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Differences in State Level Impacts of COVID-19 Policies

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Theory and History in Regional Perspective

Part of the book series: New Frontiers in Regional Science: Asian Perspectives ((NFRSASIPER,volume 56))

Abstract

This paper compares COVID-19 infections between selected pairs of neighboring states where the policies of the non-pharmaceutical interventions (NPI) such as lockdown/stay-at-home differ. This analysis uses a difference-in-differences (Diff-in-Diff) model to test the effectiveness of NPI in mitigating COVID-19 infections at the state level. The states are Iowa and Illinois, the Dakotas (North and South) and Minnesota, and Arkansas and Mississippi. In each case the policies for each pair of states differ. Based on the difference-in-difference model output, state policies appear to make a significant difference in infection rates but these differences vary. This is for the first phase (wave) of the pandemic (April–June 2020). State level results are mixed reflecting spatial heterogeneity and interaction across the inter-state system. However, there appears to be a significant positive lag effect following the lifting of these mitigation/lockdown policies.

This research in one of a series drawn from the COVID Research Grant funded by the Schar Foundation Initiative examining the first wave of the COVID disease diffusion in the USA (May–Sept/2020)—Kingsley E. Haynes, Principal Investigator.

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Notes

  1. 1.

    NBER website: https://www.nber.org/wp_covid19.html and IZA: https://covid-19.iza.org/publications/

  2. 2.

    See Brodeur et al. (2020) for a review of these literature.

  3. 3.

    JHU’s time series cumulative confirmed COVID-19 cases data were downloaded. The DiD analyses for neighboring states have COVID-19 data up to Aug 31, 2020.

  4. 4.

    A time series with daily cumulative counts is expected to be a non-decreasing by date, i.e., the values either stay the same or increase with time as fresh counts are added. However, in the JHU time series data, the confirmed COVID-19 cases may show an aperiodic drop in the cumulative counts. This is due to noise in the data, as it is compiled continuously from various sources.

  5. 5.

    Majority of infections (548) are from Cook County in Illinois

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Correspondence to Kingsley E. Haynes .

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Haynes, K.E., Kulkarni, R., Li, MH., Siddique, A.B. (2022). Differences in State Level Impacts of COVID-19 Policies. In: Kawano, M., Kourtit, K., Nijkamp, P., Higano, Y. (eds) Theory and History in Regional Perspective. New Frontiers in Regional Science: Asian Perspectives, vol 56. Springer, Singapore. https://doi.org/10.1007/978-981-16-6695-7_22

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