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Atlanta Marriott Marquis, International 7
Hosted By:
American Economic Association
In this paper, we examine whether and how the distribution of homebuyer race and income across flood risk changed over a period from 2002-2012 in response to a large information shock conveyed by a hurricane cluster in Florida that produced large damages in neighboring counties. Specifically, we use a differences-in-differences approach to compare the difference in homebuyer characteristics across high and low flood risk areas before the hurricane cluster in Florida to the same difference after the hurricane cluster to test for heterogeneity in sorting across flood risk in response. Using information on the structural characteristics of the homes that were purchased, we also impute the NFIP subsidies for each homebuyer; this allows us to additionally investigate whether the hurricane cluster affected groups differentially in their decision of the type of house to purchase, and thus the NFIP premiums (subsidies) they paid (received). Our results inform how individuals respond to disasters and market distortions. In addition, we contribute to the discourse on distributional equity regarding natural hazards policies and their potential role in exacerbating inequitable flood risk exposure in the United States.
Behavioral Hedonics: New Insights for Environmental Valuation
Paper Session
Sunday, Jan. 6, 2019 1:00 PM - 3:00 PM
- Chair: Nicolai Kuminoff, Arizona State University
Flood Risk, Subsidies, and the Distributional Impacts of the National Flood Insurance Program
Abstract
The National Flood Insurance Program (NFIP) was enacted to combat the risk of flooding, one of the most costly natural disasters in the United States. While the program was designed to solve a market incompleteness problem, it has been criticized for having, in some cases, highly subsidized premiums, hindering the program’s ability to efficiently smooth flood risk across space and time. Key policy questions surround the potential distributional consequences of the NFIP. In particular, are there systematic differences in the extent to which individuals of different sociodemographic backgrounds sort over flood risk and NFIP subsidies? If so, are those individuals also more likely to belong to populations that are considered vulnerable?In this paper, we examine whether and how the distribution of homebuyer race and income across flood risk changed over a period from 2002-2012 in response to a large information shock conveyed by a hurricane cluster in Florida that produced large damages in neighboring counties. Specifically, we use a differences-in-differences approach to compare the difference in homebuyer characteristics across high and low flood risk areas before the hurricane cluster in Florida to the same difference after the hurricane cluster to test for heterogeneity in sorting across flood risk in response. Using information on the structural characteristics of the homes that were purchased, we also impute the NFIP subsidies for each homebuyer; this allows us to additionally investigate whether the hurricane cluster affected groups differentially in their decision of the type of house to purchase, and thus the NFIP premiums (subsidies) they paid (received). Our results inform how individuals respond to disasters and market distortions. In addition, we contribute to the discourse on distributional equity regarding natural hazards policies and their potential role in exacerbating inequitable flood risk exposure in the United States.
What Is the Value of Conformity? Evidence from Home Landscaping and Water Conservation Decisions
Abstract
In this article, we estimate how consumers value conformity using housing market data. We examine homeowners' landscaping choices---which have extensive consequences for water consumption---for housing parcels throughout Phoenix, Arizona. Because of their visibility and salience, we suspect that landscaping decisions may trigger conformity norms. Using machine learning techniques to process extremely high-resolution remote sensing imagery, we generate precise classifications of landscape cover on each parcel, allowing us to estimate the hedonic value of conformity. We find that a one standard deviation departure from the peer group norm (defined by nearby neighbors) decreases property value by roughly $2250 for an average home. We then develop a theoretical model to characterize how conformity motives can be incorporated into the design of Pigouvian policies. Combining our model with empirical estimates of hedonic demand, we find that Pigouvian pricing adjustments need to be nearly twice as large to achieve a given outcome in the presence of conformity motives. Prior work has used controlled experiments to study conformity, but our work is unique as the first to study this behavioral phenomenon using rich observational data from a real-world market.Climate Change and Flood Beliefs: Evidence from New York Real Estate
Abstract
Applying a hedonic difference-in-differences framework to a census of residential property transactions in New York City 2003-2017, we estimate the effects of three flood risk signals: 1) the Biggert-Waters Flood Insurance Reform Act, which increased premiums; 2) Hurricane Sandy; and 3) new FEMA floodplain maps. Properties for which a signal provides more new information exhibit larger effects: for properties not flooded by Sandy but included in the new floodplain, prices fall by as much as 18 percent. Informed by a theoretical model, we decompose our reduced-form estimates into the effects of insurance premium changes and updating, finding that new maps (an information signal) induce belief changes substantially larger than those from insurance reform (a price signal). Using Google data, we document increases in flood-related search intensity coincident with flood risk signals.Discussant(s)
Daniel Sullivan
,
Resources for the Future
Crystal Zhan
,
University of South Carolina
Nicolai Kuminoff
,
Arizona State University
Lint Barrage
,
Brown University
JEL Classifications
- Q5 - Environmental Economics
- R3 - Real Estate Markets, Spatial Production Analysis, and Firm Location