority and controlling shareholders in state owned firms has to be considered in order to examine the variability on effective tax rates. In China, state ownership helps the government to achieve its social objectives by optimizing corporate income tax. We provide a significant result to prove that state owned firms paid higher corporate income taxes than private firms. Our results also indicate that corporate effective tax rates are positively associated with firm sized and inventory intensity. However, we have no strong evidence to support the association with leverage, return on assets and capital intensity.

  13. Interest rate risk of life insurers: Evidence from accounting data

    OpenAIRE

    Möhlmann, Axel

    2017-01-01

    Life insurers are exposed to interest rate risk, and their liability side is typically more sensitive to interest rate changes than their asset side. This paper develops an accounting-based measure of interest rate sensitivity. My approach uses the coexistence of historical cost and market value accounting, which permits the observation of valuations for different discount rates. Using microdata, I show that German life insurers have a significant exposure to interest rate risk. However, ther...

  14. Simplifying cardiovascular risk estimation using resting heart rate.

    LENUS (Irish Health Repository)

    Cooney, Marie Therese

    2010-09-01

    Elevated resting heart rate (RHR) is a known, independent cardiovascular (CV) risk factor, but is not included in risk estimation systems, including Systematic COronary Risk Evaluation (SCORE). We aimed to derive risk estimation systems including RHR as an extra variable and assess the value of this addition.

  15. Exchange rate risk in Central European countries

    Czech Academy of Sciences Publication Activity Database

    Kočenda, Evžen; Poghosyan, T.

    2010-01-01

    Roč. 60, č. 1 (2010), s. 22-39 ISSN 0015-1920 R&D Projects: GA ČR(CZ) GA402/08/1376; GA MŠk LC542 Institutional research plan: CEZ:MSM0021620846 Keywords : foreign exchange risk * time-varying risk premium * stochastic discount factor Subject RIV: AH - Economics Impact factor: 0.278, year: 2010 http://journal.fsv.cuni.cz/storage/1178_str_22_39_-_ko%C4%8Denda.pdf

  16. Profiling the environmental risk management of Chinese local environmental agencies

    NARCIS (Netherlands)

    He, G.; Zhang, L.; Mol, A.P.J.; Lu, Y.

    2013-01-01

    The increasing frequency and impact of environmental accidents have pushed the issue of environmental risk management (ERM) to the top of the Chinese governments’ agendas and popularized the term ‘emergency response.’ Although the boundary between environmental accidents and other types of accidents

  17. Agency Theory, Futures Markets and Risk Shifting in Commodity Marketing Channels

    NARCIS (Netherlands)

    Kuwornu, J.K.M.; Kuiper, W.E.; Pennings, J.M.E.; Meulenberg, M.T.G.

    2004-01-01

    This paper applies agency theory to access risk shifting between the principal (marketing firms) and the agent (farmers) in a food marketing channel. It compares the case in which there is a futures market available for the risk-averse agents with the case in which there is no futures trading. The

  18. Interest Rate Risk Management using Duration Gap Methodology

    Directory of Open Access Journals (Sweden)

    Dan Armeanu

    2008-01-01

    Full Text Available The world for financial institutions has changed during the last 20 years, and become riskier and more competitive-driven. After the deregulation of the financial market, banks had to take on extensive risk in order to earn sufficient returns. Interest rate volatility has increased dramatically over the past twenty-five years and for that an efficient management of this interest rate risk is strong required. In the last years banks developed a variety of methods for measuring and managing interest rate risk. From these the most frequently used in real banking life and recommended by Basel Committee are based on: Reprising Model or Funding Gap Model, Maturity Gap Model, Duration Gap Model, Static and Dynamic Simulation. The purpose of this article is to give a good understanding of duration gap model used for managing interest rate risk. The article starts with a overview of interest rate risk and explain how this type of risk should be measured and managed within an asset-liability management. Then the articles takes a short look at methods for measuring interest rate risk and after that explains and demonstrates how can be used Duration Gap Model for managing interest rate risk in banks.The world for financial institutions has changed during the last 20 years, and become riskier and more competitive-driven. After the deregulation of the financial market, banks had to take on extensive risk in order to earn sufficient returns. Interest rate volatility has increased dramatically over the past twenty-five years and for that an efficient management of this interest rate risk is strong required. In the last years banks developed a variety of methods for measuring and managing interest rate risk. From these the most frequently used in real banking life and recommended by Basel Committee are based on: Reprising Model or Funding Gap Model, Maturity Gap Model, Duration Gap Model, Static and Dynamic Simulation. The purpose of this article is to give a

  19. Balancing risk, interpersonal intimacy and agency: perspectives from marginalised women in Zambia.

    Science.gov (United States)

    Davis, Lwendo Moonzwe; Kostick, Kristin Marie

    2018-05-15

    Women are most exposed to sexual health risks within their marital relationships, primarily due to the sexually risky behaviours of their spouses. Studies show that expanding agency is critical for women to mitigate both physical and sexual health risks and is linked to increased psycho-social well-being and economic independence. Drawing on qualitative and quantitative primary data collected from a peri-urban community in Zambia, this paper explores how women exert agency in a community where few educational and economic opportunities and substantial food insecurity exacerbate women's risk for HIV within their marital relationships. It also examines how expressions of agency within marital unions can reduce HIV risk exposure and lead to socio-economic benefits. However, expressions of agency can also create physical, psycho-social and sexual health risks, particularly when spouses do not support independent decision-making and actions that women consider necessary to support the household and maintain intimacy. Findings highlight the importance of community involvement and addressing harmful socio-cultural norms to foster the realisation of women's agency.

  20. How information resources are used by state agencies in risk assessment applications - Illinois

    Energy Technology Data Exchange (ETDEWEB)

    Olson, C.S.

    1990-12-31

    The Environmental Protection Agency of the State of Illinois (Illinois EPA) has programs in water, air, and land pollution and water supplies paralleling those of the US Environmental Protection Agency (EPA). The organization is part of a tripartite arrangement in which the Pollution Control Board is the judicial arm, the Department of Energy and Natural Resources is the research arm, and the Illinois EPA is the enforcement arm. Other state agencies are also concerned with various aspects of the environment and may do risk assessments for chemicals. Although there are various risk assessment activities, both formal and informal, in our agency and in others, this paper will discuss only recent initiatives in water quality criteria.

  1. Hospital cost-containment strategies that earn the respect of rating agencies.

    Science.gov (United States)

    Dopoulos, Jason

    2016-01-01

    To confirm that hospitals have the necessary structures and strategies in place to reduce costs and secure future market share, credit rating agencies analyze a variety of quantitative and qualitative criteria, including: Salaries and benefits, bad debt, age of plant and depreciation, and other line items that may point to inefficiencies in a hospital's expense structure. Cost-benefit analyses, strategic plans, and leadership qualities that show the long-term value of expense cuts, capital investments, and mergers and acquisitions. Cost-effective and clinically appropriate shifts in a hospital's outpatient-to-inpatient ratio. Liquidity and market share.

  2. How information resources are used by federal agencies in risk assessment application: Rapporteur summary

    Energy Technology Data Exchange (ETDEWEB)

    Fenner-Crisp, P. [Environmental Protection Agency, Washington, DC (United States)

    1990-12-31

    The application of information available for risk assessment from the federal perspective is described. Different federal agencies conduct varying degrees of hazard evaluation, and some also generate empirical data. The role of the Agency for Toxic Substances and Disease Registry in hazard assessments of potential public health impacts of Superfund sites includes identification of the 275 most significant substances. ATSDR is responsible for preparing toxicological profiles. ATSDR also identifies data gaps and needs critical to adequately assessing human health impacts.

  3. Insurer Provide Rating Software and Competitive Advantage: An Evaluation Based on BOP Insurance Applications at Wisconsin Agencies

    OpenAIRE

    Thomas A. Aiuppa; William E. Wehrs

    1993-01-01

    This research examines whether a competitive advantage exists for insurers which provide independent agencies with rating software to generate price quotes. Data relative to the Business Owners line of insurance were collected from several Wisconsin agencies which represent several BOP insurers, some of which provide software for rating BOP applications. The results indicate that providing rating software did not increase insurers’ business volumes, but may decrease their underwriting costs. ...

  4. Self-rated health and cancer risk

    DEFF Research Database (Denmark)

    Roelsgaard, Ida Kristiane; Olesen, Anne Marie; Simonsen, Mette Kildevæld

    2016-01-01

    BACKGROUND: Self-rated health (SRH) has been shown to be a strong predictor of mortality from a number of major chronic diseases, however, the association with cancer remains unclear. The aim of this study was to investigate a possible association between change in SRH and cancer incidence...... proportional hazards model with adjustment for age, smoking, alcohol, marital status, physical activity, body mass index and estrogen replacement therapy. RESULTS: No significant association was found between SRH and overall cancer incidence in the age-adjusted Cox proportional hazards model (1.04; 95% CI 0...

  5. Real interest rates, leverage, and bank risk-taking

    NARCIS (Netherlands)

    Dell’Ariccia, G.; Laeven, L.; Marquez, R.

    2014-01-01

    Do low interest rate environments lead to greater bank risk-taking? We show that, when banks can adjust their capital structures, reductions in real interest rates lead to greater leverage and higher risk for any downward sloping loan demand function. However, if the capital structure is fixed, the

  6. Interest Rate Risk Management using Duration Gap Methodology

    Directory of Open Access Journals (Sweden)

    Dan Armeanu

    2008-01-01

    should be measured and managed within an asset-liability management. Then the articles takes a short look at methods for measuring interest rate risk and after that explains and demonstrates how can be used Duration Gap Model for managing interest rate risk in banks.

  7. Strategy for communicating benefit-risk decisions: a comparison of regulatory agencies' publicly available documents.

    Science.gov (United States)

    Leong Wai Yeen, James; Salek, Sam; Walker, Stuart

    2014-01-01

    The assessment report formats of four major regulatory reference agencies, US Food and Drug Administration, European Medicines Agency, Health Canada, and Australia's Therapeutic Goods Administration were compared to a benefit-risk (BR) documentation template developed by the Centre for Innovation in Regulatory Science and a four-member Consortium on Benefit-Risk Assessment. A case study was also conducted using a US FDA Medical Review, the European Public Assessment Report and Australia's Public Assessment Report for the same product. Compared with the BR Template, existing regulatory report formats are inadequate regarding the listing of benefits and risks, the assigning of relative importance and values, visualization and the utilization of a detailed, systematic, standardized structure. The BR Template is based on the principles of BR assessment common to major regulatory agencies. Given that there are minimal differences among the existing regulatory report formats, it is timely to consider the feasibility of a universal template.

  8. Interest Rate Risk Management and the Use of Derivative Securities

    Directory of Open Access Journals (Sweden)

    Ioana-Diana PĂUN

    2013-12-01

    Full Text Available This study aims to demonstrate the utility of derivative financial instruments for the management of interest rate risk that is faced by banks and financial institutions, and to provide an efficient flow of monitoring and control thereof. Banking institutions can now use a combination of balance sheet and off balance sheet measures, i.e. gap method, of interest rate risk management, in order to control exposure of short-term rates and derivatives to control the residual interest rate exposures. The result of the study shows that banks can achieve better diversification and risk management using derivatives.

  9. TECHNICAL RISK RATING OF DOE ENVIRONMENTAL PROJECTS - 9153

    International Nuclear Information System (INIS)

    Cercy, M.; Fayfich, Ronald; Schneider, Steven P.

    2008-01-01

    The U.S. Department of Energy's Office of Environmental Management (DOE-EM) was established to achieve the safe and compliant disposition of legacy wastes and facilities from defense nuclear applications. The scope of work is diverse, with projects ranging from single acquisitions to collections of projects and operations that span several decades and costs from hundreds of millions to billions US$. The need to be able to manage and understand the technical risks from the project to senior management level has been recognized as an enabler to successfully completing the mission. In 2008, DOE-EM developed the Technical Risk Rating as a new method to assist in managing technical risk based on specific criteria. The Technical Risk Rating, and the criteria used to determine the rating, provides a mechanism to foster open, meaningful communication between the Federal Project Directors and DOE-EM management concerning project technical risks. Four indicators (technical maturity, risk urgency, handling difficulty and resolution path) are used to focus attention on the issues and key aspects related to the risks. Pressing risk issues are brought to the forefront, keeping DOE-EM management informed and engaged such that they fully understand risk impact. Use of the Technical Risk Rating and criteria during reviews provides the Federal Project Directors the opportunity to openly discuss the most significant risks and assists in the management of technical risks across the portfolio of DOE-EM projects. Technical Risk Ratings can be applied to all projects in government and private industry. This paper will present the methodology and criteria for Technical Risk Ratings, and provide specific examples from DOE-EM projects

  10. 41 CFR 102-80.55 - Are Federal agencies responsible for managing the execution of risk reduction projects?

    Science.gov (United States)

    2010-07-01

    ... Management Risks and Risk Reduction Strategies § 102-80.55 Are Federal agencies responsible for managing the... 41 Public Contracts and Property Management 3 2010-07-01 2010-07-01 false Are Federal agencies responsible for managing the execution of risk reduction projects? 102-80.55 Section 102-80.55 Public...

  11. Corporate interest rate risk management with derivatives in Australia: empirical results

    Directory of Open Access Journals (Sweden)

    Luiz Augusto Ferreira Carneiro

    2008-04-01

    Full Text Available Financial and insurance theories explain that large widely-held corporations manage corporate risks if doing so is costective to reduce frictional costs such as taxes, agency costs and financial distress costs. A large number of previous empirical studies, most in the U.S., have tested the hypotheses underlying corporate risk management with financial derivative instruments. In order to quantify corporate hedge demand, most previous studies have used the ratio of principal notional amount of derivatives to company size, although they recognize that company size is not an appropriate proxy for financial risk. This paper analyzes the interest-rate-risk hedge demand by Australian companies, measured through the ratio of principal notional amount of interest rate derivatives to interest-rate-riskbearing liabilities. Modern panel data methods are used, with two panel data sets from 1998 to 2003 (1102 and 465 observations, respectively. Detailed information about interest-rate-risk exposures was available after manual data collection from financial annual reports, which was only possible due to specific reporting requirements in Australian accounting standards. Regarding the analysis of the extent of hedge, our measurement of interest-rate-risk exposures generates some significant results di erent from those found in previous studies. For example, this study shows that total leverage (total debt ratio is not significantly important to interest-rate-risk hedge demand and that, instead, this demand is related to the specific risk exposure in the interest bearing part of the firms liabilities. This study finds significant relations of interest-rate-risk hedge to company size, floating-interest-rate debt ratio, annual log returns, and company industry type (utilities and non-banking financial institutions.

  12. Inappropriate use of payment weights to risk adjust readmission rates.

    Science.gov (United States)

    Fuller, Richard L; Goldfield, Norbert I; Averill, Richard F; Hughes, John S

    2012-01-01

    In this article, the authors demonstrate that the use of relative weights, as incorporated within the National Quality Forum-endorsed PacifiCare readmission measure, is inappropriate for risk adjusting rates of hospital readmission.

  13. Risks and rewards of variable-rate debt.

    Science.gov (United States)

    Jordahl, Eric A

    2012-05-01

    Hospital and health system finance leaders should position their organizations to participate in the variable-rate market. To this end, one important step is to establish the right baseline variable-rate exposure target for the organization based on its credit and risk profile. Leaders also should be thoroughly familiar with the available products and understand the circumstances (pricing, terms, and embedded risk) under which the organization would be willing to deploy them within the overall capital structure.

  14. Mapping regional soil water erosion risk in the Brittany-Loire basin for water management agency

    Science.gov (United States)

    Degan, Francesca; Cerdan, Olivier; Salvador-Blanes, Sébastien; Gautier, Jean-Noël

    2014-05-01

    quantified: the soil factors (soil sealing, erodibility and runoff), the rate of land cover over three years for each season and for 77 land use classes, the topographic factor (slope and drainage area) and the climate hazard (seasonal amount and rainfall erosivity). These modifications of the original MESALES model allow to better represent erosion risk for arable and bare land. We validated model results by stakeholder consultations and meetings over all the study area. The model has finally been modified taking into account validation results. Results are provided with a spatial resolution of 1 km, and then integrated into 2121 catchments. An erosion risk map for each season and an annual erosion risk map are produced. These new maps allow to organize in hierarchy 2121 catchments into three erosion risk classes. In the annual erosion risk map, 347 catchments have the highest erosion risk, which corresponds to 16 % of total Brittany-Loire basin area. Water management agency now uses these maps to identify priority areas and to plan specific preservation practices.

  15. Risk and complication rate of uterine fibroid embolization (UFE)

    International Nuclear Information System (INIS)

    Radeleff, B.; Rimbach, S.; Kauffmann, G.W.; Richter, G.M.

    2003-01-01

    Our goal was to evaluate risks and complication rate of uterine fibroid embolization (UFE). The most frequent complications reported in the literature are associated with angiography procedure, serious complications are extremely infrequent. The embolization of fibroids is a safe angiographic intervention. Nevertheless, the interventional radiologist must be aware of the common risks and complication and the strategies to avoid them. (orig.) [de

  16. College Students' Perceived Disease Risk versus Actual Prevalence Rates

    Science.gov (United States)

    Smith, Matthew Lee; Dickerson, Justin B.; Sosa, Erica T.; McKyer, E. Lisako J.; Ory, Marcia G.

    2012-01-01

    Objective: To compare college students' perceived disease risk with disease prevalence rates. Methods: Data were analyzed from 625 college students collected with an Internet-based survey. Paired t-tests were used to separately compare participants' perceived 10-year and lifetime disease risk for 4 diseases: heart disease, cancer, diabetes, and…

  17. Sovereign ratings in the post-crisis world : an analysis of actual, shadow and relative risk ratings

    OpenAIRE

    Basu, Kaushik; De, Supriyo; Ratha, Dilip; Timmer, Hans

    2013-01-01

    This paper analyzes the evolution of sovereign credit ratings in the wake of the global financial crisis by studying changes in actual, shadow, and relative ratings between 2008 and 2012. For countries that do not have a rating from the major rating agencies, shadow ratings are estimated as a function of macroeconomic, structural, and governance variables. The shadow rating exercise confir...

  18. A Critical Analysis of the Recent Russian Regulation on Credit Rating Agencies

    Directory of Open Access Journals (Sweden)

    Lorenzo Sasso

    2016-01-01

    Full Text Available Since the recent financial crisis of 2008, credit rating agencies (CRAs have been under scrutiny for their role in the proliferation of structured finance products. Whether their methodological tools and evaluations have been up to standard is in question. As is well-known, CRAs are multinational enterprises that operate on a global basis. Their evaluations may well hinder the stability of international markets. As a legal response to the many concerns raised about CRAs, different approaches have been applied to the use of credit ratings in the US and EU with many similarities. In this international scenario, the government of the Russian Federation also recently introduced a new regulation on CRAs, drafted on the lines of the European regulation. This short paper is targeted to inform the reader of certain aspects of the newly approved regulation in Russia and to examine – in a comparative way – whether the introduced rules match the expectations behind the initiatives of the Russian government.

  19. Falls risk assessment begins with hello: lessons learned from the use of one home health agency's fall risk tool.

    Science.gov (United States)

    Flemming, Patricia J; Ramsay, Katherine

    2012-10-01

    Identifying older adults at risk for falls is a challenge all home healthcare agencies (HHAs) face. The process of assessing for falls risk begins with the initial home visit. One HHA affiliated with an academic medical center describes its experience in development and use of a Falls Risk Assessment (FRA) tool over a 10-year period. The FRA tool has been modified since initial development to clarify elements of the tool based on research and to reflect changes in the Outcome and Assessment Information Set (OASIS) document. The primary purpose of this article is to share a validated falls risk assessment tool to facilitate identification of fall-related risk factors in the homebound population. A secondary purpose is to share lessons learned by the HHA during the 10 years using the FRA.

  20. KRW/USD Exchange Rate Volatility and Efficient Risk Management

    OpenAIRE

    Sang-Yong Joo; Chae-Shick Chung; Young-Woo Lee

    1999-01-01

    This thesis analyzes the relationship between the exchange rate of Korean Won and US dollar and the amount of foreign exchange, and studies the direction of the amendment of the risk control of foreign exchange. The GARCH (Generalized Auto Regressive Conditional Heteroscedasticity) model which visually embodies the auto-regress of the wave of exchange rate shows that the amount of trade will enhance the fluidity of the exchange rate, that is, the various expects of the participators of the ma...

  1. Ratings of Sovereign Risk and the Macroeconomics Fundamentals of the countries: a Study Using Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Osvaldo Cândido da Silva Filho

    2009-05-01

    Full Text Available To minimize the consequences of asymmetric information, the sovereign risk ratings are instruments that constitute a key piece in the determination of credit market conditions, essential to the growth of developing countries like Brazil. In the present work we studied based on macroeconomics foundations, a classification to sovereign risk ratings realized by the ratings agencies finding the classification using Artificial Neural Networks. We observed homogeneity degree between the attributions of agencies and macroeconomics foundations in the countries of sample which four of foundations seem to be more directly connected with these attributions. After, in a comparative static exercise, we use the model to make simulations of scenarios of the credit external conditions for the Brazilian economy, changing the macroeconomics foundations which we noted that agencies expected for more per capita income increasing and decrease of public debt. (Full article in Portuguese only

  2. Failure rate data for fusion safety and risk assessment

    International Nuclear Information System (INIS)

    Cadwallader, L.C.

    1993-01-01

    The Fusion Safety Program (FSP) at the Idaho National Engineering Laboratory (INEL) conducts safety research in materials, chemical reactions, safety analysis, risk assessment, and in component research and development to support existing magnetic fusion experiments and also to promote safety in the design of future experiments. One of the areas of safety research is applying probabilistic risk assessment (PRA) methods to fusion experiments. To apply PRA, we need a fusion-relevant radiological dose code and a component failure rate data base. This paper describes the FSP effort to develop a failure rate data base for fusion-specific components

  3. 77 FR 57990 - Interest Rate Risk Policy and Program

    Science.gov (United States)

    2012-09-19

    ... NATIONAL CREDIT UNION ADMINISTRATION 12 CFR Part 741 RIN 3133-AD66 Interest Rate Risk Policy and Program Correction In rule document 2012-02091, appearing on pages 55155-5167 in the issue of Thursday, February 2, 2012, make the following corrections: 1. On page 5157, in the second column, in the first line...

  4. Government spending shocks, sovereign risk and the exchange rate regime

    NARCIS (Netherlands)

    Bonam, D.; Lukkezen, J.H.J.

    2014-01-01

    Keynesian theory predicts output responses upon a fiscal expansion in a small open economy to be larger under fixed than floating exchange rates. We analyse the effects of fiscal expansions using a New Keynesian model and find that the reverse holds in the presence of sovereign default risk. By

  5. Courting disaster: How diversification rate affects fitness under risk

    Science.gov (United States)

    Ratcliff, William C; Hawthorne, Peter; Libby, Eric

    2015-01-01

    Life is full of risk. To deal with this uncertainty, many organisms have evolved bet-hedging strategies that spread risk through phenotypic diversification. These rates of diversification can vary by orders of magnitude in different species. Here we examine how key characteristics of risk and organismal ecology affect the fitness consequences of variation in diversification rate. We find that rapid diversification is strongly favored when the risk faced has a wide spatial extent, with a single disaster affecting a large fraction of the population. This advantage is especially great in small populations subject to frequent disaster. In contrast, when risk is correlated through time, slow diversification is favored because it allows adaptive tracking of disasters that tend to occur in series. Naturally evolved diversification mechanisms in diverse organisms facing a broad array of environmental risks largely support these results. The theory presented in this article provides a testable ecological hypothesis to explain the prevalence of slow stochastic switching among microbes and rapid, within-clutch diversification strategies among plants and animals. PMID:25410817

  6. Courting disaster: How diversification rate affects fitness under risk.

    Science.gov (United States)

    Ratcliff, William C; Hawthorne, Peter; Libby, Eric

    2015-01-01

    Life is full of risk. To deal with this uncertainty, many organisms have evolved bet-hedging strategies that spread risk through phenotypic diversification. These rates of diversification can vary by orders of magnitude in different species. Here we examine how key characteristics of risk and organismal ecology affect the fitness consequences of variation in diversification rate. We find that rapid diversification is strongly favored when the risk faced has a wide spatial extent, with a single disaster affecting a large fraction of the population. This advantage is especially great in small populations subject to frequent disaster. In contrast, when risk is correlated through time, slow diversification is favored because it allows adaptive tracking of disasters that tend to occur in series. Naturally evolved diversification mechanisms in diverse organisms facing a broad array of environmental risks largely support these results. The theory presented in this article provides a testable ecological hypothesis to explain the prevalence of slow stochastic switching among microbes and rapid, within-clutch diversification strategies among plants and animals. © 2014 The Author(s). Evolution published by Wiley Periodicals, Inc. on behalf of The Society for the Study of Evolution.

  7. 5 CFR 591.229 - How does OPM inform agencies and employees of COLA rate changes?

    Science.gov (United States)

    2010-01-01

    ... MANAGEMENT CIVIL SERVICE REGULATIONS ALLOWANCES AND DIFFERENTIALS Cost-of-Living Allowance and Post Differential-Nonforeign Areas Cost-Of-Living Allowances § 591.229 How does OPM inform agencies and employees of...

  8. KRW/USD Exchange Rate Volatility and Efficient Risk Management

    Directory of Open Access Journals (Sweden)

    Sang-Yong Joo

    1999-03-01

    Full Text Available This thesis analyzes the relationship between the exchange rate of Korean Won and US dollar and the amount of foreign exchange, and studies the direction of the amendment of the risk control of foreign exchange. The GARCH (Generalized Auto Regressive Conditional Heteroscedasticity model which visually embodies the auto-regress of the wave of exchange rate shows that the amount of trade will enhance the fluidity of the exchange rate, that is, the various expects of the participators of the market affect the amount of trade and the fluidity, so in the process of trading, the trader who is in the dry tree of information bears more trading expenditure. It is predicted that the liberalization of foreign exchange rate and fluctuated exchange rate system will jointly bring the enhancement of the fluidity of the exchange rate and the amount of exchange trade. The change of this system will bring the rise of participators in foreign exchange market; meanwhile, it will also initiate superfluous fluidity of foreign exchange market. In order to overcome this problem, the government needs to implement the development strategy of the understructure of the foreign exchange market and the enterprises need to carry through systemic exchange rate risk control.

  9. Quality assessment of state land internal audit agency of Ukraine based on risk-oriented approach

    Directory of Open Access Journals (Sweden)

    N.G. Vugovska

    2015-03-01

    Full Text Available The article stipulates that in modern conditions of development and reform of the national system of state financial control to the fore the issue of quality, which is an integral part of - or the provision of a service or product produced. In the context of our study on the evaluation of the quality of the internal audit system of the State Land Agency, is the efficiency of its operation. The authors have developed scientific and methodical approach to assessing the quality of the internal audit system of the State Land Agency of Ukraine by specifying the list of evaluation criteria and the implementation of risk-based model selection controlled entities, which allowed to determine the potential risk of financial irregularities and frequency of inspections by the State Financial Inspection. Determined that the planned inspections of the state Land Agency should be not less than once every two years. Applying the above approach will reduce the number of violations in budgetary institutions, improve the quality control organization by the internal audit work, increase the responsibility of the head of an effective, legitimate and proper use of funds. The authors were asked to form a report on the results of the internal audit quality in budgetary institutions and determined that for the cooperation of internal audit bodies of the State financial inspection need to be able to use the latest internal audit report to provide recommendations to improve the functioning of the internal control systems in controlled entities.

  10. Let the IRIS Bloom:Regrowing the integrated risk information system (IRIS) of the U.S. Environmental Protection Agency.

    Science.gov (United States)

    Dourson, Michael L

    2018-05-03

    The Integrated Risk Information System (IRIS) of the U.S. Environmental Protection Agency (EPA) has an important role in protecting public health. Originally it provided a single database listing official risk values equally valid for all Agency offices, and was an important tool for risk assessment communication across EPA. Started in 1986, IRIS achieved full standing in 1990 when it listed 500 risk values, the effort of two senior EPA groups over 5 years of monthly face-to-face meetings, to assess combined risk data from multiple Agency offices. Those groups were disbanded in 1995, and the lack of continuing face-to-face meetings meant that IRIS became no longer EPA's comprehensive database of risk values or their latest evaluations. As a remedy, a work group of the Agency's senior scientists should be re-established to evaluate new risks and to update older ones. Risk values to be reviewed would come from the same EPA offices now developing such information on their own. Still, this senior group would have the final authority on posting a risk value in IRIS, independently of individual EPA offices. This approach could also lay the groundwork for an all-government IRIS database, especially needed as more government Agencies, industries and non-governmental organizations are addressing evolving risk characterizations. Copyright © 2018. Published by Elsevier Inc.

  11. Abdominoplasty: Risk Factors, Complication Rates, and Safety of Combined Procedures.

    Science.gov (United States)

    Winocour, Julian; Gupta, Varun; Ramirez, J Roberto; Shack, R Bruce; Grotting, James C; Higdon, K Kye

    2015-11-01

    Among aesthetic surgery procedures, abdominoplasty is associated with a higher complication rate, but previous studies are limited by small sample sizes or single-institution experience. A cohort of patients who underwent abdominoplasty between 2008 and 2013 was identified from the CosmetAssure database. Major complications were recorded. Univariate and multivariate analysis was performed evaluating risk factors, including age, smoking, body mass index, sex, diabetes, type of surgical facility, and combined procedures. The authors identified 25,478 abdominoplasties from 183,914 procedures in the database. Of these, 8,975 patients had abdominoplasty alone and 16,503 underwent additional procedures. The number of complications recorded was 1,012 (4.0 percent overall rate versus 1.4 percent in other aesthetic surgery procedures). Of these, 31.5 percent were hematomas, 27.2 percent were infections and 20.2 percent were suspected or confirmed venous thromboembolism. On multivariate analysis, significant risk factors (p procedures (1.5), and procedure performance in a hospital or surgical center versus office-based surgical suite (1.6). Combined procedures increased the risk of complication (abdominoplasty alone, 3.1 percent; with liposuction, 3.8 percent; breast procedure, 4.3 percent; liposuction and breast procedure, 4.6 percent; body-contouring procedure, 6.8 percent; liposuction and body-contouring procedure, 10.4 percent). Abdominoplasty is associated with a higher complication rate compared with other aesthetic procedures. Combined procedures can significantly increase complication rates and should be considered carefully in higher risk patients. Risk, II.

  12. Predicting temporal trends in total absenteeism rates for civil service employees of a federal public health agency.

    Science.gov (United States)

    Spears, D Ross; McNeil, Carrie; Warnock, Eli; Trapp, Jonathan; Oyinloye, Oluremi; Whitehurst, Vanessa; Decker, K C; Chapman, Sandy; Campbell, Morris; Meechan, Paul

    2014-06-01

    This study evaluates the predictability in temporal absences trends due to all causes (total absenteeism) among employees at a federal agency. The objective is to determine how leave trends vary within the year, and determine whether trends are predictable. Ten years of absenteeism data from an attendance system were analyzed for rates of total absence. Trends over a 10-year period followed predictable and regular patterns during a given year that correspond to major holiday periods. Temporal trends in leave among small, medium, and large facilities compared favorably with the agency as a whole. Temporal trends in total absenteeism rates for an organization can be determined using its attendance system. The ability to predict employee absenteeism rates can be extremely helpful for management in optimizing business performance and ensuring that an organization meets its mission.

  13. Recovering Risk-Neutral Densities from Brazilian Interest Rate Options

    Directory of Open Access Journals (Sweden)

    José Renato Haas Ornelas

    2011-03-01

    Full Text Available Building Risk-Neutral Density (RND from options data is one useful way for extracting market expectations about a financial variable. For a sample of IDI (Brazilian Interbank Deposit Rate Index options from 1998 to 2009, this paper estimates the option-implied Risk-Neutral Densities for the Brazilian short rate using three methods: Shimko, Mixture of Two Log-Normals and Generalized Beta of Second Kind. Our in-sample goodness-of-fit evaluation shows that the Mixture of Log-Normals method provides better fitting to option’s data than the other two methods. The shape of log-normal distributions seems to fit well to the mean-reversal dynamics of Brazilian interest rates. We have also calculated the RND implied Skewness, showing how it could have provided market early-warning signals of the monetary policy outcomes in 2002 and 2003. Overall, Risk-Neutral Densities implied on IDI options showed to be a useful tool for extracting market expectations about future outcomes of the monetary policy.

  14. [Work-related stress risk assessment in a home care agency].

    Science.gov (United States)

    Latocca, R; Riva, M A; D'Orso, M; Ploia, P; Rocca, S; De Vito, G; Cesana, G

    2012-01-01

    The workload, the quality of professional relationships and emotional involvement have a significant impact on distress and burnout in health care-workers; this impact has an hight variability among the different environments and different care facilities (hospital, erderly nursing homes, home care). The risk assessment of work-related stress performed in 2010 in a homecare agency highlighted organizational problems related to the content/context of work and risk factors for health and safety. High turn-over is evidenced as critical among the "sentinel events". The level of job-strain was moderate, even if some critical issues were evidenced especially in the group of physiotherapists; nurses were configured as a homogeneous group with a low level of job-strain. In informative meetings the workers identified the discomfort related to the time for transferring patients from their homes in a high-traffic metropolitan area was identified as the most critical aspect.

  15. Risk Analysis using Corrosion Rate Parameter on Gas Transmission Pipeline

    Science.gov (United States)

    Sasikirono, B.; Kim, S. J.; Haryadi, G. D.; Huda, A.

    2017-05-01

    In the oil and gas industry, the pipeline is a major component in the transmission and distribution process of oil and gas. Oil and gas distribution process sometimes performed past the pipeline across the various types of environmental conditions. Therefore, in the transmission and distribution process of oil and gas, a pipeline should operate safely so that it does not harm the surrounding environment. Corrosion is still a major cause of failure in some components of the equipment in a production facility. In pipeline systems, corrosion can cause failures in the wall and damage to the pipeline. Therefore it takes care and periodic inspections or checks on the pipeline system. Every production facility in an industry has a level of risk for damage which is a result of the opportunities and consequences of damage caused. The purpose of this research is to analyze the level of risk of 20-inch Natural Gas Transmission Pipeline using Risk-based inspection semi-quantitative based on API 581 associated with the likelihood of failure and the consequences of the failure of a component of the equipment. Then the result is used to determine the next inspection plans. Nine pipeline components were observed, such as a straight pipes inlet, connection tee, and straight pipes outlet. The risk assessment level of the nine pipeline’s components is presented in a risk matrix. The risk level of components is examined at medium risk levels. The failure mechanism that is used in this research is the mechanism of thinning. Based on the results of corrosion rate calculation, remaining pipeline components age can be obtained, so the remaining lifetime of pipeline components are known. The calculation of remaining lifetime obtained and the results vary for each component. Next step is planning the inspection of pipeline components by NDT external methods.

  16. [The Pharmaceuticals and Medical Devices Agency's Approach to Facilitate Risk Communication and Its Challenges].

    Science.gov (United States)

    Kondo, Emiko; Torii, Mayumi; Oba, Izumi; Okamoto, Mai

    2018-01-01

     The issue of drug lag in Japan has been rapidly reduced in recent years, and newly approved drugs now become available on Japanese and international markets at the same time. In this context, the risk management plan (RMP) system was introduced in 2012. RMPs describe important safety concerns recognized by Japan's Pharmaceuticals and Medical Devices Agency (PMDA) and marketing authorization holders (MAHs), as well as safety measures that MAHs request healthcare professionals (HCPs) to follow. The publication of RMPs is expected to support the sharing of drug risk management among HCPs during the postmarketing phase. In addition, to encourage risk communication between HCPs and patients, the PMDA website provides drug guides for patients and other information to promote proper understanding of drugs by patients and their families and enable them to identify serious adverse drug reactions at an early stage. However, the results of surveys conducted by the PMDA in FY2014 and FY2015 revealed low levels of awareness of RMPs and drug guides for patients in hospitals and other healthcare institutions. The surveys also showed that information regarding the proper use of drugs from MAHs and the PMDA was not incorporated into practice at healthcare institutions, resulting in the repeated release of identical safety alerts. To facilitate the increased utilization of risk communication tools, the PMDA has been providing and disseminating these tools through its website. This study addresses those efforts and the associated challenges.

  17. Basal metabolic rate and risk-taking behaviour in birds.

    Science.gov (United States)

    Møller, A P

    2009-12-01

    Basal metabolic rate (BMR) constitutes the minimal metabolic rate in the zone of thermo-neutrality, where heat production is not elevated for temperature regulation. BMR thus constitutes the minimum metabolic rate that is required for maintenance. Interspecific variation in BMR in birds is correlated with food habits, climate, habitat, flight activity, torpor, altitude, and migration, although the selective forces involved in the evolution of these presumed adaptations are not always obvious. I suggest that BMR constitutes the minimum level required for maintenance, and that variation in this minimum level reflects the fitness costs and benefits in terms of ability to respond to selective agents like predators, implying that an elevated level of BMR is a cost of wariness towards predators. This hypothesis predicts a positive relationship between BMR and measures of risk taking such as flight initiation distance (FID) of individuals approached by a potential predator. Consistent with this suggestion, I show in a comparative analysis of 76 bird species that species with higher BMR for their body mass have longer FID when approached by a potential predator. This effect was independent of potentially confounding variables and similarity among species due to common phylogenetic descent. These results imply that BMR is positively related to risk-taking behaviour, and that predation constitutes a neglected factor in the evolution of BMR.

  18. Multifractality and value-at-risk forecasting of exchange rates

    Science.gov (United States)

    Batten, Jonathan A.; Kinateder, Harald; Wagner, Niklas

    2014-05-01

    This paper addresses market risk prediction for high frequency foreign exchange rates under nonlinear risk scaling behaviour. We use a modified version of the multifractal model of asset returns (MMAR) where trading time is represented by the series of volume ticks. Our dataset consists of 138,418 5-min round-the-clock observations of EUR/USD spot quotes and trading ticks during the period January 5, 2006 to December 31, 2007. Considering fat-tails, long-range dependence as well as scale inconsistency with the MMAR, we derive out-of-sample value-at-risk (VaR) forecasts and compare our approach to historical simulation as well as a benchmark GARCH(1,1) location-scale VaR model. Our findings underline that the multifractal properties in EUR/USD returns in fact have notable risk management implications. The MMAR approach is a parsimonious model which produces admissible VaR forecasts at the 12-h forecast horizon. For the daily horizon, the MMAR outperforms both alternatives based on conditional as well as unconditional coverage statistics.

  19. 77 FR 38397 - Agency Information Collection (Interest Rate Reduction Refinancing Loan Worksheet) Activities...

    Science.gov (United States)

    2012-06-27

    ... . Please refer to ``OMB Control No. 2900- 0386.'' SUPPLEMENTARY INFORMATION: Title: Interest Rate Reduction... guaranty on all interest rate reduction refinancing loan and provide a receipt as proof that the funding... ensure lenders computed the funding fee and the maximum permissible loan amount for interest rate...

  20. Worst-Case Portfolio Optimization under Stochastic Interest Rate Risk

    Directory of Open Access Journals (Sweden)

    Tina Engler

    2014-12-01

    Full Text Available We investigate a portfolio optimization problem under the threat of a market crash, where the interest rate of the bond is modeled as a Vasicek process, which is correlated with the stock price process. We adopt a non-probabilistic worst-case approach for the height and time of the market crash. On a given time horizon [0; T], we then maximize the investor’s expected utility of terminal wealth in the worst-case crash scenario. Our main result is an explicit characterization of the worst-case optimal portfolio strategy for the class of HARA (hyperbolic absolute risk aversion utility functions.

  1. Risks to health from radiation at low dose rates

    International Nuclear Information System (INIS)

    Gentner, N.E.; Osborne, R.V.

    1997-01-01

    Our focus is on whether, using a balance-of-evidence approach, it is possible to say that at a low enough dose, or at a sufficiently low dose rate, radiation risk reduces to zero in a population. We conclude that insufficient evidence exists at present to support such a conclusion. In part this reflects statistical limitations at low doses, and in part (although mechanisms unquestionably exist to protect us against much of the damage induced by ionizing radiation) the biological heterogeneity of human populations, which means these mechanisms do not act in all members of the population at all times. If it is going to be possible to demonstrate that low doses are less dangerous than we presently assume, the evidence, paradoxically, will likely come from studies of higher dose and dose rate scenarios than are encountered occupationally. (author)

  2. Characteristics of visiting nurse agencies with high home death rates: A prefecture-wide study in Japan.

    Science.gov (United States)

    Kashiwagi, Masayo; Tamiya, Nanako; Murata, Masako

    2015-08-01

    The purpose of the present study was to identify characteristics of visiting nurse agencies (VNA) in Japan with high home death rates by a prefecture-wide survey. A cross-sectional study of visiting nurse agencies (n = 101) in Ibaraki Prefecture, Japan, was completed. Data included the basic characteristics of each VNA, the type of services provided, level of coordination with other service providers, total number of VNA patients who died per year and place of death and contractual relationship with home-care supporting clinics providing end-of-life care services in the home 24 h a day. The VNA characteristics were analyzed by logistic regression, using the home death rate per VNA as a dependent variable. A total 69 agencies, excluding those that did not report number of deaths (n = 14) and those without deaths during the year (n = 6), were analyzed. The median home death rate of the 69 VNA was 29.8%. The results of logistic regression analysis showed that higher home death rate was significantly associated with lack of attachment to a hospital, existence of a contractual relationship with home-care supporting clinics and existence of an interactive information exchange through telephone/face-to-face communication with attending physicians. In order to increase the home death rate of people using VNA, policymakers must consider establishing home-based service systems within the community that can provide home end-of-life care services 24 h a day, and support the interactive exchange of information between the visiting nurse and the attending physician. © 2014 The Authors. Geriatrics & Gerontology International published by Wiley Publishing Asia Pty Ltd on behalf of Japanese Geriatrics Society.

  3. Modelling Counterparty Credit Risk in Czech Interest Rate Swaps

    Directory of Open Access Journals (Sweden)

    Lenka Křivánková

    2017-01-01

    Full Text Available According to the Basel Committee’s estimate, three quarters of counterparty credit risk losses during the financial crisis in 2008 originate from credit valuation adjustment’s losses and not from actual defaults. Therefore, from 2015, the Third Basel Accord (EU, 2013a and (EU, 2013b instructed banks to calculate the capital requirement for the risk of credit valuation adjustment (CVA. Banks are trying to model CVA to hold the prescribed standards and also reach the lowest possible impact on their profit. In this paper, we try to model CVA using methods that are in compliance with the prescribed standards and also achieve the smallest possible impact on the bank’s earnings. To do so, a data set of interest rate swaps from 2015 is used. The interest rate term structure is simulated using the Hull-White one-factor model and Monte Carlo methods. Then, the probability of default for each counterparty is constructed. A safe level of CVA is reached in spite of the calculated the CVA achieving a lower level than CVA previously used by the bank. This allows a reduction of capital requirements for banks.

  4. Interest rate risk measurement in Brazilian sovereign markets

    Directory of Open Access Journals (Sweden)

    Caio Ibsen Rodrigues de Almeida

    2004-06-01

    Full Text Available Fixed income emerging markets are an interesting investment alternative. Measuring market risks is mandatory in order to avoid unexpected huge losses. The most used market risk measure is the Value at Risk, based on the profit-loss probability distribution of the portfolio under consideration. Estimating this probability distribution requires the prior estimation of the probability distribution of term structures of interest rates. An interesting possibility is to estimate term structures using a decomposition of the spread function into a linear combination of Legendre polynomials. Numerical examples from the Brazilian sovereign fixed income international market illustrate the practical use of the methodology.Os mercados emergentes de renda fixa são alternativas interessantes para investimentos. Devido ao elevado nível de incerteza existente em tais mercados, a mensuração dos riscos de mercado de uma carteira de investimentos é fundamental para que se evite um nível elevado de perdas. Uma das medidas de risco de mercado mais utilizadas é o Value at Risk, baseado na distribuição de probabilidades de perdas-ganhos da carteira sob análise. A estimação desta distribuição requer, no entanto, a estimação prévia da distribuição de pro-babilidades das variações da estrutura a termo da taxa de juros. Uma possibilidade interessante para a estimação de tal distribuição é efetuar uma decomposição da função de spread da estrutura a termo em uma combinação linear de Polinômios de Legendre. Exemplos numéricos do mercado internacional de títulos soberanos brasileiros são apresentados para ilustrar o uso prático desta nova metodologia.

  5. Asset backed securities : risks, ratings and quantitative modelling

    NARCIS (Netherlands)

    Jönsson, B.H.B.; Schoutens, W.

    2009-01-01

    Asset backed securities (ABSs) are structured finance products backed by pools of assets and are created through a securitisation process. The risks in asset backed securities, such as, credit risk, prepayment risk, market risks, operational risk, and legal risks, are directly connected with the

  6. Agency costs and income taxation

    Directory of Open Access Journals (Sweden)

    Ulrich Schmidt

    2012-03-01

    Full Text Available This paper analyzes agency costs and the moral hazard problem in the presence of income taxation. As basic framework, income taxes are integrated in the hidden action model of agency theory. In the case of symmetric information no agency costs occur, i.e. optimal risk-sharing can be achieved, if and only if the tax is proportional. It is well-known that asymmetric information causes a welfare loss, termed agency costs, even if no taxes are imposed. Introducing a proportional income tax now increases (decreases these agency costs if the agent exhibits decreasing (increasing absolute risk aversion. Additionally, we show that non-proportional taxes cause higher (lower agency costs than a proportional tax if the agent’s marginal tax rate exceeds (is smaller than the marginal tax rate of the principal.

  7. Flood Insurance Rate Maps and Base Flood Elevations, FIRM, DFIRM, BFE, Federal Emergency Management Agency (FEMA) - Flood Insurance Rate Maps (FIRM), Published in 2011, 1:1200 (1in=100ft) scale, Polk County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Flood Insurance Rate Maps and Base Flood Elevations, FIRM, DFIRM, BFE dataset current as of 2011. Federal Emergency Management Agency (FEMA) - Flood Insurance Rate...

  8. Alarming of exchange rate crisis: A risk management approach

    Directory of Open Access Journals (Sweden)

    Da Zhao

    2016-05-01

    Full Text Available Recently, with increasing volatility of foreign exchange rate, risk management becomes more and more important not only for multinational companies and individuals but also for central governments. This paper attempts to build an econometrics model so as to forecast and manage risks in foreign exchange market, especially during the eve of turbulent periods. By following McNeil and Frey’s (2000 two stage approach called conditional EVT to estimate dynamic VaR commonly used in stock and insurance markets, we extend it by applying a more general asymmetric ARMA-GARCH model to analyze daily foreign exchange dollar-denominated trading data from four countries of different development levels across Asia and Europe for a period of more than 10 years from January 03, 2005 to May 29, 2015, which is certainly representative of global markets. Conventionally, different kinds of backtesting methods are implemented ultimately to evaluate how well the model behaves. Inspiringly, test results show that by taking several specific characteristics (including fat-tails, asymmetry and long-range dependence of the foreign exchange market return data into consideration, the violation ratio of out-of-sample data can be forecasted very well for both fixed and flexible foreign exchange regimes. Moreover, all of the violations are evenly distributed along the whole period which indicates another favorable property of our model. Meanwhile, we find evidence of asymmetry volatility in all of the studied foreign exchange markets even though the magnitudes of the most of them are weak

  9. Dynamic Correlations of Sovereign Bond Yield Spreads in the Euro zone and the Role of Credit Rating Agencies' Downgrades

    OpenAIRE

    Antonakakis, Nikolaos

    2012-01-01

    The European debt crisis that followed the global financial crisis, erupting first with Greece, then Ireland, Portugal, Italy and Spain, has threatened the very existence of the Euro zone. In this paper we examine the evolution of dynamic co-movements of sovereign bond yield spreads (BYS) in the Euro zone and the role of credit rating agency downgrades on those co-movements. Estimation results from a multivariate DCC-GARCH model on daily BYS data for nine Euro zone countries over the period 2...

  10. Injury rates and risk factors in competitive professional boxing.

    Science.gov (United States)

    Zazryn, Tsharni R; McCrory, Paul R; Cameron, Peter A

    2009-01-01

    To determine injury rates and risk factors for injury in a cohort of professional boxers. Retrospective cohort design reporting on data collected for a fight statistics database maintained by the Professional Boxing and Combat Sports Board of Victoria, Australia. Data were extracted for the years January 1997 through June 2005. Victoria, Australia. 545 professional boxers (age, 18 to 43 years) who participated in a total of 907 fights over the study period. Independent variables under investigation included age, gender, weight, bout exposure, and location of the bout (within or outside of the State of Victoria). Physician-reported acute boxing injuries occurring during bouts of any region or nature. 214 injuries were sustained over the 8.5 years, corresponding to an injury rate of 23.6 per 100 professional fights. The majority of these injuries were lacerations to the head and face. An increasing age and an increasing number of fights were both significant predictors of injury. Injury reduction strategies for professional boxing might include restrictions of eligibility to fight based on age and boxing bout exposure. Future research using prospective cohort designs and standardized injury definitions are needed to confirm these results. Greater mechanistic detail and more complete data entry are necessary to ensure that optimal injury prevention strategies can be developed and implemented. Upon confirmation of the results of this study, the Professional Boxing and Combat Sports Board of Victoria may consider different criteria upon which to sanction a fight.

  11. An Effective Risk Minimization Strategy Applied to an Outdoor Music Festival: A Multi-Agency Approach.

    Science.gov (United States)

    Luther, Matt; Gardiner, Fergus; Lenson, Shane; Caldicott, David; Harris, Ryan; Sabet, Ryan; Malloy, Mark; Perkins, Jo

    2018-04-01

    Specific Event Identifiers a. Event type: Outdoor music festival. b. Event onset date: December 3, 2016. c. Location of event: Regatta Point, Commonwealth Park. d. Geographical coordinates: Canberra, Australian Capital Territory (ACT), Australia (-35.289002, 149.131957, 600m). e. Dates and times of observation in latitude, longitude, and elevation: December 3, 2016, 11:00-23:00. f. Response type: Event medical support. Abstract Introduction Young adult patrons are vulnerable to risk-taking behavior, including drug taking, at outdoor music festivals. Therefore, the aim of this field report is to discuss the on-site medical response during a music festival, and subsequently highlight observed strategies aimed at minimizing substance abuse harm. The observed outdoor music festival was held in Canberra (Australian Capital Territory [ACT], Australia) during the early summer of 2016, with an attendance of 23,008 patrons. First aid and on-site medical treatment data were gained from the relevant treatment area and service. The integrated first aid service provided support to 292 patients. Final analysis consisted of 286 patients' records, with 119 (41.6%) males and 167 (58.4%) females. Results from this report indicated that drug intoxication was an observed event issue, with 15 (5.1%) treated on site and 13 emergency department (ED) presentations, primarily related to trauma or medical conditions requiring further diagnostics. This report details an important public health need, which could be met by providing a coordinated approach, including a robust on-site medical service, accepting intrinsic risk-taking behavior. This may include on-site drug-checking, providing reliable information on drug content with associated education. Luther M , Gardiner F , Lenson S , Caldicott D , Harris R , Sabet R , Malloy M , Perkins J . An effective risk minimization strategy applied to an outdoor music festival: a multi-agency approach. Prehosp Disaster Med. 2018;33(2):220-224.

  12. Abnormal agency experiences in schizophrenia patients : examining the role of psychotic symptoms and familial risk

    NARCIS (Netherlands)

    Prikken, Merel; van der Weiden, A.; Renes, R.A.; Koevoets, Martijn G J C; Heering, H.D.; Kahn, R.R.; Aarts, H.; Haren, N.E.M.

    2017-01-01

    Experiencing self-agency over one’s own action outcomes is essential for social functioning. Recent research revealed that patients with schizophrenia do not use implicitly available information about their action-outcomes (i.e., prime-based agency inference) to arrive at self-agency experiences.

  13. Abnormal agency experiences in schizophrenia patients: Examining the role of psychotic symptoms and familial risk

    NARCIS (Netherlands)

    Prikken, Merel; van der Weiden, Anouk; Renes, Robert A.; Koevoets, Martijn G. J. C.; Heering, Henriette D.; Kahn, René S.; Aarts, Henk; van Haren, Neeltje E. M.

    2017-01-01

    Experiencing self-agency over one's own action outcomes is essential for social functioning. Recent research revealed that patients with schizophrenia do not use implicitly available information about their action-outcomes (i.e., prime-based agency inference) to arrive at self-agency experiences.

  14. Abnormal agency experiences in schizophrenia patients : Examining the role of psychotic symptoms and familial risk

    NARCIS (Netherlands)

    Prikken, Merel; van der Weiden, Anouk; Renes, Robert A.; Koevoets, Godefridus J C; Heering, Henriette D.; Kahn, René S.; Aarts, Henk; van Haren, Neeltje E M

    2017-01-01

    Experiencing self-agency over one's own action outcomes is essential for social functioning. Recent research revealed that patients with schizophrenia do not use implicitly available information about their action-outcomes (i.e., prime-based agency inference) to arrive at self-agency experiences.

  15. 75 FR 9257 - SBA Lender Risk Rating System

    Science.gov (United States)

    2010-03-01

    ... Liquidation Rate; 3. Gross Delinquency Rate; 4. Gross Past-Due Rate; 5. Six (6) Month Net Flow Indicator; 6.... The statistical analysis performed showed that incorporating the Portfolio Size/Age component improved...) Month Delinquency Rate; 3. Gross Delinquency Rate; 4. Gross Past-Due Rate; 5. Average Small Business...

  16. Gambling disorder: estimated prevalence rates and risk factors in Macao.

    Science.gov (United States)

    Wu, Anise M S; Lai, Mark H C; Tong, Kwok-Kit

    2014-12-01

    An excessive, problematic gambling pattern has been regarded as a mental disorder in the Diagnostic and Statistical Manual for Mental Disorders (DSM) for more than 3 decades (American Psychiatric Association [APA], 1980). In this study, its latest prevalence in Macao (one of very few cities with legalized gambling in China and the Far East) was estimated with 2 major changes in the diagnostic criteria, suggested by the 5th edition of DSM (APA, 2013): (a) removing the "Illegal Act" criterion, and (b) lowering the threshold for diagnosis. A random, representative sample of 1,018 Macao residents was surveyed with a phone poll design in January 2013. After the 2 changes were adopted, the present study showed that the estimated prevalence rate of gambling disorder was 2.1% of the Macao adult population. Moreover, the present findings also provided empirical support to the application of these 2 recommended changes when assessing symptoms of gambling disorder among Chinese community adults. Personal risk factors of gambling disorder, namely being male, having low education, a preference for casino gambling, as well as high materialism, were identified.

  17. 12 CFR 652.15 - Interest rate risk management and requirements.

    Science.gov (United States)

    2010-01-01

    ... 12 Banks and Banking 6 2010-01-01 2010-01-01 false Interest rate risk management and requirements... AGRICULTURAL MORTGAGE CORPORATION FUNDING AND FISCAL AFFAIRS Investment Management § 652.15 Interest rate risk... (direction, controls, and supervision) to the interest rate risk management program and must be knowledgeable...

  18. Critical Considerations in Becoming Literacy Educators: Pre-Service Teachers Rehearsing Agency and Negotiating Risk

    Science.gov (United States)

    Ticknor, Anne Swenson

    2015-01-01

    This article looks closely at the talk of two pre-service teachers over time to examine how they used language as a way of rehearsing their evolving agency as literacy educators. Drawing on critical sociocultural theory, I use Agency Tracing to highlight how pre-service teachers' agentic actions are not isolated phenomena but ones developed and…

  19. 77 FR 5155 - Interest Rate Risk Policy and Program

    Science.gov (United States)

    2012-02-02

    ... directors and management; appropriate IRR measurement and monitoring systems; good internal controls; and... Systems B. Risk Measurement Methods C. Components of IRR Measurement Methods V. Internal Controls VI... risk management and a program to effectively implement that policy, as part of their asset liability...

  20. Essays on long-term mortality and interest rate risk

    NARCIS (Netherlands)

    de Kort, J.P.

    2017-01-01

    This dissertation comprises a study of long-term risks which play a major role in actuarial science. In Part I we analyse long-term mortality risk and its impact on consumption and investment decisions of economic agents, while Part II focuses on the mathematical modelling of long-term interest

  1. Carbon recovery rates following different wildfire risk mitigation treatments

    Science.gov (United States)

    M. Hurteau; M. North

    2010-01-01

    Sequestered forest carbon can provide a climate change mitigation benefit, but in dry temperate forests, wildfire poses a reversal risk to carbon offset projects. Reducing wildfire risk requires a reduction in and redistribution of carbon stocks, the benefit of which is only realized when wildfire occurs. To estimate the time needed to recover carbon removed and...

  2. 12 CFR 615.5180 - Interest rate risk management by banks-general.

    Science.gov (United States)

    2010-01-01

    ... 12 Banks and Banking 6 2010-01-01 2010-01-01 false Interest rate risk management by banks-general... FISCAL AFFAIRS, LOAN POLICIES AND OPERATIONS, AND FUNDING OPERATIONS Risk Assessment and Management § 615.5180 Interest rate risk management by banks—general. The board of directors of each Farm Credit Bank...

  3. 12 CFR 563.176 - Interest-rate-risk-management procedures.

    Science.gov (United States)

    2010-01-01

    ... 12 Banks and Banking 5 2010-01-01 2010-01-01 false Interest-rate-risk-management procedures. 563... ASSOCIATIONS-OPERATIONS Financial Management Policies § 563.176 Interest-rate-risk-management procedures... association's management of that risk. (b) The board of directors shall formerly adopt a policy for the...

  4. 12 CFR 615.5181 - Bank interest rate risk management program.

    Science.gov (United States)

    2010-01-01

    ... 12 Banks and Banking 6 2010-01-01 2010-01-01 false Bank interest rate risk management program. 615... FISCAL AFFAIRS, LOAN POLICIES AND OPERATIONS, AND FUNDING OPERATIONS Risk Assessment and Management § 615.5181 Bank interest rate risk management program. (a) The board of directors of each Farm Credit Bank...

  5. 76 FR 40749 - Cost-Based and Inter-Agency Billing Rates for Medical Care or Services Provided by the Department...

    Science.gov (United States)

    2011-07-11

    ... Billed to Third Parties for Prescription Drugs Furnished by VA to a Veteran for a Nonservice-Connected... methodology set forth in 38 CFR 17.102, which was only to be used until such time as charges for prescription... follows: Cost-based Inter-agency rates rates A. Hospital Care per inpatient day General Medicine: All...

  6. Agreement in cardiovascular risk rating based on anthropometric parameters

    International Nuclear Information System (INIS)

    Dantas, Endilly Maria da Silva; Pinto, Cristiane Jordânia; Freitas, Rodrigo Pegado de Abreu; Medeiros, Anna Cecília Queiroz de

    2015-01-01

    To investigate the agreement in evaluation of risk of developing cardiovascular diseases based on anthropometric parameters in young adults. The study included 406 students, measuring weight, height, and waist and neck circumferences. Waist-to-height ratio and the conicity index. The kappa coefficient was used to assess agreement in risk classification for cardiovascular diseases. The positive and negative specific agreement values were calculated as well. The Pearson chi-square (χ"2) test was used to assess associations between categorical variables (p<0.05). The majority of the parameters assessed (44%) showed slight (k=0.21 to 0.40) and/or poor agreement (k<0.20), with low values of negative specific agreement. The best agreement was observed between waist circumference and waist-to-height ratio both for the general population (k=0.88) and between sexes (k=0.93 to 0.86). There was a significant association (p<0.001) between the risk of cardiovascular diseases and females when using waist circumference and conicity index, and with males when using neck circumference. This resulted in a wide variation in the prevalence of cardiovascular disease risk (5.5%-36.5%), depending on the parameter and the sex that was assessed. The results indicate variability in agreement in assessing risk for cardiovascular diseases, based on anthropometric parameters, and which also seems to be influenced by sex. Further studies in the Brazilian population are required to better understand this issue

  7. Agreement in cardiovascular risk rating based on anthropometric parameters

    Energy Technology Data Exchange (ETDEWEB)

    Dantas, Endilly Maria da Silva; Pinto, Cristiane Jordânia; Freitas, Rodrigo Pegado de Abreu; Medeiros, Anna Cecília Queiroz de [Universidade Federal do Rio Grande do Norte, Natal, RN (Brazil)

    2015-07-01

    To investigate the agreement in evaluation of risk of developing cardiovascular diseases based on anthropometric parameters in young adults. The study included 406 students, measuring weight, height, and waist and neck circumferences. Waist-to-height ratio and the conicity index. The kappa coefficient was used to assess agreement in risk classification for cardiovascular diseases. The positive and negative specific agreement values were calculated as well. The Pearson chi-square (χ{sup 2}) test was used to assess associations between categorical variables (p<0.05). The majority of the parameters assessed (44%) showed slight (k=0.21 to 0.40) and/or poor agreement (k<0.20), with low values of negative specific agreement. The best agreement was observed between waist circumference and waist-to-height ratio both for the general population (k=0.88) and between sexes (k=0.93 to 0.86). There was a significant association (p<0.001) between the risk of cardiovascular diseases and females when using waist circumference and conicity index, and with males when using neck circumference. This resulted in a wide variation in the prevalence of cardiovascular disease risk (5.5%-36.5%), depending on the parameter and the sex that was assessed. The results indicate variability in agreement in assessing risk for cardiovascular diseases, based on anthropometric parameters, and which also seems to be influenced by sex. Further studies in the Brazilian population are required to better understand this issue.

  8. 77 FR 9237 - Agency Information Collection Activities; Proposed Collection; Comment Request; Risk Management...

    Science.gov (United States)

    2012-02-16

    ... Activities; Proposed Collection; Comment Request; Risk Management Program Requirements and Petitions To..., non-chemical manufacturers, etc. Title: Risk Management Program Requirements and Petitions to Modify... regulated substance in a process develop and implement a risk management program and submit a risk...

  9. Flood Insurance Rate Map, Scott County, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE,

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, , USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

  12. Comparing variation in hospital rates of cesarean delivery among low-risk women using 3 different measures.

    Science.gov (United States)

    Armstrong, Joanne C; Kozhimannil, Katy B; McDermott, Patricia; Saade, George R; Srinivas, Sindhu K

    2016-02-01

    This report describes the development of a measure of low-risk cesarean delivery by the Society for Maternal-Fetal Medicine (SMFM). Safely lowering the cesarean delivery rate is a priority for maternity care clinicians and health care delivery systems. Therefore, hospital quality assurance programs are increasingly tracking cesarean delivery rates among low-risk pregnancies. Two commonly used definitions of "low risk" are available, the Joint Commission (JC) and the Agency for Healthcare Research and Quality (AHRQ) measures, but these measures are not clinically comprehensive. We sought to refine the definition of the low-risk cesarean delivery rate to enhance the validity of the metric for quality measurement. We created this refined definition-called the SMFM definition-and compared it to the JC and AHRQ measures using claims-based data from the 2011 Nationwide Inpatient Sample of >863,000 births in 612 hospitals. Using these definitions, we calculated means and interquartile ranges (25th-75th percentile range) for hospital low-risk cesarean delivery rates, stratified by hospital size, teaching status, urban/rural location, and payer mix. Across all hospitals, the mean low-risk cesarean delivery rate was lowest for the SMFM definition (12.65%), but not substantially different from the JC and AHRQ measures (13.12% and 13.29%, respectively). We empirically examined the SMFM definition to ensure its validity and utility. This refined definition performs similarly to existing measures and has the added advantage of clinical perspective, enhanced face validity, and ease of use. Copyright © 2016 Elsevier Inc. All rights reserved.

  13. Risk of solid cancer in low dose-rate radiation epidemiological studies and the dose-rate effectiveness factor.

    Science.gov (United States)

    Shore, Roy; Walsh, Linda; Azizova, Tamara; Rühm, Werner

    2017-10-01

    Estimated radiation risks used for radiation protection purposes have been based primarily on the Life Span Study (LSS) of atomic bomb survivors who received brief exposures at high dose rates, many with high doses. Information is needed regarding radiation risks from low dose-rate (LDR) exposures to low linear-energy-transfer (low-LET) radiation. We conducted a meta-analysis of LDR epidemiologic studies that provide dose-response estimates of total solid cancer risk in adulthood in comparison to corresponding LSS risks, in order to estimate a dose rate effectiveness factor (DREF). We identified 22 LDR studies with dose-response risk estimates for solid cancer after minimizing information overlap. For each study, a parallel risk estimate was derived from the LSS risk model using matching values for sex, mean ages at first exposure and attained age, targeted cancer types, and accounting for type of dosimetric assessment. For each LDR study, a ratio of the excess relative risk per Gy (ERR Gy -1 ) to the matching LSS ERR risk estimate (LDR/LSS) was calculated, and a meta-analysis of the risk ratios was conducted. The reciprocal of the resultant risk ratio provided an estimate of the DREF. The meta-analysis showed a LDR/LSS risk ratio of 0.36 (95% confidence interval [CI] 0.14, 0.57) for the 19 studies of solid cancer mortality and 0.33 (95% CI 0.13, 0.54) when three cohorts with only incidence data also were added, implying a DREF with values around 3, but statistically compatible with 2. However, the analyses were highly dominated by the Mayak worker study. When the Mayak study was excluded the LDR/LSS risk ratios increased: 1.12 (95% CI 0.40, 1.84) for mortality and 0.54 (95% CI 0.09, 0.99) for mortality + incidence, implying a lower DREF in the range of 1-2. Meta-analyses that included only cohorts in which the mean dose was LDR data provide direct evidence regarding risk from exposures at low dose rates as an important complement to the LSS risk estimates used

  14. Bank Credit Risk Management and Rating Migration Analysis on the Business Cycle

    Directory of Open Access Journals (Sweden)

    Dimitris Gavalas

    2014-03-01

    Full Text Available Credit risk measurement remains a critical field of top priority in banking finance, directly implicated in the recent global financial crisis. This paper examines the dynamic linkages between credit risk migration due to rating shifts and prevailing macroeconomic conditions, reflected in alternative business cycle states. An innovative empirical methodology applies to bank internal rating data, under different economic scenarios and investigates the implications of credit risk quality shifts for risk rating transition matrices. The empirical findings are useful and critical for banks to align to Basel guidelines in relation to core capital requirements and risk-weighted assets in the underlying loan portfolio.

  15. Study of Risk Assessment Programs at Federal Agencies and Commercial Industry Related to the Conduct or Regulation of High Hazard Operations

    International Nuclear Information System (INIS)

    Bari, R.; Rosenbloom, S.; O'Brien, J.

    2011-01-01

    In the Department of Energy (DOE) Implementation Plan (IP) for Defense Nuclear Facilities Safety Board's Recommendation 2009-1, the DOE committed to studying the use of quantitative risk assessment methodologies at government agencies and industry. This study consisted of document reviews and interviews of senior management and risk assessment staff at six organizations. Data were collected and analyzed on risk assessment applications, risk assessment tools, and controls and infrastructure supporting the correct usage of risk assessment and risk management tools. The study found that the agencies were in different degrees of maturity in the use of risk assessment to support the analysis of high hazard operations and to support decisions related to these operations. Agencies did not share a simple, 'one size fits all' approach to tools, controls, and infrastructure needs. The agencies recognized that flexibility was warranted to allow use of risk assessment tools in a manner that is commensurate with the complexity of the application. The study also found that, even with the lack of some data, agencies application of the risk analysis structured approach could provide useful insights such as potential system vulnerabilities. This study, in combination with a companion study of risk assessment programs in the DOE Offices involved in high hazard operations, is being used to determine the nature and type of controls and infrastructure needed to support risk assessments at the DOE.

  16. Risk assessment and risk management at the Canadian Food Inspection Agency (CFIA): a perspective on the monitoring of foods for chemical residues.

    Science.gov (United States)

    Bietlot, Henri P; Kolakowski, Beata

    2012-08-01

    The Canadian Food Inspection Agency (CFIA) uses 'Ranked Risk Assessment' (RRA) to prioritize chemical hazards for inclusion in monitoring programmes or method development projects based on their relative risk. The relative risk is calculated for a chemical by scoring toxicity and exposure in the 'risk model scoring system' of the Risk Priority Compound List (RPCL). The relative ranking and the risk management options are maintained and updated in the RPCL. The ranking may be refined by the data generated by the sampling and testing programs. The two principal sampling and testing programmes are the National Chemical Residue Monitoring Program (NCRMP) and the Food Safety Action Plan (FSAP). The NCRMP sampling plans focus on the analysis of federally registered products (dairy, eggs, honey, meat and poultry, fresh and processed fruit and vegetable commodities, and maple syrup) for residues of veterinary drugs, pesticides, environmental contaminants, mycotoxins, and metals. The NCRMP is complemented by the Food Safety Action Plan (FSAP) targeted surveys. These surveys focus on emerging chemical hazards associated with specific foods or geographical regions for which applicable maximum residue limits (MRLs) are not set. The data from the NCRMP and FSAP also influence the risk management (follow-up) options. Follow-up actions vary according to the magnitude of the health risk, all with the objective of preventing any repeat occurrence to minimize consumer exposure to a product representing a potential risk to human health. © Her Majesty the Queen in Right of Canada 2012. Drug Testing and Analysis © 2012 John Wiley & Sons, Ltd.

  17. Agency, Managed Care and Financial-Risk Sharing in General Medical Practice

    NARCIS (Netherlands)

    A. Vermaas

    2006-01-01

    textabstractWhich techniques can and do third-party agents apply within their relationships with general practitioners in order to reduce the agency problems within the patient-physician relationship? We gave an overview of techniques that are used by third parties rather commonly – that is to

  18. Medicine and ionizing rays: a help sheet in analysing risks in high rate curietherapy

    International Nuclear Information System (INIS)

    Gauron, C.

    2009-01-01

    This document proposes a synthesis of useful knowledge for radioprotection in the case of high rate curietherapy. Several aspects are considered: the concerned personnel, the course of treatment procedures, the hazards, the identification of the risk associated with ionizing radiation, the risk assessment and the determination of exposure levels, the strategy to control the risks (reduction of risks, technical measures concerning the installation or the personnel, teaching and information, prevention and medical monitoring), and risk control assessment

  19. Medicine and ionizing rays: a help sheet in analysing risks in pulsed rate curietherapy

    International Nuclear Information System (INIS)

    Gauron, C.

    2009-01-01

    This document proposes a synthesis of useful knowledge for radioprotection in the case of pulsed rate curietherapy. Several aspects are considered: the concerned personnel, the course of treatment procedures, the hazards, the identification of the risk associated with ionizing radiation, the risk assessment and the determination of exposure levels, the strategy to control the risks (reduction of risks, technical measures concerning the installation or the personnel, teaching and information, prevention and medical monitoring), and risk control assessment

  20. Hospital ownership: a risk factor for nosocomial infection rates?

    Science.gov (United States)

    Schröder, C; Behnke, M; Geffers, C; Gastmeier, P

    2018-03-26

    In some countries, a relationship between hospital ownership and the occurrence of healthcare-associated infection (HCAI) rates has been described. To investigate the association between hospital ownership and occurrence of HCAI in Germany. Five different components of the German national nosocomial infection surveillance system were analysed with regard to the influence of hospital ownership in the period 2014-2016. Endpoints included ventilator-associated pneumonia, central-venous-catheter-associated bloodstream infections, urinary-catheter-associated urinary tract infections, surgical site infections (SSI) following hip prosthesis and colon surgery, meticillin-resistant Staphylococcus aureus (MRSA), Clostridium difficile infections (CDI) and hand rub consumption per 1000 patient-days. Three hospital ownership types (public, non-profit and private) were analysed using univariate and multi-variate methods. The distribution of hospitals according to the three ownership types was similar in all components. In total, 661 intensive care units (ICUs), 149 departments performing colon procedures, and 349 departments performing hip prosthesis were included. In addition, 568 hospitals provided their MRSA rates and 236 provided their CDI rates, and 1833 ICUs and 12,934 non-ICUs provided their hand rub consumption data. In general, the differences between the hospital types were rather small and not significant for the ICUs. In the multi-variate analysis, public hospitals had a lower SSI rate following hip prosthesis (odds ratio 0.80, 95% confidence interval 0.65-0.99). Hospital ownership was not found to have a major influence on the incidence of HCAI in Germany. Copyright © 2018 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

  1. Sexual agency versus relational factors: a study of condom use antecedents among high-risk young African American women.

    Science.gov (United States)

    Crosby, Richard A; DiClemente, Ralph J; Wingood, Gina M; Salazar, Laura F; Head, Sara; Rose, Eve; McDermott-Sales, Jessica

    2008-03-01

    The influence that female partners exert regarding condom use is not well known. In the present study, the relative roles of personal sexual agency and relational factors in determining whether young African American women engaged in unprotected vaginal sex (UVS) were studied. A cross sectional study of 713 young, African American women (aged 15-21 years) was conducted. Data were collected using an audio-computer assisted self-interview. Three measures of sexual agency were assessed and three relational factors were assessed. To help assure validity in the outcome measure, condom use was assessed in five different ways. Multivariate analyses were used to determine whether variables independently predicted UVS. Two of the six predictor variables achieved multivariate significance with all five measures of condom use: (1) fear of negotiating condom use with male partners, and (2) indicating that stopping to use condoms takes the fun out of sex. A relational factor (male-dominated power imbalances) achieved multivariate significance for four of the five measures of UVS. A sexual agency factor (whether young women greatly enjoyed sex) achieved multivariate significance for three of the five measures. The results suggest that young African American women at high-risk of sexually transmissible infections (STI)/HIV acquisition may experience male-dominated power imbalances and also fear the process of negotiating condom use with their male partners. Although these factors were independently associated with UVS, two factors pertaining to sexual agency of these young women were also important predictors of UVS. Intervention efforts designed to avert STI/HIV acquisition among young African American women should therefore include programs to address both sexual agency and relational factors.

  2. Vaccination rates among the general adult population and high-risk groups in the United States.

    Directory of Open Access Journals (Sweden)

    Kathy Annunziata

    Full Text Available BACKGROUND: In order to adequately assess the effectiveness of vaccination in helping to control vaccine-preventable infectious disease, it is important to identify the adherence and uptake of risk-based recommendations. METHODS: The current project includes data from five consecutive datasets of the National Health and Wellness Survey (NHWS: 2007 through 2011. The NHWS is an annual, Internet-based health questionnaire, administered to a nationwide sample of adults (aged 18 or older which included items on vaccination history as well as high-risk group status. Vaccination rates and characteristics of vaccinees were reported descriptively. Logistic regressions were conducted to predict vaccination behavior from sociodemographics and risk-related variables. RESULTS: The influenza vaccination rate for all adults 18 years and older has increased significantly from 28.0% to 36.2% from 2007 to 2011 (ps<.05. Compared with those not at high risk (25.1%, all high-risk groups were vaccinated at a higher rate, from 36.8% (pregnant women to 69.7% (those with renal/kidney disease; however, considerable variability among high-risk groups was observed. Vaccination rates among high-risk groups for other vaccines varied considerably though all were below 50%, with the exception of immunocompromised respondents (57.5% for the hepatitis B vaccine and 52.5% for the pneumococcal vaccine and the elderly (50.4% for the pneumococcal. Multiple risk factors were associated with increased rate of vaccination for most vaccines. Significant racial/ethnic differences with influenza, hepatitis, and herpes zoster vaccination rates were also observed (ps<.05. CONCLUSIONS: Rates of influenza vaccination have increased over time. Rates varied by high-risk status, demographics, and vaccine. There was a pattern of modest vaccination rate increases for individuals with multiple risk factors. However, there were relatively low rates of vaccination for most risk-based recommendations

  3. Stochastic Discount Factor Approach to International Risk-Sharing: Evidence from Fixed Exchange Rate Episodes

    NARCIS (Netherlands)

    Hadzi-Vaskov, M.; Kool, C.J.M.

    2007-01-01

    This paper presents evidence of the stochastic discount factor approach to international risk-sharing applied to fixed exchange rate regimes. We calculate risk-sharing indices for two episodes of fixed or very rigid exchange rates: the Eurozone before and after the introduction of the Euro, and

  4. Study the rate of fertility and risk factors of schizophrenia in Najaf, Iraq

    African Journals Online (AJOL)

    This study is designed to investigate the main risk factors, which increased the incidence of schizophrenia and the rate of fertility in patients measuring sex hormones (testosterone and estrogen) and prolactin hormone. The aim of study was to evaluate the fertility rate and risk factors of schizophrenia. Blood samples were ...

  5. Examining women's agency in managing intimate partner violence and the related risk of homelessness: The role of harm minimisation.

    Science.gov (United States)

    Meyer, Silke

    2016-01-01

    Intimate partner violence (IPV) has a detrimental impact on women and children's emotional, physical and social well-being and has been identified as one of the most common contributors to women's experiences of housing instabilities and homelessness. Women affected by IPV often experience a great level of uncertainty around housing solutions when trying to leave an abusive partner. This study explores women's responses to IPV and the related risk of homelessness through women's narratives (n = 22) in Queensland, Australia. Of particular interest are women's decisions and actions to minimise the impact of IPV as well as homelessness on their and their children's safety and well-being. Findings reveal that women's agency in relation to harm minimisation can take various forms, including the decision to stay with, leave or return to an abusive partner. The data offer insights into women's strategic attempts to manage IPV and the related risk of homeless while trying to minimise the harm associated with one and the other. Implications for understanding women's agency in managing IPV and the related risk of homelessness and providing adequate support mechanisms to improve women and children's social, emotional and physical well-being are discussed.

  6. Risk of Interest Rates at the Level of Commercial Banks in Romania

    Directory of Open Access Journals (Sweden)

    Sbârcea Ioana Raluca

    2017-12-01

    Full Text Available The banking system in Romania is a banking system under development, subject to fluctuations that exist on the market more than on more developed banking systems, fluctuations that can generate losses for banks if they are not properly managed. The losses that may be generated by these fluctuations, known as market risk, refer to the significant fluctuations in three indicators, namely the interest rate, the exchange rate and the asset price. In this article, I will analyse the interest rate risk from a conceptual point of view and the indicators that mitigate this risk. The analysis also contains a study of this risk among commercial banks in the system to highlight the level of risk and possible effects of its manifestation. I calculated and analysed the interest rate risk indicators, individually for the first three banks in the system, but also to comparatively, in order to highlight the existing differences.

  7. NASA's Agency-Wide Strategy for Environmental Regulatory Risk Analysis and Communication

    Science.gov (United States)

    Scroggins, Sharon; Duda, Kristen

    2008-01-01

    This viewgraph presentation gives an overview of NASA's risk analysis communication programs associated with changing environmental policies. The topics include: 1) NASA Program Transition; 2) Principal Center for Regulatory Risk Analysis and Communication (RRAC PC); and 3) Regulatory Tracking and Communication Process.

  8. Barriers to implementation of risk management for federal wildland fire management agencies in the United States

    Science.gov (United States)

    Dave Calkin; Matthew P. Thompson; Alan A. Ager; Mark Finney

    2010-01-01

    In this presentation we review progress towards the implementation of a risk-based management framework for U.S. Federal wildland fire policy and operations. We first describe new developments in wildfire simulation technology that catalyzed the development of risk-based decision support systems for strategic wildfire management. These systems include new analytical...

  9. Predicting Rehabilitation Success Rate Trends among Ethnic Minorities Served by State Vocational Rehabilitation Agencies: A National Time Series Forecast Model Demonstration Study

    Science.gov (United States)

    Moore, Corey L.; Wang, Ningning; Washington, Janique Tynez

    2017-01-01

    Purpose: This study assessed and demonstrated the efficacy of two select empirical forecast models (i.e., autoregressive integrated moving average [ARIMA] model vs. grey model [GM]) in accurately predicting state vocational rehabilitation agency (SVRA) rehabilitation success rate trends across six different racial and ethnic population cohorts…

  10. Factors to consider in developing individual pharmaceutical product quality risk profiles useful to government procurement agencies.

    Science.gov (United States)

    Xu, Wei; Boehm, Garth; Zheng, Qiang

    2016-01-01

    Governments that procure pharmaceutical products from an Essential Medicine List (EML) bear special responsibility for the quality of these products. In this article we examine the possibility of developing a pharmaceutical product quality risk assessment scheme for use by government procurement officials. We use the Chinese EML as a basis, and US recall data is examined as it is publically available.This is justified as the article is only concerned with inherent product quality risks. After establishing a link between Chinese essential medicines and those available in the US, we examine US recall data to separate product specific recalls. We conclude that, in addition to existing manufacturing based risks, there are two other product specific risks that stand out from all others, degradation and dissolution failure. Methodology for relative product risk for degradation is needed to be developed and further work is required to better understand dissolution failures which largely occur with modified-release solid oral products. We conclude that a product specific quality risk profile would be enhanced by including a risk assessment for degradation for all products, and in the case of solid oral products, dissolution.

  11. Transitional rates, risk and the Ontario wholesale power market

    International Nuclear Information System (INIS)

    Rothman, M.

    2001-01-01

    Navigant Consulting is a large investor-owned management consulting firm specializing in energy-based and other networked and regulated industries across Canada. The company works with clients to create delivery and protect shareholder value in the face of uncertainty and change. This presentation discussed the issue of price volatility in competitive electricity markets. The points to keep in mind for pricing in competitive power markets is that: (1) electricity should be generated simultaneously with use, (2) rates in administered markets are average over some time period, (3) competitive pool markets do not average costs, (4) in competitive pool markets, prices are set in very short (hourly or less) intervals, (5) prices in competitive markets are more volatile than in administered markets for both economic and market structure reasons, and (6) the degree of volatility and price levels can change quickly. The Ontario power market was also discussed with reference to price volatility in Ontario and what this means for electricity customers. tabs., figs

  12. Risk management under a two-factor model of the term structure of interest rates

    OpenAIRE

    Manuel Moreno

    1997-01-01

    This paper presents several applications to interest rate risk management based on a two-factor continuous-time model of the term structure of interest rates previously presented in Moreno (1996). This model assumes that default free discount bond prices are determined by the time to maturity and two factors, the long-term interest rate and the spread (difference between the long-term rate and the short-term (instantaneous) riskless rate). Several new measures of ``generalized duration" are p...

  13. The Exposure of Mortgage Borrowers to Interest Rate Risk, Income Risk and House Price Risk – Evidence from Swiss Loan Application Data

    OpenAIRE

    Guin, Benjamin; Brown, Martin

    2015-01-01

    We study the exposure of mortgage borrowers in Switzerland to interest rate, income and house price risks and examine how the households’ choice of risky mortgages is related to individual interest rate expectations and risk-aversion. Our analysis is based on a unique data set of household mortgage applications from September 2012 until January 2014. Our assessment of risk exposure among mortgage borrowers in Switzerland is highly sensitive to the underlying assumptions on mortgage costs, hou...

  14. Discount rates in risk versus money and money versus money tradeoffs.

    Science.gov (United States)

    Alberini, Anna; Chiabai, Aline

    2007-04-01

    We use data from a survey of residents of five Italian cities conducted in late spring 2004 to estimate the discount rates implicit in (1) money versus future risk reductions and (2) money versus money tradeoffs. We find that the mean personal discount rate is 0.3-1.7% in (1) and 8.7% in (2). The latter is lower than the discount rates estimated in comparable situations in many recent studies, greater than market interest rates in Italy at the time, and exhibits modest variation with age and gender. The discount rate implicit in money versus risk tradeoffs is within the range of estimates from studies in the United States and Europe, and does not depend on observable individual characteristics. We use split samples to investigate whether a completely abstract risk reduction - one where the risk reduction delivery has been stripped of all specifics, so that respondents should focus on the risks without being distracted by details - results in WTP and discount figures comparable to those from an identified delivery mechanism (a medical test). We find that while WTP for an immediate risk reduction is 42-73% higher with the abstract risk reduction, the discount rate in the money versus risk tradeoffs and the variance of the error term in the WTP equation are the same across the two variants of the questionnaire.

  15. Cash Flow and Discount Rate Risk in Up and Down Markets: What is actually priced?

    NARCIS (Netherlands)

    Botshekan, M.; Kraeussl, R.G.W.; Lucas, A.

    2012-01-01

    We test whether asymmetric preferences for losses versus gains affect the prices of cash flow versus discount rate risk. We construct a return decomposition distinguishing cash flow and discount rate betas in up and down markets. Using U.S. data, we find that downside cash flow and discount rate

  16. [C-section rate in low-risk women: a useful indicator to compare hospitals attending deliveries with different risks].

    Science.gov (United States)

    Librero, Julián; Peiró, Salvador; Belda, Ana; Calabuig, Julia

    2014-01-01

    the C-section rate has been criticized as a performance indicator for not considering that different hospitals manage deliveries with diverse risks. In this work we explore the characteristics of a new indicator restricted to low C-section risk deliveries. retrospective cohort of all births (n=214,611) in all public hospitals during 2005-2010 in the Valencia Region, Spain (source: minimum basic dataset). A low-risk subpopulation consisting of women under-35, no history of c-section, between 37 and 41 gestational weeks, and with a single fetus, with cephalic presentation and normal weight (2500-3999 g) was constructed. We analyzed variability in the new indicator, its correlation with the crude indicator and, using multilevel logistic regression models, the presence of residual risks. a total of 117 589 births (58.4% of the whole deliveries) were identified as low C-section risk. The c-section rate in these women was 11.9% (24.4% for all deliveries) ranging between hospitals from 7.0% to 28.9%. The c-section rate in low-risk and total deliveries correlated strongly (r=0.88). The remaining risks in the population of low risk did not alter the hospital effect on the c-section rate. the percentage of C-section in low risk women include a high volume of deliveries, correlated with the crude indicator and residual risks are not differentially influenced by hospitals, being a useful indicator for monitoring the quality of obstetric care in the National Health System.

  17. Information Acquisition and Excessive Risk: Impact of Policy Rate and Market Volatility

    Directory of Open Access Journals (Sweden)

    Volha Audzei

    2015-12-01

    Full Text Available Excessive risk-taking of financial agents drew a lot of attention in the aftermath of the financial crisis. Low interest rates and subdued market volatility during the Great Moderation are sometimes blamed for stimulating risk-taking and leading to the recent financial crisis. In recent years, with many central banks around the world conducting the policy of low interest rates and mitigating market risks, it has been debatable whether this policy contributes to the building up of another credit boom. This paper addresses this issue by focusing on information acquisition by the financial agents. We build a theoretical model which captures excessive risk taking in response to changes in policy rate and market volatility. This excessive risk takes the form of an increased risk appetite of the agents, but also of decreased incentives to acquire information about risky assets. As a result, with market risk being reduced, agents tend to acquire more risk in their portfolios then they would with the higher market risk. The same forces increase portfolio risk when the safe interest rate is falling. The robustness of the results is considered with different learning rules.

  18. Changes in the sense of agency during hypnosis: The Hungarian version of the Sense of Agency Rating Scale (SOARS-HU) and its relationship with phenomenological aspects of consciousness.

    Science.gov (United States)

    Költő, András; Polito, Vince

    2017-03-01

    Changes in the sense of agency are defining feature of hypnosis. The Sense of Agency Rating Scale (SOARS) is a 10-item questionnaire, administered after a hypnosis session to assess alteration in the sense of agency. In the present study, a Hungarian version of the measure (SOARS-HU) is presented. The SOARS-HU and the Phenomenology of Consciousness Inventory (PCI) were administered to 197 subjects following hypnotizability screening with the Harvard Group Scale of Hypnotic Susceptibility Scale, Form A (HGSHS:A). Confirmatory factor analysis and correlations with hypnotizability demonstrate the reliability and validity of the SOARS-HU. Changes in the Involuntariness and Effortlessness subscales of the SOARS-HU were associated with alterations in subjective conscious experience, as measured by the PCI. These changes in subjective experience remained significant after controlling for HGSHS:A scores. These results indicate that changes in the sense of agency during hypnosis are associated with alterations of consciousness that are independent of hypnotizability. Copyright © 2017 Elsevier Inc. All rights reserved.

  19. The impact of item order on ratings of cancer risk perception.

    Science.gov (United States)

    Taylor, Kathryn L; Shelby, Rebecca A; Schwartz, Marc D; Ackerman, Josh; LaSalle, V Holland; Gelmann, Edward P; McGuire, Colleen

    2002-07-01

    Although perceived risk is central to most theories of health behavior, there is little consensus on its measurement with regard to item wording, response set, or the number of items to include. In a methodological assessment of perceived risk, we assessed the impact of changing the order of three commonly used perceived risk items: quantitative personal risk, quantitative population risk, and comparative risk. Participants were 432 men and women enrolled in an ancillary study of the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Three groups of consecutively enrolled participants responded to the three items in one of three question orders. Results indicated that item order was related to the perceived risk ratings of both ovarian (P Perceptions of risk were significantly lower when the comparative rating was made first. The findings suggest that compelling participants to consider their own risk relative to the risk of others results in lower ratings of perceived risk. Although the use of multiple items may provide more information than when only a single method is used, different conclusions may be reached depending on the context in which an item is assessed.

  20. 34 CFR 222.40 - How does a local educational agency select a local contribution rate based on generally...

    Science.gov (United States)

    2010-07-01

    ..., DEPARTMENT OF EDUCATION IMPACT AID PROGRAMS Payments for Federally Connected Children Under Section 8003(b..., size, location, or a combination of these factors, (that is, in the case of the significantly impacted... 34 Education 1 2010-07-01 2010-07-01 false How does a local educational agency select a local...

  1. 12 CFR 615.5182 - Interest rate risk management by associations and other Farm Credit System institutions other...

    Science.gov (United States)

    2010-01-01

    ... 12 Banks and Banking 6 2010-01-01 2010-01-01 false Interest rate risk management by associations... OPERATIONS, AND FUNDING OPERATIONS Risk Assessment and Management § 615.5182 Interest rate risk management by... shall comply with the requirements of §§ 615.5180 and 615.5181. The interest rate risk management...

  2. The association between social networks and self-rated risk of HIV ...

    African Journals Online (AJOL)

    Elizabeth J. Lyimo

    2014-03-18

    Mar 18, 2014 ... Bonding networks were defined as social groupings of students participating in activities ... bridging social networks and self-rated HIV risk behavior. ...... book for Theory and Research for the Sociology of Education, 241–258.

  3. Explore the Application of Financial Engineering in the Management of Exchange Rate Risk

    Directory of Open Access Journals (Sweden)

    Yang Liu

    2015-01-01

    Full Text Available In the background where the domestic enterprises commonly have a weak protection consciousness against the exchange rate risk, this article makes a deep analysis based on the definition of exchange rate risk and its cause. By comparison of the traditional management method of exchange rate risk with another one based on financial engineering tools, it also deeply analyzes the method to use the financial engineering technology in the management of exchange rate risk, and concludes the primary purpose of exchange rate risk management is for hedging. This article proposes an optimal analysis method in two aspects, namely the minimum risk and maximum efficiency, for the forward-based optimal hedging, and proposes an optimal analysis method of dynamic hedging for the optimal hedging of option-based tools. Based on the description of the application of financial tools in foreign exchange futures, forward contract, currency exchange and foreign exchange option, it makes an empirical analysis on the management of foreign exchange risk by taking an assumed T company as the carrier and based on the trading tools of forward foreign exchange and currency option, which describes the operation procedure of financial tools in a more direct way and proves the efficiency of the optimal analysis method of this article.

  4. Concordance of Motion Sensor and Clinician-Rated Fall Risk Scores in Older Adults.

    Science.gov (United States)

    Elledge, Julie

    2017-12-01

    As the older adult population in the United States continues to grow, developing reliable, valid, and practical methods for identifying fall risk is a high priority. Falls are prevalent in older adults and contribute significantly to morbidity and mortality rates and rising health costs. Identifying at-risk older adults and intervening in a timely manner can reduce falls. Conventional fall risk assessment tools require a health professional trained in the use of each tool for administration and interpretation. Motion sensor technology, which uses three-dimensional cameras to measure patient movements, is promising for assessing older adults' fall risk because it could eliminate or reduce the need for provider oversight. The purpose of this study was to assess the concordance of fall risk scores as measured by a motion sensor device, the OmniVR Virtual Rehabilitation System, with clinician-rated fall risk scores in older adult outpatients undergoing physical rehabilitation. Three standardized fall risk assessments were administered by the OmniVR and by a clinician. Validity of the OmniVR was assessed by measuring the concordance between the two assessment methods. Stability of the OmniVR fall risk ratings was assessed by measuring test-retest reliability. The OmniVR scores showed high concordance with the clinician-rated scores and high stability over time, demonstrating comparability with provider measurements.

  5. [Relationship between performance rating and risk of low back pain in manufacturing line workers].

    Science.gov (United States)

    Higuchi, Yoshiyuki; Funahashi, Atsushi; Izumi, Hiroyuki; Kumashinro, Masaharu

    2012-03-01

    It is possible that the performance rating of line workers is affected by the risk factors for musculoskeletal disorders that are included in their work more so than by the actual takt time. To investigate whether performance rating relates to the risk factors for musculoskeletal disorders, we analyzed a dataset obtained from a self-administered questionnaire answered by assembly line workers (n=1579). As a result, performance rating had a significant association with unsuitable work environments, poor working postures and handling of heavy loads. The workers who reported the fastest rating had a higher exposure than others to the risk factors for occupational low back pain. The results of our study support the effectiveness of performance rating as an index of work burden.

  6. PERCEIVED RISK, PRICE AND ONLINE TRAVEL AGENCIES: DOES PRICE ALWAYS MATTER?

    Directory of Open Access Journals (Sweden)

    Patricea Elena BERTEA

    2011-01-01

    Full Text Available The present study analyzes the influence of price level in the case of onlineshopping for travel services. The methodology used is a quasi experimentdeveloped in the online environment. The analysis is made within groups andfollows three scenarios which depend on the level of brand awareness.Inside each scenario price takes two levels: similar to competition andsmaller than competition. Results show that price does not have an influenceon all types of perceived risk and that its influence depends also on the brandawareness component.

  7. Differences Across Levels in the Language of Agency and Ability in Rating Scales for Large-Scale Second Language Writing Assessments

    OpenAIRE

    Anderson Salena Sampson

    2017-01-01

    While large-scale language and writing assessments benefit from a wealth of literature on the reliability and validity of specific tests and rating procedures, there is comparatively less literature that explores the specific language of second language writing rubrics. This paper provides an analysis of the language of performance descriptors for the public versions of the TOEFL and IELTS writing assessment rubrics, with a focus on linguistic agency encoded by agentive verbs and language of ...

  8. DRAFT DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CHEROKEE COUNTY, SC

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  9. Digital Flood Insurance Rate Map Database, Buchanan County, Iowa, USA

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  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FLEMING COUNTY, KY

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  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Charles COUNTY, MD, USA

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  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BUTLER COUNTY, NE

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  13. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SACRAMENTO COUNTY, CALIFORNIA, USA

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  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CITY OF SACRAMENTO, CALIFORNIA

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  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HONOLULU COUNTY, HI, USA

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  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, KAUAI COUNTY, HAWAII, USA

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  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SARPY COUNTY, USA

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  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LUCAS COUNTY, OHIO

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  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, NASSAU COUNTY, NEW YORK

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  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HARDIN COUNTY, TX

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  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SULLIVAN COUNTY, NEW YORK

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  2. Digital Flood Insurance Rate Map Database, PRINCE GEORGE, VA, USA

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  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SHELBY COUNTY, OHIO, USA

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  4. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WAGONER COUNTY, OKLAHOMA, USA

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  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SUFFOLK COUNTY, MASSACHUSETTS

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  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FAIRFIELD COUNTY, CONNECTICUT

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  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE ROCKLAND COUNTY, NY, USA

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  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, OTTAWA COUNTY, OHIO, USA

    Data.gov (United States)

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  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SAUNDERS COUNTY, NEBRASKA

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  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RED WILLOW COUNTY, NEBRASKA

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  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CHEROKEE COUNTY, KANSAS

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  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, POLK COUNTY, NEBRASKA

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  13. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HARLAN COUNTY, NEBRASKA

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  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RENO COUNTY, KANSAS

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  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE FOR HOWARD COUNTY, NEBRASKA

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  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FURNAS COUNTY, NEBRASKA

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  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LANCASTER COUNTY, NE, USA

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  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ALLAMAKEE COUNTY, IOWA

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  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CASS COUNTY, NEBRASKA

    Data.gov (United States)

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  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MCPHERSON COUNTY, KANSAS

    Data.gov (United States)

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  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DAWES COUNTY, NEBRASKA

    Data.gov (United States)

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  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, VALLEY COUNTY, NEBRASKA

    Data.gov (United States)

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  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ELLSWORTH COUNTY, KANSAS

    Data.gov (United States)

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  4. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SHERMAN COUNTY, NEBRASKA

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  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HARVEY COUNTY, KANSAS

    Data.gov (United States)

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  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, PLATTE COUNTY, NEBRASKA

    Data.gov (United States)

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  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, COLFAX COUNTY, NEBRASKA

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  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, THURSTON COUNTY, NEBRASKA

    Data.gov (United States)

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  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, TAMA COUNTY, IOWA

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  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WEBSTER COUNTY, NEBRASKA

    Data.gov (United States)

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  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Eddy County, NM

    Data.gov (United States)

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  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RAY COUNTY, MISSOURI, USA

    Data.gov (United States)

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  13. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, JEFFERSON COUNTY, IDAHO, USA

    Data.gov (United States)

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  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LAWRENCE COUNTY, OHIO, USA

    Data.gov (United States)

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  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GRANT COUNTY, WISCONSIN, USA

    Data.gov (United States)

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  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SEBASTIAN COUNTY, AR

    Data.gov (United States)

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  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SEBASTIAN COUNTY, ARKANSAS

    Data.gov (United States)

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  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FERGUS COUNTY, MONTANA, USA

    Data.gov (United States)

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  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BONNER COUNTY, IDAHO

    Data.gov (United States)

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  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SAN JOAQUIN COUNTY, CALIFORNIA

    Data.gov (United States)

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  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LORAIN COUNTY, OHIO USA

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  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ROBERTSON COUNTY, KY

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  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, COSHOCTON COUNTY, OHIO, USA

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  4. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, NEWTON COUNTY, MISSOURI, USA

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  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CHEROKEE COUNTY, TX

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  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HAMILTON COUNTY, OHIO, USA

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  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GRANT COUNTY, KY

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  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ESSEX COUNTY, MA

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  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CARROLL COUNTY, GEORGIA, USA

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  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DOUGLAS COUNTY, ILLINOIS USA

    Data.gov (United States)

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  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Douglas County, Oregon, USA

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  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LINCOLN COUNTY, ARKANSAS, USA

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  13. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, POWELL COUNTY, KY

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  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, COLFAX COUNTY, New Mexico

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  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Winston COUNTY, AL

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  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CONVERSE COUNTY, WYOMING, USA.

    Data.gov (United States)

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  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Dougherty County, GA

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  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, POLK COUNTY, TX

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  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HUNTERDON CO., NJ

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  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SEDGWICK COUNTY, KANSAS, USA

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  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FINNEY COUNTY, USA

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  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CULLMAN COUNTY, AL

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  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, JOHNSON COUNTY, GEORGIA, USA

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  4. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Northumberland County, VA, USA

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  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CADDO PARISH, LOUISIANA, USA

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  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ETOWAH COUNTY, AL

    Data.gov (United States)

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  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FORT BEND COUNTY, TEXAS

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  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LACLEDE COUNTY, MISSOURI, USA

    Data.gov (United States)

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  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CLINTON COUNTY, MISSOURI, USA

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  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MCDONALD COUNTY, USA

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  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MERCER COUNTY, KY

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  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, AUGUSTA COUNTY, VA, USA

    Data.gov (United States)

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  13. Digital Flood Insurance Rate Map Database, Crawford County, PA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WARREN COUNTY, OH, USA

    Data.gov (United States)

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  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BATH COUNTY, KY

    Data.gov (United States)

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  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Spartanburg County, South Carolina

    Data.gov (United States)

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  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Douglas COUNTY, Nevada

    Data.gov (United States)

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  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Rio Grande County, Colorado

    Data.gov (United States)

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  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Elbert County, Colorado

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, JASPER COUNTY, TX

    Data.gov (United States)

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  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Roosevelt COUNTY, New Mexico

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Linn County, Oregon, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, TEHAMA COUNTY, CALIFORNIA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  4. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Wythe County, VA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SULLIVAN COUNTY, PA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Cleburne COUNTY, AL

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, KITSAP COUNTY, WASHINGTON, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE,CAMDEN COUNTY, GEORGIA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MENDOCINO COUNTY, CALIFORNIA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, APPLING COUNTY, GEORGIA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Wilcox COUNTY, AL

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WASHINGTON COUNTY, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  13. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BALLARD COUNTY, KY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HARRISON COUNTY, KY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, PASCO COUNTY, FLORIDA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GILMER COUNTY, GEORGIA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MIAMI - DADE COUNTY, FLORIDA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WALKER COUNTY, TX

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WALKER COUNTY, AL

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WALKER COUNTY, GEORGIA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BENTON COUNTY, MINNESOTA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DAVIESS COUNTY, KY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MONROE COUNTY, GEORGIA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

  4. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HENRY COUNTY, GEORGIA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MARLBORO COUNTY, SC

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  6. FINAL DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GREENWOOD COUNTY, SC

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RICE COUNTY, MINNESOTA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CHRISTIAN COUNTY, KY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CHRISTIAN COUNTY, ILLINOIS USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SHELBY COUNTY, IA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, POTTAWATTAMIE COUNTY, IOWA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MITCHELL COUNTY, IOWA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

  13. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WARREN COUNTY, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CLAYTON COUNTY, IOWA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HOWARD COUNTY, IOWA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

  16. DIGITAL FLOOD INSURANCE RATE MAP DATABAES, LA PAZ COUNTY, AZ

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SEWARD COUNTY, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SCOTT COUNTY, KY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, NEWTON COUNTY, GEORGIA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, NEWTON COUNTY, GEORGIA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MIDDLESEX, VA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, KARNES COUNTY, TEXAS, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, VOLUSIA COUNTY, FL, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  4. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Marshall COUNTY, AL

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  5. DRAFT DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HEMPSTEAD COUNTY, AR

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, TOM GREEN COUNTY, TEXAS

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Berks County, Pennsylvania, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, STONE COUNTY, MISSOURI, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, VAL VERDE COUNTY, TEXAS

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  10. Digital Flood Insurance Rate Map Database, Richmond County, Virginia, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WASATCH COUNTY, UTAH, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  12. Digital Flood Insurance Rate Map Database, Westmoreland County, Virginia, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  13. Flood Insurance Rate Map Database, Kent County, Delaware, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SHELBY COUNTY, KENTUCKY, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MCCRACKEN COUNTY, KY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE,GRAVES COUNTY, KY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LYON COUNTY, KY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WOLFE COUNTY, KY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WEBSTER COUNTY, KY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HAWAII COUNTY, HAWAII, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MCINTOSH COUNTY, GEORGIA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HART COUNTY, KY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, OSCEOLA COUNTY, FL

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  4. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ELLIOTT COUNTY, KY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GAGE COUNTY, NEBRASKA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CLARK COUNTY, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ALLEN COUNTY, INDIANA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ANGELINA COUNTY, TX

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DOUGLAS COUNTY, NEBRASKA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, NEWPORT COUNTY, RHODE ISLAND

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ATASCOSA COUNTY, TEXAS

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DOUGLAS COUNTY, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  13. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, POLK COUNTY, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MARION COUNTY, KY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LEBANON COUNTY, PENNSYLVANIA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CRAWFORD COUNTY, AR ,USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SOLANO COUNTY, CALIFORNIA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Mitchell County, GA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, TAYLOR COUNTY, FL, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GRIMES COUNTY, TX

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  1. Digital Flood Insurance Rate Map Database, Allegheny County, Pennsylvania, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ST. LOUIS, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DELAWARE COUNTY, OK, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  4. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, UNION COUNTY, FLORIDA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LEE COUNTY, FLORIDA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HAMILTON COUNTY, FLORIDA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WAYNE COUNTY, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Jefferson COUNTY, AL

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WALTON COUNTY, FL, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Kenton COUNTY, Kentucky

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RUSSELL COUNTY, KY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  12. DRAFT DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LANCASTER COUNTY, SC

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  13. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CHAMBERS COUNTY, TEXAS

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CHATHAM COUNTY, GEORGIA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HILLSBOROUGH COUNTY, FLORIDA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WALLER COUNTY, TX

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CARBON COUNTY, UTAH

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Liberty County, TX

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SAN JACINTO COUNTY, TX

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, New London County, CT

    Data.gov (United States)

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  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Westmoreland County, PA, USA

    Data.gov (United States)

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  2. Digital Flood Insurance Rate Map Database, Sussex County, Delaware, USA

    Data.gov (United States)

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  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, TYLER COUNTY, TX

    Data.gov (United States)

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  4. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Stafford County , VIRGINIA

    Data.gov (United States)

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  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SUMNER COUNTY, USA

    Data.gov (United States)

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  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GREENVILLE COUNTY, SOUTH CAROLINA

    Data.gov (United States)

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  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DICKENSON COUNTY, VA, USA

    Data.gov (United States)

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  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HOUSTON COUNTY, TX

    Data.gov (United States)

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  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DESOTO COUNTY, FL, USA

    Data.gov (United States)

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  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FANNIN COUNTY, GEORGIA, USA

    Data.gov (United States)

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  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ST. FRANCOIS COUNTY, USA

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  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LAFAYETTE COUNTY, MISSOURI, USA

    Data.gov (United States)

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  13. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RANDALL COUNTY, TX, USA

    Data.gov (United States)

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  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, PEMBINA COUNTY, USA

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  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MCLEAN COUNTY, KY

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  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RUSK COUNTY, TX

    Data.gov (United States)

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  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Nelson County, VA, USA

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  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CHEROKEE COUNTY, GEORGIA, USA

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  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, NELSON COUNTY, KY

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  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MIDDLESEX COUNTY, MASSACHUSETTS

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  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ESCAMBIA COUNTY, AL

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  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Baldwin COUNTY, AL

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  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BARTOW COUNTY, GEORGIA, USA

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  4. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ALPENA COUNTY, MI

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  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CALDWELL PARISH, LOUISIANA, USA

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  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SHIAWASSEE COUNTY, MICHIGAN, USA

    Data.gov (United States)

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  7. Digital Flood Insurance Rate Map for Vermillion County, IN

    Data.gov (United States)

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  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, EL DORADO COUNTY, CALIFORNIA

    Data.gov (United States)

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  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GADSDEN COUNTY, FL, USA

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  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MARION COUNTY, FLORIDA

    Data.gov (United States)

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  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SHELBY COUNTY, AL

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  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Harris COUNTY, TX

    Data.gov (United States)

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  13. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, PIKE COUNTY, AL

    Data.gov (United States)

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  14. Digital Flood Insurance Rate Map Database, Bradford County, Pennsylvania, USA

    Data.gov (United States)

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  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, JOHNSON COUNTY, KY

    Data.gov (United States)

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  16. Digital Flood Insurance Rate Map Database, Charles County, Maryland, USA

    Data.gov (United States)

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  17. Digital Flood Insurance Rate Map Database, Essex County, Virginia, USA

    Data.gov (United States)

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  18. Digital Flood Insurance Rate Map Database, Calvert County, Maryland, USA

    Data.gov (United States)

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  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, COBB COUNTY, GA, USA

    Data.gov (United States)

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  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MATHEWS COUNTY, VIRGINIA

    Data.gov (United States)

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  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HOLMES COUNTY, OHIO

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  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HOLMES COUNTY, USA

    Data.gov (United States)

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  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, KOOTENAI COUNTY, USA

    Data.gov (United States)

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  4. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Accomack County, VIRGINIA

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  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CLARKE COUNTY, GEORGIA, USA

    Data.gov (United States)

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  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LYCOMING COUNTY, PENNSYLVANIA

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  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WHATCOM COUNTY, WASHINGTON

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  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HARRISON COUNTY, TEXAS

    Data.gov (United States)

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  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DELTA COUNTY, COLORADO, USA

    Data.gov (United States)

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  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GULF COUNTY, FLORIDA, USA

    Data.gov (United States)

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  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Delaware County, Pennsylvania, USA

    Data.gov (United States)

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  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HALL COUNTY, NE, USA

    Data.gov (United States)

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  13. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, NORFOLK COUNTY, MASSACHUSETTS

    Data.gov (United States)

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  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, COWLEY COUNTY, USA

    Data.gov (United States)

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  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, TALBOT, MARYLAND, USA

    Data.gov (United States)

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  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, NANTUCKET COUNTY, MASSACHUSETTS

    Data.gov (United States)

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  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, PATRICK COUNTY, VA, USA

    Data.gov (United States)

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  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RANDOLPH COUNTY, WV, USA

    Data.gov (United States)

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  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GRAYSON COUNTY, VA, USA

    Data.gov (United States)

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  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CHESTERFIELD, VA, USA

    Data.gov (United States)

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  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SURRY COUNTY, VA, USA

    Data.gov (United States)

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  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WORCESTER COUNTY, MASSACHUSETTS

    Data.gov (United States)

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  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Buckingham County, VA, USA

    Data.gov (United States)

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  4. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GARRETT COUNTY, Maryland, USA

    Data.gov (United States)

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  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, OTTAWA COUNTY, USA

    Data.gov (United States)

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  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RALEIGH COUNTY, WV, USA

    Data.gov (United States)

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  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Essex County, VA, USA

    Data.gov (United States)

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  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GRAND COUNTY, USA

    Data.gov (United States)

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  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Caroline COUNTY, Maryland, USA

    Data.gov (United States)

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  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, TUCKER COUNTY, WV, USA

    Data.gov (United States)

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  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Sussex County, VA, USA

    Data.gov (United States)

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  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WESTMORELAND COUNTY, VA, USA

    Data.gov (United States)

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  13. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FLUVANNA COUNTY, VA, USA

    Data.gov (United States)

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  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Richmond County, VA, USA

    Data.gov (United States)

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  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Pulaski County, VA, USA

    Data.gov (United States)

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  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Scott County, VA, USA

    Data.gov (United States)

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  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DILLON COUNTY, USA

    Data.gov (United States)

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  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Upshur County, WV, USA

    Data.gov (United States)

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  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ALLEN COUNTY, USA

    Data.gov (United States)

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  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, LINN COUNTY, IA, USA

    Data.gov (United States)

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  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CAROLINE COUNTY, VA, USA

    Data.gov (United States)

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  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BANDERA COUNTY, TEXAS

    Data.gov (United States)

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  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Washington COUNTY, NE

    Data.gov (United States)

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  4. Digital Flood Insurance Rate Map Database, Mercer County, PA

    Data.gov (United States)

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  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ST JOSEPH COUNTY, MI

    Data.gov (United States)

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  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SHERBURNE COUNTY, MINNESOTA, USA

    Data.gov (United States)

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  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, DUKES COUNTY, MA

    Data.gov (United States)

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  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Terrell County, GA

    Data.gov (United States)

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  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GLOUCESTER, VA, USA

    Data.gov (United States)

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  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WORCESTER COUNTY, MA

    Data.gov (United States)

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  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SONOMA COUNTY, CALIFORNIA

    Data.gov (United States)

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  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MONMOUTH COUNTY, NEW JERSEY

    Data.gov (United States)

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  13. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, YORK COUNTY, PA, USA

    Data.gov (United States)

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  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BENTON COUNTY, ARKANSAS

    Data.gov (United States)

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  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GORDON COUNTY, GEORGIA

    Data.gov (United States)

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  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SUSSEX COUNTY, NEW JERSEY

    Data.gov (United States)

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  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MARIN COUNTY, CALIFORNIA

    Data.gov (United States)

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  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CLEARFIELD COUNTY, PA, USA

    Data.gov (United States)

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  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, COOPER COUNTY, MISSOURI, USA

    Data.gov (United States)

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  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CAMERON COUNTY, PA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BOYLE COUNTY, KY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, WARREN COUNTY, NEW JERSEY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FAYETTE COUNTY, GEORGIA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk Information And supporting data used to develop the risk data. The primary risk;...

  4. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SUFFOLK COUNTY, NEW YORK

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Bell COUNTY, Kentucky

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BATH COUNTY, VIRGINIA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, INDIAN RIVER COUNTY, FL

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SIMPSON COUNTY, KY

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Cherokee COUNTY, AL

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, JACKSON COUNTY, AL

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Lancaster County, VA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BEDFORD COUNTY, VA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  13. DRAFT DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HONOLULU COUNTY, HI

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MAYES COUNTY, OK

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  15. DRAFT DIGITAL FLOOD INSURANCE RATE MAP DATABASE, NEWBERRY COUNTY, SC

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GREENE COUNTY, GEORGIA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, FRANKLIN COUNTY, VA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HIGHLAND COUNTY, VIRGINIA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SUMTER COUNTY, AL

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, GRADY COUNTY, OKLAHOMA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  1. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SHASTA COUNTY, CALIFORNIA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  2. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HOWELL COUNTY, MISSOURI, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  3. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SISKIYOU COUNTY, CALIFORNIA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  4. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, YOLO COUNTY, CALIFORNIA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  5. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, PLUMAS COUNTY, CALIFORNIA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  6. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, ORANGE COUNTY, CALIFORNIA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  7. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RIVERSIDE COUNTY, CALIFORNIA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  8. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, Tuolumne County, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  9. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, PIMA COUNTY, ARIZONA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  10. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, COCHISE COUNTY, ARIZONA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  11. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MADERA COUNTY, CALIFORNIA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  12. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, TEHAMA COUNTY, CALIFORNIA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  13. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, YUMA COUNTY, ARIZONA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  14. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, SACRAMENTO COUNTY, CALIFORNIA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  15. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, BUTTE COUNTY, CALIFORNIA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  16. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, CLATSOP COUNTY, OR, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  17. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HENRY COUNTY, VA, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  18. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, RALLS COUNTY, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  19. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, MARION COUNTY, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...

  20. DIGITAL FLOOD INSURANCE RATE MAP DATABASE, HOUSTON COUNTY, Georgia

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk...