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The pre-pandemic political economy determinants of lockdown severity

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Abstract

We investigate the determinants of the severity of U.S. state-level lockdown regulations adopted during the COVID-19 pandemic. We employ a new measure of Lockdown Regulatory Freedom from Miozzi and Powell (Am J Econ Sociol, 2023b. https://doi.org/10.1111/ajes.12512) to investigate whether pre-pandemic measures of economic freedom, political variables, and measures of COVID-19 exposure and severity impacted the severity of subsequent lockdowns. Our main finding is that the severity of a state’s lockdown regulations were primarily determined by pre-pandemic levels of economic freedom and pre-existing political ideology, as measured by the share of votes for the 2016 Democrat presidential candidate.

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Notes

  1. See Allen et al. (2022) for a further analysis of the Coasian nature of the COVID-19 externality.

  2. See Bentkowska, 2021; Dingle & Nieman, 2020; Fairlie, 2020; Greenstone & Nigam, 2020; Gupta et al., 2020; Redford & Dills, 2021; for a few of the costly impacts of COVID-19 regulation on economic activity.

  3. Similarly, Baaccini & Brodeur (2020) also find that democratic governors were more aggressive in issuing stay-at-home orders.

  4. This state level Lockdown Regulatory Freedom measure is itself derived from an international Lockdown Regulatory Freedom measure created in Miozzi & Powell (2023a) that was used to adjust the index of economic freedom in the Economic Freedom of the World Annual Report.

  5. While this study is only using the Lockdown Regulatory Freedom Component developed in Miozzi & Powell (2023a, b) it is worth noting that in both those studies they find the short-run trade off where pandemic responses substantially reduced economic liberty as posited in Koyama (2023).

  6. See Miozzi & Powell (2023a or b) for a thorough description of the Lockdown Regulatory Freedom measure.

  7. The Lockdown Regulatory Freedom scores for 2020 includes daily scores from March 1st through December 31st since no state had any significant lockdown policies before March.

  8. All variables related to COVID deaths and cases come from the Center for Disease Control’s COVID Data Tracker, available at: https://covid.cdc.gov/covid-data-tracker.

  9. These variables come from the U.S. Department of Health & Human Services, available at: https://healthdata.gov/Hospital/COVID-19-Reported-Patient-Impact-and-Hospital-Capa/g62h-syeh.

  10. These states are: California, Georgia, Hawaii, Illinois, Massachusetts, Michigan, Nevada, New York, Texas, and Washington.

  11. See https://www.nga.org/.

  12. See https://morningconsult.com/governor-rankings/.

  13. Date of First Death is omitted from this table as the variable tracks dates and not a quantitative value. For this variable, the state with the first COVID-related death was Alabama (2-27-20). The last state with its first reported COVID death was Wyoming (4-13-20)

  14. We run these correlations with 2021 lockdown regulatory freedom as well, but leave them unreported, finding that the 2021 relationship is also statistically significant. Exposure to Asia could presumably influence regulatory responses early in the pandemic. However, the fact that 2021 is also statistically significant suggests that perhaps these results don’t indicate exposure because all U.S. states had widespread COVID exposure by 2021. What is, perhaps, more likely is this is capturing “backlash effects” such that voters in areas with large Asian populations become more concerned with the pandemic as time goes on.

  15. Our results remain largely unchanged when we retain the direct flights variable and drop the Asian population share variable.

  16. We get the same result when we replace the Democratic Governor dummy with a dummy for only Democratic Governors that had unified governments.

  17. See Bazi et al. (2021) for a similar finding. They examine county level pandemic reactions and find that counties with greater “total frontier experience,” which they use as a proxy for individualist values, had less social distancing, mask use, and local government pandemic restrictions. This finding is consistent with our findings, though we do not endorse their normative interpretation of their results.

  18. Also see Geloso et al. (2021) for an examination of the institutional tradeoff between liberty and health during pandemics and Goodman et al. (2021) for the relationship between infectious disease and government growth.

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  1. Texas Tech University, Lubbock, USA

    Vincent Miozzi & Benjamin Powell

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  1. Vincent Miozzi
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  2. Benjamin Powell
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Correspondence to Benjamin Powell.

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We thank the editors, two anonymous referees, the participants at Texas Tech University’s Free Market Institute “brown bag” research seminar series, the participants at the Association of Private Enterprise Education’s 2023 conference, and the participants at Ball State’s 2023 Midwest Institutes Conference for helpful comments on earlier drafts of this paper.

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Miozzi, V., Powell, B. The pre-pandemic political economy determinants of lockdown severity. Public Choice 197, 167–183 (2023). https://doi.org/10.1007/s11127-023-01086-5

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