IDEAS home Printed from https://ideas.repec.org/a/eee/ecanpo/v79y2023icp376-394.html

The effectiveness of COVID deaths to COVID policies: A robust conditional approach

Author

Listed:
  • Gearhart, Richard
  • Michieka, Nyakundi
  • Anders, Anne

Abstract

This paper examines the effectiveness of four major COVID-19 social distancing policies, (i) shelter-in-place orders (SIPO), (ii) non-essential business closures, (iii) mandatory quarantine for travelers, and (iv) bans on large gatherings, on both COVID cases and COVID deaths. Results indicate that states are highly ineffective in producing the fraction of the population that does not have COVID-19 or the fraction of the population that does not die from COVID-19. We find that having any form of social distancing policies increases the fraction of the population not considered a positive COVID-19 case by 23.5 percentage points. Results also show that having any of the four major social distancing policies reduces the fraction of the population who has died of COVID-19 by 1.3 percentage points between March 1, 2020 and September 1, 2020; during the first 100 days, effectiveness would improve by 2.1 percentage points. Evidence suggests that there is no effective uniform national COVID-19 social distancing policy. Furthermore, conditional efficiency regressions after 100 days suggest that behavioral noncompliance and premature expiration of social distancing policies both negatively impact effectiveness. Partial regression plots suggest that bans on large gatherings and the closure of non-essential businesses were the two most impactful COVID-19 social distancing policies.

Suggested Citation

  • Gearhart, Richard & Michieka, Nyakundi & Anders, Anne, 2023. "The effectiveness of COVID deaths to COVID policies: A robust conditional approach," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 376-394.
    • Handle: RePEc:eee:ecanpo:v:79:y:2023:i:c:p:376-394
    DOI: 10.1016/j.eap.2023.06.026
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0313592623001479
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eap.2023.06.026?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
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Coibion, Olivier & Gorodnichenko, Yuriy & Weber, Michael, 2020. "Labor Markets During the Covid-19 Crisis: A Preliminary View," Department of Economics, Working Paper Series qt7rx7t91p, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    2. Tom Kompas & R Quentin Grafton & Tuong Nhu Che & Long Chu & James Camac, 2021. "Health and economic costs of early and delayed suppression and the unmitigated spread of COVID-19: The case of Australia," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-18, June.
    3. Carola Binder, 2020. "Coronavirus Fears and Macroeconomic Expectations," The Review of Economics and Statistics, MIT Press, vol. 102(4), pages 721-730, October.
    4. Christopher Avery & William Bossert & Adam Thomas Clark & Glenn Ellison & Sara Ellison, 2020. "Policy Implications of Models of the Spread of Coronavirus: Perspectives and Opportunities for Economists," CESifo Working Paper Series 8293, CESifo.
    5. Wheelock, David C. & Wilson, Paul W., 2008. "Non-parametric, unconditional quantile estimation for efficiency analysis with an application to Federal Reserve check processing operations," Journal of Econometrics, Elsevier, vol. 145(1-2), pages 209-225, July.
    6. Richard Gearhart & Lyudmyla Sonchak-Ardan & Nyakundi Michieka, 2022. "The efficiency of COVID cases to COVID policies: a robust conditional approach," Empirical Economics, Springer, vol. 63(6), pages 2903-2948, December.
    7. Léopold Simar & Paul Wilson, 2011. "Two-stage DEA: caveat emptor," Journal of Productivity Analysis, Springer, vol. 36(2), pages 205-218, October.
    8. Dhaval Dave & Andrew I. Friedson & Kyutaro Matsuzawa & Joseph J. Sabia, 2021. "When Do Shelter‐In‐Place Orders Fight Covid‐19 Best? Policy Heterogeneity Across States And Adoption Time," Economic Inquiry, Western Economic Association International, vol. 59(1), pages 29-52, January.
    9. Kristof De Witte & Mika Kortelainen, 2013. "What explains the performance of students in a heterogeneous environment? Conditional efficiency estimation with continuous and discrete environmental variables," Applied Economics, Taylor & Francis Journals, vol. 45(17), pages 2401-2412, June.
    10. Luiz Brotherhood & Philipp Kircher & Cezar Santos & Michèle Tertilt, 2020. "An Economic Model of the Covid-19 Epidemic: The Importance of Testing and Age-Specific Policies," CESifo Working Paper Series 8316, CESifo.
    11. Richard Gearhart, 2016. "The robustness of cross-country healthcare rankings among homogeneous OECD countries," Journal of Applied Economics, Universidad del CEMA, vol. 19, pages 113-144, May.
    12. 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]," The Review of Financial Studies, Society for Financial Studies, vol. 34(11), pages 5149-5187.
    13. Thunström, Linda & Newbold, Stephen C. & Finnoff, David & Ashworth, Madison & Shogren, Jason F., 2020. "The Benefits and Costs of Using Social Distancing to Flatten the Curve for COVID-19," Journal of Benefit-Cost Analysis, Cambridge University Press, vol. 11(2), pages 179-195, July.
    14. Cazals, Catherine & Florens, Jean-Pierre & Simar, Leopold, 2002. "Nonparametric frontier estimation: a robust approach," Journal of Econometrics, Elsevier, vol. 106(1), pages 1-25, January.
    15. Christopher Avery & William Bossert & Adam Clark & Glenn Ellison & Sara Fisher Ellison, 2020. "Policy Implications of Models of the Spread of Coronavirus: Perspectives and Opportunities for Economists," NBER Working Papers 27007, National Bureau of Economic Research, Inc.
    16. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    17. Jeffrey D Sachs & Salim S Abdool Karim & Lara Aknin & Joseph Allen & Kirsten Brosbol & Francesca Colombo & Gabriela Cuevas Barron & Maria Fernanda Espinosa & Vitor Gaspar & Alejandro Gaviria & Andy Ha, 2022. "The Lancet Commission on lessons for the future from the COVID-19 pandemic," DEOS Working Papers 2226, Athens University of Economics and Business.
    18. Wheelock, David C. & Wilson, Paul W., 2009. "Robust Nonparametric Quantile Estimation of Efficiency and Productivity Change in U.S. Commercial Banking, 1985–2004," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(3), pages 354-368.
    19. 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.
    20. Fried, Harold O. & Lovell, C. A. Knox & Schmidt, Shelton S. (ed.), 2008. "The Measurement of Productive Efficiency and Productivity Growth," OUP Catalogue, Oxford University Press, number 9780195183528.
    21. Coibion, Olivier & Gorodnichenko, Yuriy & Weber, Michael, 2025. "The cost of the COVID-19 crisis: Lockdowns, macroeconomic expectations, and consumer spending," Journal of Economic Behavior & Organization, Elsevier, vol. 229(C).
    22. Brotherhood, Luiz & Kircher, Philipp & Santos, Cezar & Tertilt, Michèle, 2020. "An economic model of the Covid-19 epidemic: The importance of testing and age-specific policies," CEPR Discussion Papers 14695, C.E.P.R. Discussion Papers.
    23. Zachary A. Bethune & Anton Korinek, 2020. "Covid-19 Infection Externalities: Trading Off Lives vs. Livelihoods," NBER Working Papers 27009, National Bureau of Economic Research, Inc.
    24. Walmsley, Terrie & Rose, Adam & John, Richard & Wei, Dan & Hlávka, Jakub P. & Machado, Juan & Byrd, Katie, 2023. "Macroeconomic consequences of the COVID-19 pandemic," Economic Modelling, Elsevier, vol. 120(C).
    25. David Berger & Kyle Herkenhoff & Chengdai Huang & Simon Mongey, 2022. "Testing and Reopening in an SEIR Model," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 43, pages 1-21, January.
    26. Cinzia Daraio & Léopold Simar, 2005. "Introducing Environmental Variables in Nonparametric Frontier Models: a Probabilistic Approach," Journal of Productivity Analysis, Springer, vol. 24(1), pages 93-121, September.
    27. Krishna Regmi & Cho Mar Lwin, 2021. "Factors Associated with the Implementation of Non-Pharmaceutical Interventions for Reducing Coronavirus Disease 2019 (COVID-19): A Systematic Review," IJERPH, MDPI, vol. 18(8), pages 1-27, April.
    28. Brotherhood, Luiz & Kircher, Philipp & Santos, Cezar & Tertilt, Michèle, 2020. "An economic model of the Covid-19 epidemic: The importance of testing and age-specific policies," CEPR Discussion Papers 14695, C.E.P.R. Discussion Papers.
    29. Mark J Siedner & Guy Harling & Zahra Reynolds & Rebecca F Gilbert & Sebastien Haneuse & Atheendar S Venkataramani & Alexander C Tsai, 2020. "Social distancing to slow the US COVID-19 epidemic: Longitudinal pretest–posttest comparison group study," PLOS Medicine, Public Library of Science, vol. 17(8), pages 1-12, August.
    30. Daniel L. Millimet & Christopher F. Parmeter, 2022. "COVID‐19 severity: A new approach to quantifying global cases and deaths," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 1178-1215, July.
    31. Breitenbach, Marthinus C & Ngobeni, Victor & Ayte, Goodness, 2020. "The first 100 days of COVID-19 coronavirus – How efficient did country health systems perform to flatten the curve in the first wave?," MPRA Paper 8872, University Library of Munich, Germany.
    32. repec:rza:wpaper:826 is not listed on IDEAS
    33. Breitenbach, Marthinus C & Ngobeni, Victor & Aye, Goodness C, 2020. "Global Healthcare Resource Efficiency in the Management of COVID-19 Death and Infection Prevalence Rates," MPRA Paper 104814, University Library of Munich, Germany.
    34. Richard Gearhart, 2016. "The Robustness of Cross-Country Healthcare Rankings Among Homogeneous Oecd Countries," Journal of Applied Economics, Taylor & Francis Journals, vol. 19(1), pages 113-143, May.
    35. Cinzia Daraio & Léopold Simar, 2007. "Conditional nonparametric frontier models for convex and nonconvex technologies: a unifying approach," Journal of Productivity Analysis, Springer, vol. 28(1), pages 13-32, October.
    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. Changsaar CHAI, 2023. "Navigating the Path to Construction 4.0: Policies, Challenges, and Strategies in Malaysian Construction Industry ," GATR Journals jber241, Global Academy of Training and Research (GATR) Enterprise.

    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. Richard Gearhart & Lyudmyla Sonchak-Ardan & Nyakundi Michieka, 2022. "The efficiency of COVID cases to COVID policies: a robust conditional approach," Empirical Economics, Springer, vol. 63(6), pages 2903-2948, December.
    2. Gearhart, Richard S. & Michieka, Nyakundi M., 2018. "A comparison of the robust conditional order-m estimation and two stage DEA in measuring healthcare efficiency among California counties," Economic Modelling, Elsevier, vol. 73(C), pages 395-406.
    3. Gearhart, Richard & Michieka, Nyakundi, 2019. "Natural resource abundance and healthcare efficiency in Appalachia: A robust conditional approach," Energy Policy, Elsevier, vol. 129(C), pages 985-996.
    4. Arthur S. Kuchenbecker & Hudson S. Torrent & Flavio A. Ziegelmann, 2025. "Measuring and explaining efficiency of pre-vaccine country responses to COVID-19 pandemic: a conditional robust nonparametric approach," Empirical Economics, Springer, vol. 68(1), pages 107-137, January.
    5. Gearhart Richard, 2019. "The Impact of Secondary Environmental Variables on OECD Healthcare Efficiency: A Robust Conditional Approach," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 19(2), pages 1-16, April.
    6. Cordero Ferrera, Jose Manuel & Alonso Morán, Edurne & Nuño Solís, Roberto & Orueta, Juan F. & Souto Arce, Regina, 2013. "Efficiency assessment of primary care providers: A conditional nonparametric approach," MPRA Paper 51926, University Library of Munich, Germany.
    7. Bisin, Alberto & Moro, Andrea, 2022. "Spatial‐SIR with network structure and behavior: Lockdown rules and the Lucas critique," Journal of Economic Behavior & Organization, Elsevier, vol. 198(C), pages 370-388.
    8. Calogero Guccio & Marco Martorana & Isidoro Mazza & Giacomo Pignataro & Ilde Rizzo, 2020. "An analysis of the efficiency of Italian museums using a generalised conditional efficiency model," ACEI Working Paper Series AWP-06-2020, Association for Cultural Economics International, revised Feb 2020.
    9. Martin F. Quaas & Jasper N. Meya & Hanna Schenk & Björn Bos & Moritz A. Drupp & Till Requate, 2020. "The Social Cost of Contacts: Theory and Evidence for the Covid-19 Pandemic in Germany," CESifo Working Paper Series 8347, CESifo.
    10. Tsutomu Watanabe & Tomoyoshi Yabu, 2021. "Japan’s voluntary lockdown: further evidence based on age-specific mobile location data," The Japanese Economic Review, Springer, vol. 72(3), pages 333-370, July.
    11. Cordero, José Manuel & Alonso-Morán, Edurne & Nuño-Solinis, Roberto & Orueta, Juan F. & Arce, Regina Sauto, 2015. "Efficiency assessment of primary care providers: A conditional nonparametric approach," European Journal of Operational Research, Elsevier, vol. 240(1), pages 235-244.
    12. Calogero Guccio & Marco Martorana & Isidoro Mazza & Giacomo Pignataro & Ilde Rizzo, 2019. "An analysis of the efficiency of Italian museums using a generalised conditional efficiency model," ACEI Working Paper Series AWP-06-2019, Association for Cultural Economics International, revised Dec 2019.
    13. Shami, Labib & Lazebnik, Teddy, 2022. "Economic aspects of the detection of new strains in a multi-strain epidemiological–mathematical model," Chaos, Solitons & Fractals, Elsevier, vol. 165(P2).
    14. Calogero Guccio & Domenico Lisi & Marco Martorana & Anna Mignosa, 2017. "On the role of cultural participation in tourism destination performance: an assessment using robust conditional efficiency approach," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 41(2), pages 129-154, May.
    15. Masayuki Morikawa, 2022. "Work‐from‐home productivity during the COVID‐19 pandemic: Evidence from Japan," Economic Inquiry, Western Economic Association International, vol. 60(2), pages 508-527, April.
    16. Cordero, José Manuel & Pedraja-Chaparro, Francisco & Pisaflores, Elsa C. & Polo, Cristina, 2016. "Efficiency assessment of Portuguese municipalities using a conditional nonparametric approach," MPRA Paper 70674, University Library of Munich, Germany.
    17. López-Herrera, Carmen & Cordero, José M. & Pedraja-Chaparro, Francisco & Polo, Cristina, 2023. "Fiscal rules and their influence on public sector efficiency," MPRA Paper 119018, University Library of Munich, Germany.
    18. De Witte, Kristof & Geys, Benny, 2013. "Citizen coproduction and efficient public good provision: Theory and evidence from local public libraries," European Journal of Operational Research, Elsevier, vol. 224(3), pages 592-602.
    19. Attar, M. Aykut & Tekin-Koru, Ayça, 2022. "Latent social distancing: Identification, causes and consequences," Economic Systems, Elsevier, vol. 46(1).
    20. Belmonte-Martin, Irene & Ortiz, Lidia & Polo, Cristina, 2021. "Local tax management in Spain: A study of the conditional efficiency of provincial tax agencies," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

    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:eee:ecanpo:v:79:y:2023:i:c:p:376-394. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/economic-analysis-and-policy .

    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.