By James P. Howard II
This short provides a benefit-cost research of the nationwide Flood coverage software (NFIP) in addition to an review of its cumulative socioeconomic results. Created by means of Congress in 1968, the NFIP offers flood assurance safeguard to homeowners, in go back for neighborhood executive dedication to sound floodplain administration. on account that 1994, the NFIP has integrated a Flood Mitigation advice (FMA) software to supply neighborhood groups with aid for flood mitigation. This e-book deals quantitative proof of the web social advantage of the NFIP for the years 1996-2010, together with an autonomous review of the patron profit. moment, it presents distributionally weighted research to teach the socioeconomic results of funds and claims. eventually, this short contains an research of the switch in executive profit brought on by the NFIP and FMA courses. The types utilized in each one component to the research are usable via others for extending and revising the research. supplying a accomplished research of this more and more vital federal coverage, this short may be of use to scholars of environmental economics and public coverage in addition to these attracted to threat administration within the period of weather swap.
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Additional resources for Socioeconomic Effects of the National Flood Insurance Program
However, the separate fund hides a large debt of the US government. Hurricane Sandy, which damaged the East and Northeast coasts in late 2012, has exacerbated the problem as the NFIP hit its debt ceiling before Congress raised the limit. This analysis will assume that there is no cost to financing the NFIP’s borrowing, though this is a subject for further study. The effects of the NFIP and FMA programs on government revenues can be considered a kind of distributional analysis focusing on the effects to government.
For example, Fig. 1 shows an area shaded pink, which is the area between the line of equality and a hypothetical observed income distribution. The blue area in the plot is the area under the Lorenz curve. Given the relationship between the Gini coefficient and the Lorenz curve, and the existing selection of group ordering by average income, a weightset based on the Lorenz curve is possible. One such weightset, based on the work of Atkinson (1970), uses income to establish multiple tiers, such as quintile groups, and assigns each tier a weight.
One method might order groups by their respective incomes and relates to the Gini coefficient. The Gini coefficient represents the deviation from an exactly equal distribution of income among a population (Lambert 2001, 27–29). A group where all members received an equal income has a Gini coefficient of zero. The Gini coefficient increases as the disparity in income among members of the group increases. For instance, the counties of the USA could be ordered by their median incomes providing an income distribution curve by geography.