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The effect of nonpharmaceutical interventions on COVID-19 infections for lower and middle-income countries: A debiased LASSO approach

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  • Akbar Zamanzadeh
  • Tony Cavoli

Abstract

This paper investigates the determinants of COVID-19 infection in the first 100 days of government actions. Using a debiased LASSO estimator, we explore how different measures of government nonpharmaceutical interventions affect new infections of COVID-19 for 37 lower and middle-income countries (LMCs). We find that closing schools, stay-at-home restrictions, and contact tracing reduce the growth of new infections, as do economic support to households and the number of health care workers. Notably, we find no significant effects of business closures. Finally, infections become higher in countries with greater income inequality, higher tourist inflows, poorly educated adults, and weak governance quality. We conclude that several policy interventions reduce infection rates for poorer countries. Further, economic and institutional factors are important; thereby justifying the use, and ultimately success, of economic support to households during the initial infection period.

Suggested Citation

  • Akbar Zamanzadeh & Tony Cavoli, 2022. "The effect of nonpharmaceutical interventions on COVID-19 infections for lower and middle-income countries: A debiased LASSO approach," PLOS ONE, Public Library of Science, vol. 17(7), pages 1-17, July.
    • Handle: RePEc:plo:pone00:0271586
    DOI: 10.1371/journal.pone.0271586
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    as
    1. Lu, Xun & Su, Liangjun, 2016. "Shrinkage estimation of dynamic panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 190(1), pages 148-175.
    2. Daron Acemoglu & Victor Chernozhukov & Iván Werning & Michael D. Whinston, 2021. "Optimal Targeted Lockdowns in a Multigroup SIR Model," American Economic Review: Insights, American Economic Association, vol. 3(4), pages 487-502, December.
    3. Robert J. Barro & José F. Ursúa & Joanna Weng, 2020. "The Coronavirus and the Great Influenza Pandemic: Lessons from the “Spanish Flu” for the Coronavirus’s Potential Effects on Mortality and Economic Activity," NBER Working Papers 26866, National Bureau of Economic Research, Inc.
    4. Joseph G. Ibrahim & Hongtu Zhu & Ramon I. Garcia & Ruixin Guo, 2011. "Fixed and Random Effects Selection in Mixed Effects Models," Biometrics, The International Biometric Society, vol. 67(2), pages 495-503, June.
    5. Victor Ginsburgh & Glenn Magerman & Ilaria Natali, 2021. "COVID-19 and the role of inequality in French regional departments," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(2), pages 311-327, March.
    6. Roman Hoffmann & Sebastian Uljas Lutz, 2019. "The health knowledge mechanism: evidence on the link between education and health lifestyle in the Philippines," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(1), pages 27-43, February.
    7. John Wildman, 2021. "COVID-19 and income inequality in OECD countries," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(3), pages 455-462, April.
    8. Mounir Amdaoud & Giuseppe Arcuri & Nadine Levratto, 2021. "Are regions equal in adversity? A spatial analysis of spread and dynamics of COVID-19 in Europe," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(4), pages 629-642, June.
    9. Laura Langbein & Stephen Knack, 2010. "The Worldwide Governance Indicators: Six, One, or None?," Journal of Development Studies, Taylor & Francis Journals, vol. 46(2), pages 350-370.
    10. Mounir Amdaoud & Giuseppe Arcuri & Nadine Levratto, 2021. "Are regions equal in adversity? A spatial analysis of spread and dynamics of COVID-19 in Europe," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(4), pages 629-642, June.
    11. Barro, Robert J., 2022. "Non-pharmaceutical interventions and mortality in U.S. cities during the great influenza pandemic, 1918–1919," Research in Economics, Elsevier, vol. 76(2), pages 93-106.
    12. Ruben Dezeure & Peter Bühlmann & Cun-Hui Zhang, 2017. "High-dimensional simultaneous inference with the bootstrap," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(4), pages 685-719, December.
    13. Arindam Chatterjee, 2017. "Comments on: High-dimensional simultaneous inference with the bootstrap," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(4), pages 729-730, December.
    14. Alberto Abadie & Alexis Diamond & Jens Hainmueller, 2015. "Comparative Politics and the Synthetic Control Method," American Journal of Political Science, John Wiley & Sons, vol. 59(2), pages 495-510, February.
    15. Seth Flaxman & Swapnil Mishra & Axel Gandy & H. Juliette T. Unwin & Thomas A. Mellan & Helen Coupland & Charles Whittaker & Harrison Zhu & Tresnia Berah & Jeffrey W. Eaton & Mélodie Monod & Azra C. Gh, 2020. "Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe," Nature, Nature, vol. 584(7820), pages 257-261, August.
    16. repec:aei:rpaper:1008563887 is not listed on IDEAS
    17. Sala-i-Martin, Xavier, 1997. "I Just Ran Two Million Regressions," American Economic Review, American Economic Association, vol. 87(2), pages 178-183, May.
    18. Honda, Toshio & 本田, 敏雄, 2019. "The de-biased group Lasso estimation for varying coefficient models," Discussion Papers 2018-04, Graduate School of Economics, Hitotsubashi University.
    19. Tingni Sun & Cun-Hui Zhang, 2012. "Scaled sparse linear regression," Biometrika, Biometrika Trust, vol. 99(4), pages 879-898.
    20. Cun-Hui Zhang & Stephanie S. Zhang, 2014. "Confidence intervals for low dimensional parameters in high dimensional linear models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 76(1), pages 217-242, January.
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