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Replication data for: Learning about an Infrequent Event: Evidence from Flood Insurance Take-Up in the United States

Version
1
Resource Type
Dataset
Creator
  • Gallagher, Justin
Publication Date
2013-12-30
Description
  • Abstract

    I examine the learning process that economic agents use to update their expectation of an uncertain and infrequently observed event. I use a new nation-wide panel dataset of large regional floods and flood insurance policies to show that insurance take-up spikes the year after a flood and then steadily declines to baseline. Residents in nonflooded communities in the same television media market increase take-up at one-third the rate of flooded communities. I find that insurance take-up is most consistent with a Bayesian learning model that allows for forgetting or incomplete information about past floods.
Availability
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Relations
  • Is supplemented by
    DOI: 10.1257/app.6.3.206 (Text)
Publications
  • Gallagher, Justin. “Learning about an Infrequent Event: Evidence from Flood Insurance Take-Up in the United States.” American Economic Journal: Applied Economics 6, no. 3 (July 2014): 206–33. https://doi.org/10.1257/app.6.3.206.
    • ID: 10.1257/app.6.3.206 (DOI)

Update Metadata: 2019-10-12 | Issue Number: 1 | Registration Date: 2019-10-12

Gallagher, Justin (2013): Replication data for: Learning about an Infrequent Event: Evidence from Flood Insurance Take-Up in the United States. Version: 1. ICPSR - Interuniversity Consortium for Political and Social Research. Dataset. http://doi.org/10.3886/E113898V1