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Extreme Weather Events and Local Fiscal Responses: Evidence from U.S. Counties

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Abstract

This paper examines the impacts of floods and hurricanes on U.S. county government finances. Using a novel event study model that allows for heterogeneous treatment effects, we find that a flood or hurricane presidential disaster declaration (PDD) lowers tax revenue but increases government spending and intergovernmental revenues. Compared to flooding, hurricanes result in much larger repercussions on both revenues and borrowing. Our results also suggest disparate patterns of disaster-induced long-run fiscal impacts in counties with different socioeconomic conditions. Counties with lower incomes or greater social vulnerability tend to experience tax revenue losses and engage in more borrowing after a PDD, whereas higher-income counties see increased tax revenues and spending and also receive more intergovernmental transfers than their poorer counterparts.

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Data Availability

Parts of the data collected for conducting the current study are not publicly available due to purchase, but are available from the corresponding author upon reasonable request.

Notes

  1. The PDD allows federal aid to be distributed through various disaster programs to state and local governments, and at times, affected households and businesses as well. The vast majority of federal disaster aid is provided after a PDD. It is estimated that from 2005 to 2019, the federal government spent over $460 billion on disaster assistance (Pew 2020), and about $200 billion was disbursed through the Disaster Relief Fund (DRF), the primary source of federal disaster relief aid administered by FEMA (Congressional Research Service or CRS 2020).

  2. For example, Strobl (2011) finds that hurricanes cause the out-migration of higher-income households and such disaster-induced relocation and demographic changes can negatively affect local own-source revenues.

  3. Connecticut and Rhode Island are excluded due to data unavailability.

  4. It should be noted that the differences are not only statistically significant but also economically significant. Specifically, the county-level average personal income per capita in our sample is about 20% higher than that of the non-sampled counties. The average county population in our sample is more than six times bigger than that of the non-sampled counties. The total population from the counties in our estimation sample accounted for approximately 85% of the entire U.S. population in 2015.

  5. If the measurement error is random, it should not bias our estimates of disaster-induced fiscal impacts but may cause more noise. Yet, it is possible that governments may engage in “strategic reporting” of their financial data, which could occur in both directions. If the pattern of strategic reporting is associated with certain county characteristics, this may cause more systematic measurement errors and potentially bias our estimates. In our empirical model, we include the county fixed effects to alleviate the self-reporting bias.

  6. We also performed the T-test between our sampled counties and non-sampled counties in the four fiscal measures and found the two groups are relatively comparable. There is no statistical difference in their average tax revenues and long-term debt per capita. Our sampled counties have higher public spending and intergovernmental revenues than those not included, but their differences are only marginally significant (at the 10% level).

  7. We specify and estimate the dynamics in relative periods from t-9 to t + 9 in the regression to allow for examining a 10-year cumulative effect since the PDD shock occurs in year t. In addition, the model includes an indicator for all years prior to this period and one for all years after. We do not report the coefficients on this pair of indicators as they are less meaningful to interpret.

  8. While hurricanes induce larger long-term increases in intergovernmental transfers and long-term debt issuance than flooding, they also cause larger tax revenue losses than flooding, which may constrain local spending growths.

  9. In our national sample of counties, the total tax revenue variable highly correlates with property tax revenues (correlation coefficient is 0.96), and the latter on average accounts for 77% of the former.

  10. We also estimated the impact of PDDs on a county’s population size using data from the Bureau of Economic Analysis and do not find a significant disaster effect. In addition to property taxes, we have also examined the changes in a county’s total sales tax revenues following PDDs. Our results, available upon request, suggest that flooding and hurricane PDDs generally have insignificant effects on sales tax revenues in the short- or longer term.

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Authors and Affiliations

  1. Department of Public Policy, Rochester Institute of Technology, Rochester, NY, USA

    Qing Miao

  2. Philippine Institute for Development Studies, Quezon City, The Philippines

    Michael Abrigo

  3. Center for Policy Research, Syracuse University, Syracuse, NY, USA

    Yilin Hou

  4. Resources for the Future, Washington, DC, USA

    Yanjun (Penny) Liao

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  1. Qing Miao
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  2. Michael Abrigo
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  3. Yilin Hou
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  4. Yanjun (Penny) Liao
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Contributions

Qing Miao conducted the literature review, data analysis and wrote the main manuscript text. Michael Abrigo worked on the econometric modeling. Yilin Hou and Yanjun Liao contributed to the writing of the manuscript. All authors reviewed the manuscript.

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Correspondence to Qing Miao.

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Miao, Q., Abrigo, M., Hou, Y. et al. Extreme Weather Events and Local Fiscal Responses: Evidence from U.S. Counties. EconDisCliCha 7, 93–115 (2023). https://doi.org/10.1007/s41885-022-00120-y

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