Jump to ContentJump to Main Navigation
Show Summary Details
More options …

The B.E. Journal of Economic Analysis & Policy

Editor-in-Chief: Jürges, Hendrik / Ludwig, Sandra

Ed. by Auriol , Emmanuelle / Brunner, Johann / Fleck, Robert / Mendola, Mariapia / Requate, Till / Schirle, Tammy / de Vries, Frans / Zulehner, Christine

4 Issues per year


IMPACT FACTOR 2016: 0.252
5-year IMPACT FACTOR: 0.755

CiteScore 2016: 0.48

SCImago Journal Rank (SJR) 2016: 0.330
Source Normalized Impact per Paper (SNIP) 2016: 0.526

Online
ISSN
1935-1682
See all formats and pricing
More options …
Ahead of print

Issues

Volume 6 (2006)

Volume 4 (2004)

Volume 2 (2002)

Volume 1 (2001)

Does the National Flood Insurance Program Have Redistributional Effects?

Okmyung Bin
  • Corresponding author
  • Department of Economics, East Carolina University, Brewster A-427, Greenville, NC 27858-4353, USA
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ John Bishop
  • Department of Economics, East Carolina University, Brewster A-427, Greenville, NC 27858-4353, USA
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Carolyn Kousky
  • Risk Management and Decision Processes Center, Wharton School, University of Pennsylvania, Philadelphia, PA 19104, USA
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2017-09-01 | DOI: https://doi.org/10.1515/bejeap-2016-0321

Abstract

This study examines possible redistributional effects of the National Flood Insurance Program (NFIP), using a nationwide database of flood insurance policies and claims between 2001 and 2013 from the Federal Emergency Management Agency. Applying methods from the tax and transfer progressivity literature, we use the departure from per capita income proportionality at the zip code level as our measure of progressivity. Our findings indicate that premiums as a percentage of coverage purchased are regressive: premium shares are larger than income shares for lower-income zip codes. Payouts, however, also as a percentage of coverage purchased, are progressive, meaning lower-income zip codes receive a larger portion of claims paid. Overall net premiums (premiums – payouts) divided by coverage are also regressive. Our findings are driven by certain aspects of the current rate structure of the NFIP, as well as how income is related to risk. We discuss potential policies to provide assistance to lower-income households in purchasing flood insurance.

Keywords: Gini index; NFIP; redistributive effect; departure from proportionality

JEL Classification: D31; G22; Q54; R38

References

  • Bin, O., J. Bishop, and C. Kousky. 2012. “Redistributional Effects of the National Flood Insurance Program.” Public Finance Review 40 (3):360–380.Google Scholar

  • Bishop, J. A., K. V. Chow, and J. P. Formby. 1994. “A Large Sample Test for Differences between Lorenz and Concentration Curves.” International Economic Review 35:479–488.Google Scholar

  • Bishop, J. A., H. Liu, and B. Zheng. 2010. “Rising Incomes and Nutritional Inequality in China.” Studies in Applied Welfare Analysis: Papers from the Third ECINEQ Meeting. Research on Economic Inequality 18: 257–266.Google Scholar

  • Bump, P. 2014. “You are Subsidizing a Fancy Beach House that Will Be Destroyed in a Flood.” The Atlantic. February 18.Google Scholar

  • Coronado, J., D. Fullerton, and T. Glass. 2011. “The Progressivity of Social Security.” The B.E. Journal of Economic Analysis & Policy 11 (1):1–45.Google Scholar

  • Dixon, L., N. Clancy, B. M. Miller, S. Hoegberg, M. M. Lewis, B. Bener, S. Ebinger, M. Hodges, G. M. Syck, C. Nagy, and S. R. Choquette. 2017. The Cost and Affordability of Flood Insurance in New York City: Economic Impacts of Rising Premiums and Policy Options for One- to Four-Family Homes. Santa Monica, CA: RAND Corporation.Google Scholar

  • Dixon, L., N. Clancy, S. A. Seabury, and A. Overton. 2006. The National Flood Insurance Program’s Market Penetration Rate: Estimates and Policy Implications. Santa Monica, CA: RAND Corporation. February.Google Scholar

  • Gall, M., K. A. Borden, C. T. Emrich, and S. Cutter. 2011. “The Unsustainable Trend of Natural Hazard Losses in the United States.” Sustainability 3:2157–2181.Google Scholar

  • GAO. 2013. Flood Insurance: More Information Needed on Subsidized Properties. Washington, DC: Government Accountability Office. July.Google Scholar

  • Garcia-Diaz, D. 2014. Testimony to the Subcommittee on Housing and Insurance, Committee on Financial Services, House of Representatives. Washington, DC: Government Accountability Office. April 9.Google Scholar

  • Hayes, T. L., and D. A. Neal. 2011. Actuarial Rate Review: In Support of the Recommended October 1, 2011, Rate and Rule Changes. Washington, DC: Federal Emergency Management Agency.Google Scholar

  • Holladay, J. S., and J. A. Schwartz. 2010. Flooding the Market: The Distributional Consequences of the NFIP. New York, NY: Institute for Policy Integrity, New York University School of Law.Google Scholar

  • Kakwani, N. C. 1977. “Measurement of Tax Progressivity: An International Comparison.” Economic Journal 87:71–80.Google Scholar

  • Kousky, C., and H. Kunreuther. 2014. “Addressing Affordability in National Flood Insurance Program.” Journal of Extreme Events 1 (1):1450.Google Scholar

  • Kousky, C., and E. Michel-Kerjan. 2015. “Examining Flood Insurance Claims in the United States.” Journal of Risk and Insurance doi:.CrossrefGoogle Scholar

  • Kousky, C., and L. Shabman. 2014. “Pricing Flood Insurance: How and Why the NFIP Differs from a Private Insurance Company.” RFF Discussion Paper 14-37. Washington, DC: Resources for the Future.Google Scholar

  • Kriesel, W., and C. Landry. 2004. “Participation in the National Flood Insurance Program: An Empirical Analysis for Coastal Properties.” Journal of Risk and Insurance 71 (3):405–420.Google Scholar

  • Lambert, P. J. 2002. The Distribution and Redistribution of Income. Manchester and New York: Manchester University Press.Google Scholar

  • Lerman, R. I., and S. Yitzhaki. 1989. “Improving the Accuracy of Estimates of Gini Coefficients.” Journal of Econometrics 42 (1):43–47.Google Scholar

  • Logue, K. D., and O. Ben-Shahar. 2015. “The Perverse Effects of Subsidized Weather Insurance.” Law & Economics Working Papers. Paper 111.Google Scholar

  • McGuire, C., M. Goodman, and J. Wright. 2015. “Subsidizing Risk: The Regressive and Counterproductive Nature of National Flood Insurance Rate Setting in Massachusetts.” PPC Working Paper Series- Working Paper No. ENV-2015-01.Google Scholar

  • National Research Council (NRC). 2015. Affordability of National Flood Insurance premiums: Report 1. Washington, DC: National Academies Press.Google Scholar

  • New York City. 2013. A Stronger, More Resilient New York. New York City: Special Initiative for Rebuilding and Resiliency.Google Scholar

  • O’Donnell, O., E. Van Doorslaer, A. Wagstaff, and M. Lindelow. 2008. Analyzing Health Equity Using Household Survey Data: A Guide to Techniques and Their Implementation. Washington, DC: World Bank Group.Google Scholar

  • Pociask, S. 2014. “Flood Insurance Welfare for the Rich.” The Daily Caller. February 25.Google Scholar

About the article

Published Online: 2017-09-01


Citation Information: The B.E. Journal of Economic Analysis & Policy, ISSN (Online) 1935-1682, DOI: https://doi.org/10.1515/bejeap-2016-0321.

Export Citation

© 2017 Walter de Gruyter GmbH, Berlin/Boston. Copyright Clearance Center

Comments (0)

Please log in or register to comment.
Log in