Surge of Inequality: How Different Neighborhoods React to Flooding

Abstract
Recovery scenarios after flooding vary by locality, from permanent declines in economic activity to capital gains. This paper shows that divergent post-flood trajectories at the neighborhood level increased preexisting spatial polarization along property value, racial, and income lines. Using evidence from property sales in four US states affected by Superstorm Sandy in 2012, combined with buyers' demographics, I find that flooded properties in neighborhoods with a high preexisting income had more high-income white buyers and higher sale prices than comparable non-flooded coastal properties, seemingly capitalizing on the flood and offsetting average drops. Using machine learning algorithms, I conclude that of a rich set of preexisting place characteristics, neighborhood income best discriminates between most positively and most negatively affected properties. This evidence is consistent with a model of neighborhood segregation in which residential sorting—induced by credit-constrained households deriving higher disutility from flooding—rationally results in more high-income residents and higher property prices in initially higher-income neighborhoods. As coastal flooding is forecasted to increase, these results improve our understanding of the heterogeneous impacts of floods and the existence of adaptive behavior, or lack thereof, after flooding.