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Essays on the Economics of Flood Risk

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Essays on the Economics of Flood Risk Essays on the Economics of Flood Risk Caroline A. Hopkins A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Economics Tepper School of Business Carnegie Mellon University April 9th, 2021 Dissertation Committee: Nicholas Z. Muller, Tepper School of Business, Carnegie Mellon University Karam Kang, Tepper School of Business, Carnegie Mellon University Dennis Epple, Tepper School of Business, Carnegie Mellon University Laura Bakkensen, School of Government and Public Policy, University of Arizona Acknowledgements I have received an incredible amount of support while working on this dissertation. Thank you to the members of my committee, Nicholas Muller, Karam Kang, and Dennis Epple, whose guid- ance was integral to completing this dissertation. And, thank you to my outside reader, Laura Bakkensen, for her thoughtful feedback. My research benefited from comments by Jay Apt, Ak- shaya Jha, and numerous seminar and conference participants. I also thank the professors and economists who helped me get here, including: Art Goldsmith, Joseph Guse, Paul Bourdon, Sarah Sprenkle, Peter Fox-Penner, Shaun Ledgerwood, Nicholas Powers, and James Reitzes. I am indebted to Laila Lee and Lawrence Rapp; their assistance and kindness made completing every step of this process easier. I thank all of my peers for the enlightening conversations about research and life. A special thanks to my peer, Elizabeth Campbell, for helping me break big questions into manageable tasks. I am grateful to my friends and family whose endless encouragement kept me going. I am especially thankful for my parents, James and Kathy Hopkins, who instilled in me a love of learning and sense of self. I thank my dog, Lucy, for making sure I laughed, walked, and played every day. Lastly, I thank David Adler for being the best partner to go on this journey with. i Abstract Climate change yields heightened flood risk due to both sea level rise and an increased frequency of significant storms. While prior literature has estimated flood damages, it is difficult to measure how agents will respond to an increase in flood risk. Furthermore, it is important to understand how policymakers can minimize these risks by investing in flood hazard protections. My disserta- tion studies the problem of valuing the cost of flood risk and the role of policymakers in response to flood risk. In the first part, I explore the relationship between flood risk and the housing market. This allows me to measure the cost of increased flood risk on housing markets using revealed pref- erence methods. In the second part of my dissertation, Chapters 2 and 3, I study why policymakers invest in flood hazard reduction and how flood hazard mitigation is valued by homeowners. My findings on what factors influence policymakers to invest in flood hazard protection at the local level and how these investments are valued provide important insights for the federal government as it redesigns the National Flood Insurance Program (NFIP). My first chapter (joint with Nicholas Z. Muller) provides evidence that well-informed home- owners of coastal real estate respond to flood risk. Our innovations in this paper are two-fold. First, we parse homeowners according to the quality of information they possess about their flood risk, and second, we disentangle flood risk from property damage. Prior literature has found evi- dence that homeowners respond to flood shocks, however these papers focus mostly on local flood shocks. As such, it is difficult to separate the cost of damages from the effect of information about risk. Our paper circumvents this identification issue by testing whether non-local flooding events affect housing prices in coastal markets. Utilizing a difference-in-differences methodology, we test whether homeowners in high flood risk areas along the coast of New Jersey respond to non-local flooding. We use several well-publicized hurricanes and tropical storms that did not strike the Atlantic seaboard as non-local shocks. We find that prices of homes in areas of high flood risk do not decrease after a storm, but rather increase. The literature has shown current and prospec- tive homeowners do not always know their flood risk, so we further test if informed homeowners respond differently. We use participation in Community Rating System (CRS) public awareness activities as a measurement of homeowner’s information. We find that homes in high flood risk zones situated in towns that participate in public flood awareness activities incur a 7 to 16 percent decrease in price after the non-local shock. Further, we show that firms are more responsive to risk information than individuals and that markets exposed to such information are less adversely affected by future disasters. For my second chapter I study the decision to participate in CRS, which is a federally run pro- gram that incentivizes local jurisdictions to undertake activities related to flood hazard mitigation in exchange for flood insurance discounts for their constituents. In this chapter I study the decisions ii of the government to participate in CRS from a static perspective. First, I build a model of the local government’s decision to provide a public good that mitigates hazard risk. Second, I use participa- tion in CRS in New Jersey to empirically test the hypotheses generated by the theoretical model in the context of flood hazard mitigation. Consistent with the model predictions, the empirical results show that an array of factors affect participation: income, population, housing values, risk, value of amenity access, information, and whether the local jurisdiction type is mayor-council. This paper further contributes to the literature on optimal public good provision by showing that incomplete information, weak government accountability, and lobbying can lead to inefficient levels of hazard mitigation. My third chapter further explores the decision of local governments to invest in flood hazard mitigation and builds on my second chapter by using a dynamic structural model of the local gov- ernment’s decision, which accounts for the value of flood hazard mitigation to homeowners. Thus, I am able to consider the interdependency between changes in federal policy and the decisions of the local government. To this end, I estimate a homeowner’s marginal willingness to pay for flood insurance and for the local government’s flood hazard mitigation actions based on housing sales in New Jersey from 1998 to 2018. I then use a dynamic discrete choice model of the local govern- ment’s investment decision to estimate their costs. I find that the spillover effects from mitigation are positive, insurance discounts are valued more than the actual savings, and that large initial perceived costs may prevent investments in hazard mitigation. Finally, I perform counterfactual analyses to consider the local government response to alternative federal policies. The counterfac- tuals suggest that either increasing the proportion of homes in federally designated high risk zones to account for climate change or raising the federally set flood insurance rates increase investment in flood hazard mitigation, and that implementing a cost subsidy rather than the current insurance discount policy may increase investment in municipalities with low property values. iii Contents 1 The Role of Information in the Market Response to Flood Risk: Hurricane Katrina and the New Jersey Coast 1 1.1 Introduction . .1 1.1.1 Relevant Literature . .5 1.2 Data and Empirical Analysis . .8 1.2.1 Data . .8 1.2.2 Empirical Analysis . 11 1.3 Identification . 13 1.3.1 Parallel Trends . 14 1.3.2 Event Studies . 14 1.4 Results . 16 1.4.1 Diff-in-Diff Model: High Risk Zone as Treatment . 16 1.4.2 Triple Difference Model: High Risk Zone, CRS Enrollment as Treatment . 18 1.4.3 Robustness Checks . 22 1.4.4 Monetary Impact of Flood Risk and Welfare Implications . 27 1.5 Conclusion . 29 2 Why Local Governments Provide Hazard Mitigation: Evidence from The Community Rating System 30 2.1 Introduction . 30 2.2 Background . 34 2.3 Model . 37 2.3.1 Model Setup . 37 2.3.2 Optimization Problems . 38 2.3.3 Optimal Public Good Provision . 40 2.3.4 Implications of the Model . 42 2.3.5 Extension with Homeowner’s Utility Function . 43 2.3.6 Extension with Government’s Problem: Inefficient Case . 44 iv 2.4 Data . 48 2.4.1 Community Rating System . 48 2.4.2 Local Municipality Data . 49 2.4.3 Descriptive Statistics . 49 2.5 Empirical Results . 51 2.5.1 Initial Test of Model and Extensions . 51 2.5.2 Tests of the Role of Information . 57 2.5.3 Tests of Government Accountability Using Hurricane Sandy . 61 2.6 Conclusion . 66 3 Flood Hazard Mitigation and the Role of the Government: A Dynamic Model of Local Government Investment in a Public Good 68 3.1 Introduction . 68 3.1.1 Related Literature . 72 3.2 Empirical Setting . 73 3.2.1 Institutional Background . 73 3.2.2 Data . 75 3.3 Model . 80 3.4 Estimation . 85 3.4.1 First Stage: Benefits . 85 3.4.2 First Stage: Transition Probabilities . 87 3.4.3 First Stage: Conditional Choice Probabilities . 87 3.4.4 Second Stage . 88 3.5 Results . 89 3.5.1 Results of Hedonic Estimation . 89 3.5.2 Results of Dynamic Discrete Choice Model . 93 3.5.3 Model Fit . 94 3.6 Counterfactuals . 97 3.6.1 Counterfactual 1 . 97 3.6.2 Counterfactual 2 . 99 3.6.3 Counterfactual 3 . 101 3.7 Conclusion . 102 Appendices 117 A Appendix to Chapter 1 . 118 A.1 Appendix Tables . 118 A.2 Appendix Figures . 136 v B Appendix to Chapter 2 . 144 B.1 Model Proofs . 144 B.2 Model Proofs: Relaxing Assumption on Full Insurance .
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