Sorting over flood risk and implications for policy reform

Do individuals sort across flood risk? This paper applies a boundary discontinuity design to a residential sorting model to provide novel estimates of sorting across flood risk by race, ethnicity, and income. We find clear evidence that low income and minority residents are more likely to move into high risk flood zones. We then highlight the overall and distributional implications of proposed price and information reforms to the U.S. National Flood Insurance Program. While such reforms are likely welfare increasing overall, heterogeneous behavioral responses yield significant distributive effects that also alter the composition of residents in harm's way. (c) 2020 Elsevier Inc. All rights reserved.Gulf Research Program24 month embargo; available online 15 August 2020This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Going Underwater? Flood Risk Belief Heterogeneity and Coastal Home Price Dynamics

How do climate risk beliefs affect coastal housing markets? This paper provides theoretical and empirical evidence. First, we build a dynamic housing market model and show that belief heterogeneity can reconcile prior mixed evidence on flood risk capitalization. Second, we implement a door-To-door survey in Rhode Island, finding significant flood risk underestimation and sorting based on risk perceptions and amenity values. Third, we estimate that coastal prices exceed fundamentals by 6\%-13\% in our benchmark area, with potentially higher overvaluation in other locations. Finally, we quantify both allocative inefficiency and distributional consequences arising from flood risk misperceptions and insurance policy reform.24 month embargo; published: 10 November 2021This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Is Tropical Cyclone Surge, Not Intensity, What Kills So Many People in South Asia?

This paper statistically examines the hypothesis that the level of storm surge, not storm intensity, is primarily responsible for the large number of tropical cyclone fatalities in SouthAsia. Because the potential causal link between intensity and surge can confound statistical inference, the authors develop two fatality models using different assumptions on the relationship between storm surge and intensity. The authors find evidence that storm surge is a primary killer of people in South Asia relative to storm intensity. In a surge-pressure independence model, it is found that a 10-cm increase in storm surge results in a 14% increase in the number of fatalities. In a surge-pressure dependence model, a 10-cm increase in the level of surge not driven by minimumcentral pressure (MCP) leads to 9.9% increase in the number of fatalities. By contrast, a one-millibar (1 hPa) decrease in MCP leads to a 7.3% increase in the number of fatalities, some of which is also attributable to storm surge. In South Asia, adaptation strategies should target a higher level of storm surge instead of higher-intensity storms. Policies to combat surge include permanent relocation, temporary evacuation, changes in building structures, and coastal fortification.6 month embargo; Published Online: 15 February 2017This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Flood Risk and Salience: New Evidence from the Sunshine State

A growing literature finds evidence that flood risk salience varies over time, spiking directly following a flood and then falling off individuals' cognitive radar in the following years. In this article, we provide new evidence of salience exploiting a hurricane cluster impacting Florida that was preceded and followed by periods of unusual calm. Utilizing residential property sales across the state from 2002 through 2012, our main estimate finds a salience impact of -8%, on average. The salience effect persists when we base estimation only on spatial variation in prices to limit confounding from other simultaneous changes due to shifting hedonic equilibria over time. These effects range from housing prices decreases of 5.4-12.3% depending on the year of sale. Understanding flood risk salience has important implications for flood insurance and disaster policy, the benefits transfer literature, and, more broadly, our understanding of natural disaster resilience. JEL Classification: Q51, Q54, R2112 month embargo; first published: 08 March 2019This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Validating Resilience and Vulnerability Indices in the Context of Natural Disasters

Due to persistent and serious threats from natural disasters around the globe, many have turned to resilience and vulnerability research to guide disaster preparation, recovery, and adaptation decisions. In response, scholars and practitioners have put forth a variety of disaster indices, based on quantifiable metrics, to gauge levels of resilience and vulnerability. However, few indices are empirically validated using observed disaster impacts and, as a result, it is often unclear which index should be preferred for each decision at hand. Thus, we compare and empirically validate five of the top U.S. disaster indices, including three resilience indices and two vulnerability indices. We use observed disaster losses, fatalities, and disaster declarations from the southeastern United States to empirically validate each index. We find that disaster indices, though thoughtfully substantiated by literature and theoretically persuasive, are not all created equal. While four of the five indices perform as predicted in explaining damages, only three explain fatalities and only two explain disaster declarations as expected by theory. These results highlight the need for disaster indices to clearly state index objectives and structure underlying metrics to support validation of the results based on these goals. Further, policymakers should use index results carefully when developing regional policy or investing in resilience and vulnerability improvement projects.US Army Corps of Engineers.24 month embargo; Version of record online: 30 August 2016This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Cumulative impacts in environmental justice: Insights from economics and policy

Disparities in health and socioeconomic well-being are a result of the cumulative impacts from multiple coinciding environmental, health, and social stressors. Addressing cumulative impacts is seen as a crucial step toward environmental justice (EJ). Using the case of the United States, we compare different methods to operationalize the concept for real-world application. We empirically demonstrate the extent to which non-White and low-income neighborhoods are subject to a wide array of burdens and how these burdens are reflected in national EJ indices and housing prices. We find that non-White and low-income neighborhoods are correlated with measures of multiple environmental burdens and social stressors but correlate to a lesser extent with natural disaster risk. Two existing EJ indices are only moderately correlated and more correlated with low-income status than with percent non-White. Models that employ the housing market for benefits estimation may fail to capture preferences to avoid multiple stressors due to issues including data availability and market frictions, such as discrimination. Finally, we highlight the challenges in cumulative impacts analysis for research and policy-making.24 month embargo; first published 7 March 2024This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Climate costs of tropical cyclone losses also depend on rain

It is well established that climate change will lead to changes in tropical cyclone (TC) characteristics and affiliated impacts to human communities. While a growing social science literature estimates losses from TCs, almost all have characterized TCs by wind speed alone. However, TC winds are commonly accompanied by intense rainfall, both of which will likely be impacted by climate change. We assess the impact of rain on current and future TC losses and estimate the bias in loss calculations from omitting rainfall. Using a TC Integrated Assessment Model utilizing 60 000 simulated TCs making landfall in South Korea, we find rain to be a significant loss determinant. For both the wind-only and wind + rain cases, socioeconomic change will cause a decrease in fatalities and a large increase in property losses due to a shrinking population and growing wealth. Regarding climate change, the wind-only case considerably underestimates the climate costs of TC losses compared to the wind + rain case, driven by notable increases in future rainfall in contrast with minor wind intensity changes. While the relative impacts of TC wind versus rain under climate change will no doubt be different across countries, our results highlight the importance of accounting for both wind and rainfall in research and policy, especially in mitigation and adaptation planning.Korea Meteorological Administration Research and Program [KMI2018-03413]This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]