A Bayesian Modeling Approach to Private Preparedness Behavior Against Flood Hazards

Abstract

This study investigates if the hypotheses supporting the Protective Action Decision Model (PADM) are satisfied in a survey involving individuals under risk of river floods in Brazil. Our model improves previous efforts in many ways: (1) it is based on a probabilistic sample, with 1164 individuals interviewed in a city with a large share of the population under risk of river floods; (2) it introduces a hierarchical Bayesian logistic model relating the probability of adopting protective measures against floods to covariates directly measured from individuals, as well as to latent covariates representing risk-aversion and perceptions about the effectiveness (PE) and the opportunity cost (PCO) of those measures; (3) it measures PE and PCO through Bayesian item response theory (IRT) models, appropriately quantifying the uncertainty inherent to such quantities; (4) it includes a random effect reflecting unmeasured individual features to correlate the individual responses to the different protective measures considered. We found that the effect of PCO is small and negative in contrast to the high and positive effect of PE, as predicted by PADM.