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The sooner the better: lives saved by the lockdown during the COVID-19 outbreak. The case of Italy

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  • Roy Cerqueti
  • Raffaella Coppier
  • Alessandro Girardi
  • Marco Ventura

Abstract

SummaryThis paper estimates the effects of non-pharmaceutical interventions – mainly, the lockdown – on the COVID-19 mortality rate for the case of Italy, the first Western country to impose a national shelter-in-place order. We use a new estimator, the augmented synthetic control method (ASCM), that overcomes some limits of the standard synthetic control method (SCM). The results are twofold. From a methodological point of view, the ASCM outperforms the SCM in that the latter cannot select a valid donor set, assigning all the weights to only one country (Spain) while placing zero weights to all the remaining. From an empirical point of view, we find strong evidence of the effectiveness of non-pharmaceutical interventions in avoiding losses of human lives in Italy: conservative estimates indicate that the policy saved in total more than 21,000 human lives.

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  • Roy Cerqueti & Raffaella Coppier & Alessandro Girardi & Marco Ventura, 2022. "The sooner the better: lives saved by the lockdown during the COVID-19 outbreak. The case of Italy," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 46-70.
  • Handle: RePEc:oup:emjrnl:v:25:y:2022:i:1:p:46-70.
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    1. Luca Bonacini & Giovanni Gallo & Fabrizio Patriarca, 2021. "Identifying policy challenges of COVID-19 in hardly reliable data and judging the success of lockdown measures," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(1), pages 275-301, January.
    2. Eli Ben-Michael & Avi Feller & Jesse Rothstein, 2021. "The Augmented Synthetic Control Method," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1789-1803, October.
    3. 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.
    4. Mónica Amador-Jiménez & Naomi Millner & Charles Palmer & R. Toby Pennington & Lorenzo Sileci, 2020. "The Unintended Impact of Colombia’s Covid-19 Lockdown on Forest Fires," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 76(4), pages 1081-1105, August.
    5. Garret Christensen & Edward Miguel, 2018. "Transparency, Reproducibility, and the Credibility of Economics Research," Journal of Economic Literature, American Economic Association, vol. 56(3), pages 920-980, September.
    6. Dmitry Arkhangelsky & Susan Athey & David A. Hirshberg & Guido W. Imbens & Stefan Wager, 2021. "Synthetic Difference-in-Differences," American Economic Review, American Economic Association, vol. 111(12), pages 4088-4118, December.
    7. Muhummad Amjad & Vishal Misra & Devavrat Shah & Dennis Shen, 2019. "mRSC: Multi-dimensional Robust Synthetic Control," Papers 1905.06400, arXiv.org, revised Sep 2019.
    8. Mitze, Timo & Kosfeld, Reinhold & Rode, Johannes & Wälde, Klaus, 2020. "Face masks considerably reduce COVID-19 cases in Germany," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 124130, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    9. Franco Peracchi & Daniele Terlizzese, 2020. "Estimating the prevalence of the COVID-19 infection, with an application to Italy," EIEF Working Papers Series 2013, Einaudi Institute for Economics and Finance (EIEF), revised May 2020.
    10. Wolf, Nikolaus & Eckardt, Matthias, 2020. "Covid-19 across European Regions: the Role of Border Controls," CEPR Discussion Papers 15178, C.E.P.R. Discussion Papers.
    11. Mitze, Timo & Kosfeld, Reinhold & Rode, Johannes & Wälde, Klaus, 2020. "Face masks considerably reduce COVID-19 cases in Germany," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 124587, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    12. Mitze, Timo & Kosfeld, Reinhold & Rode, Johannes & Wälde, Klaus, 2020. "Face Masks Considerably Reduce COVID-19 Cases in Germany: A Synthetic Control Method Approach," IZA Discussion Papers 13319, Institute of Labor Economics (IZA).
    13. Ozkan Eren & Serkan Ozbeklik, 2016. "What Do Right‐to‐Work Laws Do? Evidence from a Synthetic Control Method Analysis," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 35(1), pages 173-194, January.
    14. Bruno Ferman & Cristine Pinto & Vitor Possebom, 2020. "Cherry Picking with Synthetic Controls," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 39(2), pages 510-532, March.
    15. Lee, Jongkwan & Yang, Hee-Seung, 2022. "Pandemic and employment: Evidence from COVID-19 in South Korea," Journal of Asian Economics, Elsevier, vol. 78(C).
    16. 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.
    17. Alberto Abadie & Javier Gardeazabal, 2003. "The Economic Costs of Conflict: A Case Study of the Basque Country," American Economic Review, American Economic Association, vol. 93(1), pages 113-132, March.
    18. Irene Botosaru & Bruno Ferman, 2019. "On the role of covariates in the synthetic control method," The Econometrics Journal, Royal Economic Society, vol. 22(2), pages 117-130.
    19. Abel Brodeur & Mathias Lé & Marc Sangnier & Yanos Zylberberg, 2016. "Star Wars: The Empirics Strike Back," American Economic Journal: Applied Economics, American Economic Association, vol. 8(1), pages 1-32, January.
    20. 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.
    21. Eduardo Cavallo & Sebastian Galiani & Ilan Noy & Juan Pantano, 2013. "Catastrophic Natural Disasters and Economic Growth," The Review of Economics and Statistics, MIT Press, vol. 95(5), pages 1549-1561, December.
    22. Dube, Arindrajit & Zipperer, Ben, 2015. "Pooling Multiple Case Studies Using Synthetic Controls: An Application to Minimum Wage Policies," IZA Discussion Papers 8944, Institute of Labor Economics (IZA).
    23. Abadie, Alberto & Imbens, Guido W., 2011. "Bias-Corrected Matching Estimators for Average Treatment Effects," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 1-11.
    24. Augusto Cerqua & Roberta Di Stefano & Marco Letta & Sara Miccoli, 2021. "Local mortality estimates during the COVID-19 pandemic in Italy," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(4), pages 1189-1217, October.
    25. Benjamin Born & Alexander M Dietrich & Gernot J Müller, 2021. "The lockdown effect: A counterfactual for Sweden," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-13, April.
    26. Sang-Wook (Stanley) Cho, 0. "Quantifying the impact of nonpharmaceutical interventions during the COVID-19 outbreak: The case of Sweden," Econometrics Journal, Royal Economic Society, vol. 23(3), pages 323-344.
    27. Matias D. Cattaneo & Yingjie Feng & Rocio Titiunik, 2021. "Prediction Intervals for Synthetic Control Methods," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1865-1880, October.
    28. Amuedo-Dorantes, Catalina & Borra, Cristina & Rivera Garrido, Noelia & Sevilla, Almudena, 2020. "Timing is Everything when Fighting a Pandemic: COVID-19 Mortality in Spain," IZA Discussion Papers 13316, Institute of Labor Economics (IZA).
    29. Andrew I. Friedson & Drew McNichols & Joseph J. Sabia & Dhaval Dave, 2020. "Did California’s Shelter-in-Place Order Work? Early Coronavirus-Related Public Health Effects," NBER Working Papers 26992, National Bureau of Economic Research, Inc.
    30. Sá, Filipa, 2020. "Socioeconomic Determinants of Covid-19 Infections and Mortality: Evidence from England and Wales," CEPR Discussion Papers 14781, C.E.P.R. Discussion Papers.
    31. Susan Athey & Guido W. Imbens, 2017. "The State of Applied Econometrics: Causality and Policy Evaluation," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 3-32, Spring.
    32. Martin Huber & Henrika Langen, 2020. "Timing matters: the impact of response measures on COVID-19-related hospitalization and death rates in Germany and Switzerland," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 156(1), pages 1-19, December.
    33. 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.
    34. Michael W. Robbins & Jessica Saunders & Beau Kilmer, 2017. "A Framework for Synthetic Control Methods With High-Dimensional, Micro-Level Data: Evaluating a Neighborhood-Specific Crime Intervention," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 109-126, January.
    35. Sa, Filipa, 2020. "Socioeconomic Determinants of COVID-19 Infections and Mortality: Evidence from England and Wales," IZA Policy Papers 159, Institute of Labor Economics (IZA).
    36. Alberto Abadie, 2021. "Using Synthetic Controls: Feasibility, Data Requirements, and Methodological Aspects," Journal of Economic Literature, American Economic Association, vol. 59(2), pages 391-425, June.
    37. 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.
    38. Susan Athey & Guido W. Imbens & Stefan Wager, 2018. "Approximate residual balancing: debiased inference of average treatment effects in high dimensions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 80(4), pages 597-623, September.
    39. 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.
    40. G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1.
    41. Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881, September.
    42. Alberto Abadie & Jérémy L’Hour, 2021. "A Penalized Synthetic Control Estimator for Disaggregated Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1817-1834, October.
    43. Amuedo-Dorantes, Catalina & Borra, Cristina & Rivera-Garrido, Noelia & Sevilla, Almudena, 2021. "Early adoption of non-pharmaceutical interventions and COVID-19 mortality," Economics & Human Biology, Elsevier, vol. 42(C).
    44. Ting Tian & Jianbin Tan & Wenxiang Luo & Yukang Jiang & Minqiong Chen & Songpan Yang & Canhong Wen & Wenliang Pan & Xueqin Wang, 2021. "The Effects of Stringent and Mild Interventions for Coronavirus Pandemic," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(534), pages 481-491, April.
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    2. Feindouno, Sosso & Arcand, Jean-Louis & Guillaumont, Patrick, 2024. "COVID-19's death transfer to Sub-Saharan Africa," Social Science & Medicine, Elsevier, vol. 340(C).
    3. Sarah Kelley & M. D. R. Evans & Jonathan Kelley, 2023. "Happily Distant or Bitter Medicine? The Impact of Social Distancing Preferences, Behavior, and Emotional Costs on Subjective Wellbeing During the Epidemic," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 18(1), pages 115-162, February.
    4. Deiana, Claudio & Geraci, Andrea & Mazzarella, Gianluca & Sabatini, Fabio, 2022. "Can relief measures nudge compliance in a public health crisis? Evidence from a kinked fiscal policy rule," Journal of Economic Behavior & Organization, Elsevier, vol. 202(C), pages 407-428.
    5. Girardi, Alessandro & Ventura, Marco, 2023. "The cost of waiting and the death toll in Italy during the first wave of the covid-19 pandemic," Health Policy, Elsevier, vol. 134(C).
    6. Cerqueti, Roy & Tramontana, Fabio & Ventura, Marco, 2022. "The complex interplay between COVID-19 and economic activity," Mathematical Social Sciences, Elsevier, vol. 119(C), pages 97-107.

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