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RESEARCHER SPOTLIGHT
Carolyn Kousky
Kousky describes her research on how risk is managed in natural catastrophes and other extreme events.
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Related Subtopics: Risk Analysis

Who’s Benefiting from the National Flood Insurance Program?

RFF Feature
March 29, 2011

The National Flood Insurance Program (NFIP) has been the subject of renewed interest since the unprecedented losses of the 2005 hurricane season sent it deeply into debt. The program, run by the Federal Emergency Management Agency (FEMA), provides flood insurance to residents of communities that adopt basic floodplain management policies. Reform options are currently being evaluated by both FEMA and Congress as the NFIP is operating under an extension that will expire September 30.

As Congress keeps one eye on deficits and another on warming temperatures and melting snowpack, debate is emerging over who benefits and who bears the costs of this program. Of particular interest is a fairness question – does the program end up subsidizing households in wealthier counties?

In a new RFF Discussion Paper, “Redistributional Effects of the National Flood Insurance Program,” authors Okmyung Bin, John A. Bishop, and Carolyn Kousky analyze more than 25 years of NFIP premium and claims data to determine how the program’s price and payouts correlate to per-capita county income.

They find, broadly, that the program has spread costs and benefits fairly uniformly across county income levels. “We measure progressivity as the departure of total county premiums and program payouts from per capita county income proportionality,” the authors write. “We find that NFIP premiums are weakly regressive on an annual basis but become proportional as the time horizon is extended beyond a single year. In contrast, we find that NFIP claim payments are moderately progressive over all time horizons studied. In sum, we find no evidence that the NFIP disproportionally advantages richer counties.” The authors caution, however, that looking at only 25 years of data for a low-probability risks can bias results as payouts are strongly driven by whether the worst storms happen to hit low or high income areas.

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