Background/Objectives
Climate disasters like floods, hurricanes, and wildfires can devastate communities. Public investment in resilience is intended to reduce the negative impacts of climate disasters. In theory, investment in resilience should both reduce the impact of disasters on people and property and increase community desirability. Therefore, people should economically value resilience, especially in areas where climate risk is high. This study examines whether resilience moderates the effects of disaster exposure on community desirability. Our hypothesis is that resilience is more economically valued when disaster risk is high. In other words, when two counties are similar and face a high risk of climate disasters, home prices and population growth will be higher in the more resilient county.
Approach/Activities
We test our hypothesis concerning the role of community resilience in determining community desirability by estimating separate linear models for quantiles of disaster exposure using ordinary least squares (OLS) regression. Our outcomes of interest are proxies for the desirability of living in a given location. Our first set of outcome variables is the natural log of the median house price in the county and the natural log of the median price per square foot. We also include the natural logs of population density and housing stock density as alternative outcomes. Our measures of disaster resilience are taken from the 2015 version of the Baseline Resilience Indicators for Communities (BRIC) produced by the University of South Carolina. Our measure of disaster exposure is intended to capture the degree of risk that a county faces from natural disasters. Specifically, it is the weighted sum of the average annual frequency of disasters of a specific type experienced by the county. Relevant data for the calculation of the disaster exposure measure comes from FEMA’s National Risk Index. We control for a set of geographic characteristics of the county including latitude, latitude squared, longitude, longitude squared, the interaction between latitude and longitude, average annual temperature, average annual temperature squared, the natural log of elevation, the natural log of distance from the coast, and the natural log of our disaster exposure index.
Results/Lessons Learned
The results vary depending on the outcome variable, but generally, we find that resilience is valued more when climate disaster risk is low than it is when risk is high. There are several possible explanations for this finding. For example, people may not adequately value resilience due to misaligned incentives and moral hazard, such as government policies that encourage rebuilding rather than risk mitigation. Resilience indexes might only be providing partial measures of resilience. Drawing from foundational behavioral science, people might discount the benefits of resilience when risk is very high. To minimize risk, some people may choose to live in low risk, highly resilient communities. Whatever the reason, investment in resilience will be critical as climate risk increases. Policymakers and agency officials need better data on and understanding of how and why people choose to live in high-risk areas and what aspects of resilience, if any, they consider when making that choice. Policymakers should prioritize interventions that increase climate and disaster risk awareness, improve the ability of individuals to accurately assess their own risk, and invest in efforts that help people understand the benefits of resilience both in terms of investing in resilience and choosing to live in resilient communities. Finally, unless and until the broader social and economic benefits of climate and disaster resilience are quantified and accounted for in macroeconomic policymaking, resilience is unlikely to be sufficiently accounted for in individual homebuying decisions.