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Assessing the effectiveness of international government responses to the COVID-19 pandemic

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  • Lopez-Medoza, Hector
  • González-Álvarez, Maria A.
  • Montañés, Antonio

Abstract

This paper studies the effectiveness of the non-pharmaceutical measures adopted by governments in order to control the evolution of the COVID-19 pandemic. To that end, we estimate a Panel VAR model for 50 countries and test for causality between the 7 day cumulative incidence, the mortality rate and a stringency index that measures government actions. The use of Granger-type statistics provides evidence that the evolution of the COVID-19 pandemic caused the measures taken by governments; however, we cannot find evidence of the reverse situation. This result suggests that the government measures were not very effective in controlling the pandemic. This does not necessarily imply that the government responses were useless. However, our results show a considerable lack of effectiveness, a lesson that governments should learn and correct if similar events occur again.

Suggested Citation

  • Lopez-Medoza, Hector & González-Álvarez, Maria A. & Montañés, Antonio, 2023. "Assessing the effectiveness of international government responses to the COVID-19 pandemic," MPRA Paper 117826, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:117826
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    1. Thomas Hale & Noam Angrist & Rafael Goldszmidt & Beatriz Kira & Anna Petherick & Toby Phillips & Samuel Webster & Emily Cameron-Blake & Laura Hallas & Saptarshi Majumdar & Helen Tatlow, 2021. "A global panel database of pandemic policies (Oxford COVID-19 Government Response Tracker)," Nature Human Behaviour, Nature, vol. 5(4), pages 529-538, April.
    2. David Meenagh & Patrick Minford, 2021. "A structural model of coronavirus behaviour for testing on data behaviour," Applied Economics, Taylor & Francis Journals, vol. 53(30), pages 3515-3534, June.
    3. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1988. "Estimating Vector Autoregressions with Panel Data," Econometrica, Econometric Society, vol. 56(6), pages 1371-1395, November.
    4. M. Hashem Pesaran, 2021. "General diagnostic tests for cross-sectional dependence in panels," Empirical Economics, Springer, vol. 60(1), pages 13-50, January.
    5. Michael R. M. Abrigo & Inessa Love, 2016. "Estimation of panel vector autoregression in Stata," Stata Journal, StataCorp LP, vol. 16(3), pages 778-804, September.
    6. Im, Kyung So & Pesaran, M. Hashem & Shin, Yongcheol, 2003. "Testing for unit roots in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 115(1), pages 53-74, July.
    7. M. Hashem Pesaran, 2015. "Testing Weak Cross-Sectional Dependence in Large Panels," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 1089-1117, December.
    8. John Gibson, 2022. "Hard, not early: putting the New Zealand Covid-19 response in context," New Zealand Economic Papers, Taylor & Francis Journals, vol. 56(1), pages 1-8, January.
    9. Yang, Qi-Cheng & Chen, Xia & Chang, Chun-Ping & Chen, Di & Hao, Yu, 2021. "What is the relationship between government response and COVID-19 pandemics? Global evidence of 118 countries," Structural Change and Economic Dynamics, Elsevier, vol. 59(C), pages 98-107.
    10. Vincenzo Alfano & Salvatore Ercolano, 2020. "The Efficacy of Lockdown Against COVID-19: A Cross-Country Panel Analysis," Applied Health Economics and Health Policy, Springer, vol. 18(4), pages 509-517, August.
    11. Pesaran, M. Hashem & Vanessa Smith, L. & Yamagata, Takashi, 2013. "Panel unit root tests in the presence of a multifactor error structure," Journal of Econometrics, Elsevier, vol. 175(2), pages 94-115.
    12. David E. Bloom & Michael Kuhn & Klaus Prettner, 2022. "Modern Infectious Diseases: Macroeconomic Impacts and Policy Responses," Journal of Economic Literature, American Economic Association, vol. 60(1), pages 85-131, March.
    13. Alfano, Vincenzo & Capasso, Salvatore & Ercolano, Salvatore & Goel, Rajeev K., 2022. "Death takes no bribes: Impact of perceived corruption on the effectiveness of non-pharmaceutical interventions at combating COVID-19," Social Science & Medicine, Elsevier, vol. 301(C).
    14. Mark Pingle, 2022. "Addressing threats like Covid: why we will tend to over-react and how we can do better," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 21(1), pages 9-23, June.
    15. Abel Brodeur & David Gray & Anik Islam & Suraiya Bhuiyan, 2021. "A literature review of the economics of COVID‐19," Journal of Economic Surveys, Wiley Blackwell, vol. 35(4), pages 1007-1044, September.
    16. Herby, Jonas & Jonung, Lars & Hanke, Steve, 2022. "A Literature Review and Meta-Analysis of the Effects of Lockdowns on COVID-19 Mortality – II," Studies in Applied Economics 210, The Johns Hopkins Institute for Applied Economics, Global Health, and the Study of Business Enterprise.
    17. Andrews, Donald W. K. & Lu, Biao, 2001. "Consistent model and moment selection procedures for GMM estimation with application to dynamic panel data models," Journal of Econometrics, Elsevier, vol. 101(1), pages 123-164, March.
    18. M. Hashem Pesaran, 2007. "A simple panel unit root test in the presence of cross-section dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 265-312.
    19. Vincenzo Alfano & Salvatore Ercolano, 2022. "Stay at Home! Governance Quality and Effectiveness of Lockdown," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 159(1), pages 101-123, January.
    20. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    21. Dergiades, Theologos & Milas, Costas & Panagiotidis, Theodore, 2022. "Unemployment claims during COVID-19 and economic support measures in the U.S," Economic Modelling, Elsevier, vol. 113(C).
    22. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    23. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    24. Douglas W. Allen, 2022. "Covid-19 Lockdown Cost/Benefits: A Critical Assessment of the Literature," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 29(1), pages 1-32, January.
    25. Nina Haug & Lukas Geyrhofer & Alessandro Londei & Elma Dervic & Amélie Desvars-Larrive & Vittorio Loreto & Beate Pinior & Stefan Thurner & Peter Klimek, 2020. "Ranking the effectiveness of worldwide COVID-19 government interventions," Nature Human Behaviour, Nature, vol. 4(12), pages 1303-1312, December.
    26. Alfano, Vincenzo & Ercolano, Salvatore & Cicatiello, Lorenzo, 2021. "School openings and the COVID-19 outbreak in Italy. A provincial-level analysis using the synthetic control method," Health Policy, Elsevier, vol. 125(9), pages 1200-1207.
    27. Michael R.M. Abrigo & Inessa Love, 2016. "Estimation of Panel Vector Autoregression in Stata: a Package of Programs," Working Papers 201602, University of Hawaii at Manoa, Department of Economics.
    28. Christian Bjørnskov, 2021. "Did Lockdown Work? An Economist’s Cross-Country Comparison," CESifo Economic Studies, CESifo Group, vol. 67(3), pages 318-331.
    29. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
    30. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    31. Alfano, Vincenzo & Ercolano, Salvatore & Pinto, Mauro, 2022. "Fighting the COVID pandemic: National policy choices in non-pharmaceutical interventions," Journal of Policy Modeling, Elsevier, vol. 44(1), pages 22-40.
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    More about this item

    Keywords

    Government response index; stringency indexes; Granger causality; incidence; SARS-CoV-2 infection; COVID-19;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • H0 - Public Economics - - General

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