IDEAS home Printed from https://ideas.repec.org/a/wly/japmet/v37y2022i1p187-209.html
   My bibliography  Save this article

Economic impact of the most drastic lockdown during COVID‐19 pandemic—The experience of Hubei, China

Author

Listed:
  • Xiao Ke
  • Cheng Hsiao

Abstract

This paper uses a panel data approach to assess the evolution of economic consequences of the drastic lockdown policy in the epicenter of COVID‐19—the Hubei Province of China during worldwide curbs on economic activity. We find that the drastic 76‐day COVID‐19 lockdown policy brought huge negative impacts on Hubei's economy. In 2020:q1, the lockdown quarter, the treatment effect on GDP was about 37% of the counterfactual. However, the drastic lockdown also brought the spread of COVID‐19 under control in little more than two months. After the government lifted the lockdown in early April, the economy quickly recovered with the exception of passenger transportation sector which rebounded not as quickly as the rest of the general economy.

Suggested Citation

  • Xiao Ke & Cheng Hsiao, 2022. "Economic impact of the most drastic lockdown during COVID‐19 pandemic—The experience of Hubei, China," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 187-209, January.
    • Handle: RePEc:wly:japmet:v:37:y:2022:i:1:p:187-209
    DOI: 10.1002/jae.2871
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/jae.2871
    Download Restriction: no
    File URL: https://libkey.io/10.1002/jae.2871?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Matthew A. Cole & Robert J R Elliott & Bowen Liu, 2020. "The Impact of the Wuhan Covid-19 Lockdown on Air Pollution and Health: A Machine Learning and Augmented Synthetic Control Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 76(4), pages 553-580, August.
    2. Martin S Eichenbaum & Sergio Rebelo & Mathias Trabandt, 2021. "The Macroeconomics of Epidemics [Economic activity and the spread of viral diseases: Evidence from high frequency data]," Review of Financial Studies, Society for Financial Studies, vol. 34(11), pages 5149-5187.
    3. P. C. B. Phillips & S. N. Durlauf, 1986. "Multiple Time Series Regression with Integrated Processes," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 53(4), pages 473-495.
    4. Hsiao, Cheng, 1982. "Autoregressive modeling and causal ordering of economic variables," Journal of Economic Dynamics and Control, Elsevier, vol. 4(1), pages 243-259, November.
    5. 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.
    6. Xu, Yiqing, 2017. "Generalized Synthetic Control Method: Causal Inference with Interactive Fixed Effects Models," Political Analysis, Cambridge University Press, vol. 25(1), pages 57-76, January.
    7. Bai, ChongEn & Li, Qi & Ouyang, Min, 2014. "Property taxes and home prices: A tale of two cities," Journal of Econometrics, Elsevier, vol. 180(1), pages 1-15.
    8. Fang, Hanming & Wang, Long & Yang, Yang, 2020. "Human mobility restrictions and the spread of the Novel Coronavirus (2019-nCoV) in China," Journal of Public Economics, Elsevier, vol. 191(C).
    9. Li, Kathleen T. & Bell, David R., 2017. "Estimation of average treatment effects with panel data: Asymptotic theory and implementation," Journal of Econometrics, Elsevier, vol. 197(1), pages 65-75.
    10. Eichenbaum, Martin S. & Rebelo, Sergio & Trabandt, Mathias, 2022. "The macroeconomics of testing and quarantining," Journal of Economic Dynamics and Control, Elsevier, vol. 138(C).
    11. Abadie, Alberto & Diamond, Alexis & Hainmueller, Jens, 2010. "Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 493-505.
    12. Oscar Jorda & Sanjay R. Singh & Alan M. Taylor, 2022. "Longer-Run Economic Consequences of Pandemics," The Review of Economics and Statistics, MIT Press, vol. 104(1), pages 166-175, March.
    13. James H. Stock & Mark W. Watson, 2005. "Implications of Dynamic Factor Models for VAR Analysis," NBER Working Papers 11467, National Bureau of Economic Research, Inc.
    14. W. Erwin Diewert & Kevin J. Fox, 2020. "Measuring Real Consumption and CPI Bias under Lockdown Conditions," NBER Working Papers 27144, National Bureau of Economic Research, Inc.
    15. Ouyang, Min & Peng, Yulei, 2015. "The treatment-effect estimation: A case study of the 2008 economic stimulus package of China," Journal of Econometrics, Elsevier, vol. 188(2), pages 545-557.
    16. Cheng Hsiao & H. Steve Ching & Shui Ki Wan, 2012. "A Panel Data Approach For Program Evaluation: Measuring The Benefits Of Political And Economic Integration Of Hong Kong With Mainland China," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(5), pages 705-740, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. González, Marta Ramos & Ureña, Antonio Partal & Fernández-Aguado, Pilar Gómez, 2023. "Forecasting for regulatory credit loss derived from the COVID-19 pandemic: A machine learning approach," Research in International Business and Finance, Elsevier, vol. 64(C).
    2. Deng, Yongheng & Meng, Lina & Zhou, Yinggang, 2022. "The effectiveness and costs of nonpharmaceutical interventions for COVID-19 containment: A border discontinuous difference-in-difference approach," China Economic Review, Elsevier, vol. 75(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Carlos Viana de Carvalho & Ricardo Masini & Marcelo Cunha Medeiros, 2016. "The perils of Counterfactual Analysis with Integrated Processes," Textos para discussão 654, Department of Economics PUC-Rio (Brazil).
    2. Carvalho, Carlos & Masini, Ricardo & Medeiros, Marcelo C., 2018. "ArCo: An artificial counterfactual approach for high-dimensional panel time-series data," Journal of Econometrics, Elsevier, vol. 207(2), pages 352-380.
    3. Anderson, Heather M. & Gao, Jiti & Turnip, Guido & Vahid, Farshid & Wei, Wei, 2023. "Estimating the effect of an EU-ETS type scheme in Australia using a synthetic treatment approach," Energy Economics, Elsevier, vol. 125(C).
    4. Shi, Zhentao & Huang, Jingyi, 2023. "Forward-selected panel data approach for program evaluation," Journal of Econometrics, Elsevier, vol. 234(2), pages 512-535.
    5. Hongjun Li & Zheng Li & Cheng Hsiao, 2023. "Assessing the impacts of pandemic and the increase in minimum down payment rate on Shanghai housing prices," Empirical Economics, Springer, vol. 64(6), pages 2661-2682, June.
    6. Viviano, Davide & Bradic, Jelena, 2023. "Synthetic Learner: Model-free inference on treatments over time," Journal of Econometrics, Elsevier, vol. 234(2), pages 691-713.
    7. Xingyu Li & Yan Shen & Qiankun Zhou, 2022. "Confidence Intervals of Treatment Effects in Panel Data Models with Interactive Fixed Effects," Papers 2202.12078, arXiv.org.
    8. Louis-Philippe Beland & Abel Brodeur & Taylor Wright, 2020. "COVID-19, Stay-at-Home Orders and Employment: Evidence from CPS Data," Carleton Economic Papers 20-04, Carleton University, Department of Economics, revised 19 May 2020.
    9. Qi Li & Wei Long, 2018. "Do parole abolition and Truth-in-Sentencing deter violent crimes in Virginia?," Empirical Economics, Springer, vol. 55(4), pages 2027-2045, December.
    10. Du, Zaichao & Pei, Pei, 2021. "A simple and robust counterfactual impact evaluation," Economics Letters, Elsevier, vol. 207(C).
    11. Howard Bodenhorn, 2020. "Business in a Time of Spanish Influenza," NBER Working Papers 27495, National Bureau of Economic Research, Inc.
    12. Ke, Xiao & Chen, Haiqiang & Hong, Yongmiao & Hsiao, Cheng, 2017. "Do China's high-speed-rail projects promote local economy?—New evidence from a panel data approach," China Economic Review, Elsevier, vol. 44(C), pages 203-226.
    13. Asli Demirgüç‐Kunt & Michael Lokshin & Iván Torre, 2021. "The sooner, the better: The economic impact of non‐pharmaceutical interventions during the early stage of the COVID‐19 pandemic," Economics of Transition and Institutional Change, John Wiley & Sons, vol. 29(4), pages 551-573, October.
    14. Bianchi, Francesco & Bianchi, Giada & Song, Dongho, 2023. "The long-term impact of the COVID-19 unemployment shock on life expectancy and mortality rates," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    15. Callaway, Brantly & Karami, Sonia, 2023. "Treatment effects in interactive fixed effects models with a small number of time periods," Journal of Econometrics, Elsevier, vol. 233(1), pages 184-208.
    16. Bruno Ferman & Cristine Pinto, 2021. "Synthetic controls with imperfect pretreatment fit," Quantitative Economics, Econometric Society, vol. 12(4), pages 1197-1221, November.
    17. Li, Hongjun & Li, Qi & Shi, Yutang, 2017. "Determining the number of factors when the number of factors can increase with sample size," Journal of Econometrics, Elsevier, vol. 197(1), pages 76-86.
    18. Shui Ki Wan & Cheng Hsiao & Qiankun Zhou, 2021. "Can a time-varying structure provide a more robust panel construction of counterfactuals-straitjacket or straitjackets?," Empirical Economics, Springer, vol. 60(1), pages 113-129, January.
    19. Gao, Yichen & Li, Hongjun & Li, Qi, 2022. "The misalignments in Chinese real effective exchange rate from 1994 to 2020: A counterfactual analysis," China Economic Review, Elsevier, vol. 75(C).
    20. Shih-Chih Chen & Jianing Hou & De Xiao, 2018. "“One Belt, One Road” Initiative to Stimulate Trade in China: A Counter-Factual Analysis," Sustainability, MDPI, vol. 10(9), pages 1-13, September.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:japmet:v:37:y:2022:i:1:p:187-209. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/0883-7252/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.