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Examining the impact of socioeconomic variables on COVID-19 death rates at the state level

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  • James L. Doti

    (Chapman University)

Abstract

This study uses a step-wise regression model to identify the socioeconomic variables most significant in explaining COVID-19 death rates on a state-level basis. The regression tests cover the 1/1/2020 to 12/1/2020 period as well as the first and second halves of 2020. This study also uses the Oxford stringency index to measure more precisely the efficacy of governmental mandates at the state level. The results in this study rigorously showed that while the density variables were the most significant explanatory variables during the first half of the year, their significance fell during the second half. Use of the Oxford stringency index revealed that more stringent mandates led to significant reductions in COVID-19 death rates, especially during the second half of the year. The study’s findings also reveal that a higher poverty rate in a state is significantly associated with higher COVID-19 death rates during all three periods tested.

Suggested Citation

  • James L. Doti, 2021. "Examining the impact of socioeconomic variables on COVID-19 death rates at the state level," Journal of Bioeconomics, Springer, vol. 23(1), pages 15-53, April.
    • Handle: RePEc:kap:jbioec:v:23:y:2021:i:1:d:10.1007_s10818-021-09309-9
    DOI: 10.1007/s10818-021-09309-9
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    Cited by:

    1. Janine Aron & John Muellbauer, 2022. "Excess Mortality Versus COVID‐19 Death Rates: A Spatial Analysis of Socioeconomic Disparities and Political Allegiance Across U.S. States," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 68(2), pages 348-392, June.
    2. James L. Doti, 2023. "The impact of vaccinations and chronic disease on COVID death rates," Journal of Bioeconomics, Springer, vol. 25(3), pages 239-269, December.

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