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

Principal Investigator(s): View help for Principal Investigator(s) Justin Gallagher

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Project Citation:

Gallagher, Justin. Replication data for: Learning about an Infrequent Event: Evidence from Flood Insurance Take-Up in the United States. Nashville, TN: American Economic Association [publisher], 2014. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2019-10-12. https://doi.org/10.3886/E113898V1

Project Description

Summary: 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.

Scope of Project

JEL Classification:
      D12 Consumer Economics: Empirical Analysis
      D83 Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
      D84 Expectations; Speculations
      G22 Insurance; Insurance Companies; Actuarial Studies
      Q54 Climate; Natural Disasters and Their Management; Global Warming

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V1 [2019-10-12]

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