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Natural Hazards, Disasters, and Demographic Change: The Case of Severe Tornadoes in the United States, 1980–2010

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Demography

Abstract

Natural hazards and disasters distress populations and inflict damage on the built environment, but existing studies yielded mixed results regarding their lasting demographic implications. I leverage variation across three decades of block group exposure to an exogenous and acute natural hazard—severe tornadoes—to focus conceptually on social vulnerability and to empirically assess local net demographic change. Using matching techniques and a difference-in-difference estimator, I find that severe tornadoes result in no net change in local population size but lead to compositional changes, whereby affected neighborhoods become more White and socioeconomically advantaged. Moderation models show that the effects are exacerbated for wealthier communities and that a federal disaster declaration does not mitigate the effects. I interpret the empirical findings as evidence of a displacement process by which economically disadvantaged residents are forcibly mobile, and economically advantaged and White locals rebuild rather than relocate. To make sense of demographic change after natural hazards, I advance an unequal replacement of social vulnerability framework that considers hazard attributes, geographic scale, and impacted local context. I conclude that the natural environment is consequential for the sociospatial organization of communities and that a disaster declaration has little impact on mitigating this driver of neighborhood inequality.

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Notes

  1. Although spatial location does not differentiate vulnerability in this case, residents’ dwelling type will determine their level of vulnerability. This is a constitutive factor of social vulnerability here. Also, tornadoes occur less frequently in urban areas because cities occupy relatively less land area compared with suburbs and rural areas (Hall and Ashely 2008; Wurman 2008).

  2. A disaster declaration may include provisions for public assistance and/or hazard mitigation. I use a parsimonious indicator for declarations and include any of the provisions. This captures aid for direct housing damage and indirect damage that assists public works or local businesses but not with respect to aid from community organizations and churches.

  3. For more information on the construction of SVRGIS, see Murphy (2018) and Edwards (2018). Kurdzo et al. (2017) compared tornado data from SVRGIS with data from Atmospheric Imaging Radar for several outbreak cases, and they found that the data sets closely align in space and time but that the SVRGIS data miss several short-lived, smaller tornadoes.

  4. For example, if the tornado path had F4 wind speed for only one-half mile along the path and F3 wind speed for three miles, it would be assigned an F4. For a discussion of tornado intensity assessment, see Strader et al. (2015).

  5. I restrict my analysis to the 25 states in which at least one severe tornado occurred in each of the three decades. Twelve other states (AZ, CT, CO, FL, MA, MD, MT, NJ, NY, UT, WV, and WY) experienced a severe tornado in the 30-year period, but in these states, severe tornadoes were extremely rare (five or fewer severe tornadoes) and were only F3 in magnitude.

  6. The 1970 to 1980 population trend is calculated at the census tract level and interpolated for the block groups within the census tracts. Missingness is a value to be matched on.

  7. I also exclude the block groups that experienced a tornado in the 1970s (n = 3,226) to ensure a clear temporal pattern for the matching and later treatment.

  8. The lead term equals 1 for a block group the decade before it experiences a severe tornado, and the lag term equals 1 for the decade after (Angrist and Pishke 2008:237). For example, for a block group that experienced a tornado in the 1990s, the treatment term is coded 1 for the 1990s, the lead term is coded 1 for the 1980s, and the lag term is coded 1 for the 2000s. Lag term for the 1980s identifies treated block groups from 1970 to 1979. Lead for the 2000s identifies treated block groups from 2010 to 2016.

  9. From 1980 to 1996, property loss information is in nine categories: <$50; $50–$500; $500–$5,000; $5,000–$50,000; $50,000–$500,000; $500,000–$5,000,000; $5,000,000–$50,000,000; $50,000,000–$500,000,000; and >$500,000,000. For comparability, I collapse post-1996 data into the same categories.

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Acknowledgments

Thank you to the four anonymous reviewers, Jason Beckfield, Jim Elliott, Joscha Legewie, Maya Sen, Mary Waters, Chris Wimer, Chris Winship, and Meghan Zacher for their suggestions that greatly improved this article. I also benefitted from audiences in the Seminar in Inequality and Social Policy, Harvard Sociology Qualifying Paper seminar, and the 2019 annual meeting of the Population Association of America in Austin, Texas. John Baldisserotto and the Harvard Data Reference library team provided tremendous assistance. Funding for this project was generously provided by a Malcolm H. Wiener PhD Scholarship from the Multidisciplinary Program in Inequality and Social Policy at Harvard University.

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  1. Department of Sociology, Harvard University, 536 William James Hall, 33 Kirkland Street, Cambridge, MA, 02138, USA

    Ethan J. Raker

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Raker, E.J. Natural Hazards, Disasters, and Demographic Change: The Case of Severe Tornadoes in the United States, 1980–2010. Demography 57, 653–674 (2020). https://doi.org/10.1007/s13524-020-00862-y

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