Flood Risk Analysis for the National Flood Insurance Program

Author(s):  
Brian R. Mrazik
2021 ◽  
Author(s):  
Konstantinos Papoulakos ◽  
Theano Iliopoulou ◽  
Panayiotis Dimitriadis ◽  
Dimosthenis Tsaknias ◽  
Demetris Koutsoyiannis

<p>During the last decades, scientific research in the field of flood risk management has provided new insights and strong computational tools towards the deeper understanding of the fundamental probabilistic and stochastic behaviour that characterizes such natural hazards. Flood hazards are controlled by hydrometeorological processes and their inherent uncertainties. Historically, a high percentage of flood disasters worldwide are inaccurately or ineffectively reported regarding the aggregated number of the affected people, economic losses and generated flood insurance claims. In this respect, the recently published National Flood Insurance Program (NFIP) data by the Federal Emergency Management Agency (FEMA), including more than two million claims records dating back to 1978 and more than 47 million policy records for transactions, may provide new insights into flood impacts. The aim of this research is to process the actual insurance data derived from this database, in order to detect the underlying patterns and investigate its stochastic structure, paving the way for the development of more accurate flood risk assessment and modelling strategies.</p>


2012 ◽  
Vol 105 ◽  
pp. 64-72 ◽  
Author(s):  
F.L.M. Diermanse ◽  
C.P.M. Geerse

Author(s):  
Niloy Pramanick ◽  
Rituparna Acharyya ◽  
Sandip Mukherjee ◽  
Sudipta Mukherjee ◽  
Indrajit Pal ◽  
...  

Author(s):  
Okmyung Bin ◽  
John Bishop ◽  
Carolyn Kousky

AbstractThis 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.


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