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The Causal Effects of Lockdown Policies on Health and Macroeconomic Outcomes

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  • Jonas E. Arias
  • Jesús Fernández- Villaverde
  • Juan F. Rubio-Ramírez
  • Minchul Shin

Abstract

We assess the causal impact of pandemic-induced lockdowns on health and macroeconomic outcomes and measure the trade-off between containing the spread of a pandemic and economic activity. To do so, we estimate an epidemiological model with time-varying parameters and use its output as information for estimating SVARs and LPs that quantify the causal effects of nonpharmaceutical policy interventions. We apply our approach to Belgian data for the COVID-19 pandemic during 2020. We find that additional government-mandated mobility curtailments would have reduced deaths at a very small cost in terms of GDP.

Suggested Citation

  • Jonas E. Arias & Jesús Fernández- Villaverde & Juan F. Rubio-Ramírez & Minchul Shin, 2023. "The Causal Effects of Lockdown Policies on Health and Macroeconomic Outcomes," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(3), pages 287-319, July.
    • Handle: RePEc:aea:aejmac:v:15:y:2023:i:3:p:287-319
    DOI: 10.1257/mac.20210367
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    1. Victor Aguirregabiria & Jiaying Gu & Yao Luo & Pedro Mira, 2020. "A Dynamic Structural Model of Virus Diffusion and Network Production: A First Report," Working Papers tecipa-665, University of Toronto, Department of Economics.
    2. James H. Stock & Mark W. Watson, 2018. "Identification and Estimation of Dynamic Causal Effects in Macroeconomics Using External Instruments," Economic Journal, Royal Economic Society, vol. 128(610), pages 917-948, May.
    3. Chernozhukov, Victor & Kasahara, Hiroyuki & Schrimpf, Paul, 2021. "Causal impact of masks, policies, behavior on early covid-19 pandemic in the U.S," Journal of Econometrics, Elsevier, vol. 220(1), pages 23-62.
    4. Manski, Charles F. & Molinari, Francesca, 2021. "Estimating the COVID-19 infection rate: Anatomy of an inference problem," Journal of Econometrics, Elsevier, vol. 220(1), pages 181-192.
    5. Goolsbee, Austan & Syverson, Chad, 2021. "Fear, lockdown, and diversion: Comparing drivers of pandemic economic decline 2020," Journal of Public Economics, Elsevier, vol. 193(C).
    6. Lutz Kilian & Daniel P. Murphy, 2012. "Why Agnostic Sign Restrictions Are Not Enough: Understanding The Dynamics Of Oil Market Var Models," Journal of the European Economic Association, European Economic Association, vol. 10(5), pages 1166-1188, October.
    7. Arias, Jonas E. & Caldara, Dario & Rubio-Ramírez, Juan F., 2019. "The systematic component of monetary policy in SVARs: An agnostic identification procedure," Journal of Monetary Economics, Elsevier, vol. 101(C), pages 1-13.
    8. Toulis, Panos, 2021. "Estimation of Covid-19 prevalence from serology tests: A partial identification approach," Journal of Econometrics, Elsevier, vol. 220(1), pages 193-213.
    9. Simon Gilchrist & Egon Zakrajsek, 2012. "Credit Spreads and Business Cycle Fluctuations," American Economic Review, American Economic Association, vol. 102(4), pages 1692-1720, June.
    10. Christopher A. Sims & Tao Zha, 2006. "Were There Regime Switches in U.S. Monetary Policy?," American Economic Review, American Economic Association, vol. 96(1), pages 54-81, March.
    11. Sang-Wook (Stanley) Cho, 2020. "Quantifying the impact of nonpharmaceutical interventions during the COVID-19 outbreak: The case of Sweden," The Econometrics Journal, Royal Economic Society, vol. 23(3), pages 323-344.
    12. Dario Caldara & Christophe Kamps, 2017. "The Analytics of SVARs: A Unified Framework to Measure Fiscal Multipliers," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 84(3), pages 1015-1040.
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    Cited by:

    1. Xiwen Bai & Jesús Fernández-Villaverde & Yiliang Li & Francesco Zanetti, 2024. "The Causal Effects of Global Supply Chain Disruptions on Macroeconomic Outcomes: Evidence and Theory," Economics Series Working Papers 1033, University of Oxford, Department of Economics.
    2. Ida Johnsson & M. Hashem Pesaran & Cynthia Fan Yang, 2023. "Structural Econometric Estimation of the Basic Reproduction Number for Covid-19 across U.S. States and Selected Countries," CESifo Working Paper Series 10659, CESifo.
    3. Christis Katsouris, 2023. "Structural Analysis of Vector Autoregressive Models," Papers 2312.06402, arXiv.org, revised Feb 2024.
    4. Hilde C. Bjørnland & Malin C. Jensen & Leif Anders Thorsrud, 2023. "Business Cycle and Health Dynamics during the COVID-19 Pandemic. A Scandinavian Perspective," Working Papers No 15/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.

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    More about this item

    JEL classification:

    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production
    • H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I15 - Health, Education, and Welfare - - Health - - - Health and Economic Development
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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