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Extreme Weather: Housing, Transport, and Finance

Paper Session

Friday, Jan. 5, 2024 10:15 AM - 12:15 PM (CST)

Grand Hyatt, Republic A
Hosted By: Association of Environmental and Resource Economists
  • Chair: Amine Ouazad, Rutgers University

Weather and the safety of U.S. railways

Xinming Du
,
National University of Singapore
Andrew Wilson
,
Columbia University

Abstract

Railway safety is affected by the weather. We quantify these effects by leveraging a comprehensive dataset on railway safety incidents in the United States spanning 1997–2019. Though weather conditions are noted as a primary or contributing factor to 2.2% of railway safety incidents during our data period, we find that weather causes closer to 8.5% of all rail safety incidents—four times the documented amount. Both heat and cold cause elevated incident counts, with effects especially strong for incidents leading to injuries or deaths. Exposure to a daily average temperature over 30◦C (86◦F) leads to a 9.5% increase in the number of rail safety incidents, a 27% increase in the number of incidents leading to a casualty, and 25% and 57% increases injuries and deaths—effects net of any operational adjustments made to mitigate these effects. Extreme cold and extreme precipitation also affect safety. We find that locations are adapted to their local climate, with, for example, warmer places exhibiting a weaker relationship between heat and incident count. Further, past exposure to hazardous weather leads to fewer accidents future accidents, perhaps demonstrating learning. The numbers of injuries and deaths associated with rail system weather exposure may suggest a role for enhanced rail safety regulations and adaptation funding to protect critical infrastructure.

Natural Disasters and Mortgage Risk in the Federal Housing Administration

Michael Craig
,
United States Department of Housing and Urban Development
Adam Hoffberg
,
United States Department of Housing and Urban Development

Abstract

Climate change poses significant risk to the US housing and mortgage finance ecosystem, with many effects shown or predicted to disproportionately affect economically vulnerable populations. Households exposed to natural disasters face risks of damaged homes, loss of residence and income disruptions, among others. For mortgage borrowers, disaster related financial shocks could lead to significant financial distress resulting in mortgage default. Focusing on the Federal Housing Administration’s (FHA) single family mortgage insurance (MI) program, this study characterizes past disaster exposure on a sample of 897,00 FHA insured mortgages from 2004-2017 and estimates a relationship between past exposure and homebuyer outcomes. Additionally, this study estimates risks to the FHA Mutual Mortgage Insurance Fund (MMI Fund) through a two-stage process. Despite FHA safeguards against disaster-related costs, such as requirements for hazard insurance and “preservation and protection” requirements, results indicate a positive correlation between exposure and adverse borrower outcomes. Using a standard claims-probability logit model with zip-code level disaster exposure data from FEMA and an 18-year loan level panel of FHA borrower and mortgage characteristics, we find disaster exposure correlates with a 20% increase in the probability of mortgage foreclosure with an MI claim. These effects are heterogeneous across race, disaster type and credit groups, providing evidence that economically vulnerable groups are more susceptible to adverse outcomes within the FHA portfolio. A second stage simulation using estimated coefficients from the claims probit model finds that disaster exposure caused between $0.8 billion and $1.5 billion in additional MI claims from 2004 to 2019. The role of hazard insurance and disaster aid are also examined.

The Effects of Floodplain Buyouts on Local Housing Market: Evidence from Harris County, Texas

Meri Davlasheridze
,
Texas A&M University-Galveston
Qing Miao
,
Rochester Institute of Technology
Kayode O. Atoba
,
Texas A&M University-Galveston

Abstract

Concerns over climate change and increased climatic disasters (e.g., hurricanes and flooding) have prompted growing interests in long-term adaptation involving permanent changes in land use and the built environment. Managed retreat has been recognized as an essential strategy for reducing flood risks in low-lying coastal areas where structural protection alone is insufficient to address repetitive flooding losses. Retreat is often supported through government buyouts of disasterdamaged properties, which are later demolished with the land being converted into open space. Buyouts are expected to deliver considerable social benefits by reducing future disaster losses (e.g., through reducing exposure of population and assets in high-risk areas) and improving environmental amenities (e.g., open space, increased recreational opportunities) and other ecosystem services. However, little research has empirically examined the effect of government buyouts and subsequent migration on the local communities, in particular their social welfare and well-being. This paper presents one of the first few studies of government buyouts of floodplain properties on local housing markets, in order to advance our understanding and assessment of the economic value of buyouts as land-based adaptation policy. Specifically, we focus on government buyouts implemented through the FEMA’s Hazard Mitigation Grants Program (the nation’s primary program funding post-disaster buyouts) in Harris County, Texas. The city of Houston is the largest city in the county and has the most property acquisitions in the nation, and meanwhile is the one of most flood-impacted areas. Rapid population growth increases local exposure to flood hazards, thereby making land use and development decisions highly important in local hazard mitigation. Our empirical analysis focuses on the property buyouts implemented after 2017 Hurricane Harvey, and uses the housing transaction data between 2010 and 2022. We combine a difference-in-difference approach with a hedonic model which controls for various housing structural, neighborhood, locational, and hazard risk characteristics along

Extreme Weather and Low-Income Household Finance: Evidence from Payday Loans

Shihan Xie
,
University of Illinois
Victoria Wenxin Xie
,
Santa Clara University
Xu Zhang
,
Bank of Canada

Abstract

This paper explores the impact of extreme weather exposures on the financial outcomes of low-income households. Using a novel dataset comprising individual-level payday loan applications and loan-level information, we find that both extreme heat and cold days lead to surges in payday loan demand. Extra extreme heat days result in an increase in delinquency and default rates and a reduction of total credit issued, indicating a contraction in loan supply. The effects are especially noticeable for online payday loans. Our findings highlight the heightened financial vulnerability of low-income households to environmental shocks and underscore the need for targeted policies.

Discussant(s)
Eric Zou
,
University of Oregon
William Boyd McClain
,
Fannie Mae
Amine Ouazad
,
Rutgers University
JEL Classifications
  • Q5 - Environmental Economics
  • G2 - Financial Institutions and Services