IDEAS home Printed from https://ideas.repec.org/a/eee/socmed/v349y2024ics0277953624003228.html
   My bibliography  Save this article

Clear as a bell? Policy stringency and elderly health during Covid-19

Author

Listed:
  • Dupuy, Jules
  • Barnay, Thomas
  • Defebvre, Eric

Abstract

This paper investigates how restriction policies have impacted elderly self-assessed health (SAH) in Europe during the pandemic, and how the Covid-19 infection interacts with policy stringency to modulate the SAH deterioration. Using the Survey of Health, Aging and Retirement in Europe (SHARE) between October 2019 and August 2021, including 9,034 adults aged 50 years and above, alongside with a stringency index from the Oxford's Coronavirus Government Response Tracker (OxCGRT), we design both an adjusted probit model and a recursive bivariate probit model to test for endogeneity of Covid-19 infection. Estimations results show a bell curve between stringency and SAH degradation: a deleterious effect of restrictions at low levels of stringency up to a tipping point after which more stringent policies become protective. Covid-19 infection moderates this association. Depending on individuals' initial health, the effect of restrictions is uneven: highly stringent policies become damaging for individuals most likely to enter a vulnerabilization path, for whom the bell curve is thus inverted. Overall, this study shows clear patterns of association between policy stringency and perceived health among older Europeans, and highlights the potential trade-off between targeting as many people as possible, those in poor health or those on the edge of vulnerability.

Suggested Citation

  • Dupuy, Jules & Barnay, Thomas & Defebvre, Eric, 2024. "Clear as a bell? Policy stringency and elderly health during Covid-19," Social Science & Medicine, Elsevier, vol. 349(C).
  • Handle: RePEc:eee:socmed:v:349:y:2024:i:c:s0277953624003228
    DOI: 10.1016/j.socscimed.2024.116878
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0277953624003228
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.socscimed.2024.116878?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 look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Andrew E. Clark & Anthony Lepinteur, 2022. "Pandemic Policy and Life Satisfaction in Europe," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 68(2), pages 393-408, June.
    2. Kline Patrick & Santos Andres, 2012. "A Score Based Approach to Wild Bootstrap Inference," Journal of Econometric Methods, De Gruyter, vol. 1(1), pages 23-41, August.
    3. MacKinnon, James G. & Nielsen, Morten Ørregaard & Webb, Matthew D., 2023. "Cluster-robust inference: A guide to empirical practice," Journal of Econometrics, Elsevier, vol. 232(2), pages 272-299.
    4. Chiburis, Richard C. & Das, Jishnu & Lokshin, Michael, 2012. "A practical comparison of the bivariate probit and linear IV estimators," Economics Letters, Elsevier, vol. 117(3), pages 762-766.
    5. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2008. "Bootstrap-Based Improvements for Inference with Clustered Errors," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 414-427, August.
    6. David Roodman & James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2019. "Fast and wild: Bootstrap inference in Stata using boottest," Stata Journal, StataCorp LP, vol. 19(1), pages 4-60, March.
    7. Au, Nicole & Johnston, David W., 2014. "Self-assessed health: What does it mean and what does it hide?," Social Science & Medicine, Elsevier, vol. 121(C), pages 21-28.
    8. 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.
    9. Ai, Chunrong & Norton, Edward C., 2003. "Interaction terms in logit and probit models," Economics Letters, Elsevier, vol. 80(1), pages 123-129, July.
    10. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, April.
    11. Ahn, SangNam & Kim, Seonghoon & Koh, Kanghyock, 2020. "Changes in Healthcare Utilization, Spending, and Perceived Health during COVID–19: A Longitudinal Study from Singapore," IZA Discussion Papers 13715, Institute of Labor Economics (IZA).
    12. Theologos Dergiades & Costas Milas & Elias Mossialos & Theodore Panagiotidis, 2022. "Effectiveness of government policies in response to the first COVID-19 outbreak," PLOS Global Public Health, Public Library of Science, vol. 2(4), pages 1-19, April.
    13. Joshua D. Angrist, 1991. "Instrumental Variables Estimation of Average Treatment Effects in Econometrics and Epidemiology," NBER Technical Working Papers 0115, National Bureau of Economic Research, Inc.
    14. Grimalda, Gianluca & Buchan, Nancy R. & Ozturk, Orgul G. & Pinate, Adriana C. & Urso, Giulia & Brewer, Marilynn B., 2021. "Exposure to COVID-19 is associated with increased altruism, particularly at the local level," Open Access Publications from Kiel Institute for the World Economy 248645, Kiel Institute for the World Economy (IfW Kiel).
    Full references (including those not matched with items on IDEAS)

    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. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2023. "Fast and reliable jackknife and bootstrap methods for cluster‐robust inference," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(5), pages 671-694, August.
    2. Costa-Font, Joan & Jiménez-Martín, Sergi & Vilaplana-Prieto, Cristina, 2022. "Do Public Caregiving Subsidies and Supports affect the Provision of Care and Transfers?," Journal of Health Economics, Elsevier, vol. 84(C).
    3. Wenjie Wang & Yichong Zhang, 2021. "Wild Bootstrap for Instrumental Variables Regressions with Weak and Few Clusters," Papers 2108.13707, arXiv.org, revised Jan 2024.
    4. James G. MacKinnon, 2019. "How cluster‐robust inference is changing applied econometrics," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 52(3), pages 851-881, August.
    5. Arrieta Vidal, Johar & Florián Hoyle, David & López Vargas, Kristian & Morales Vásquez, Valeria, 2022. "Policies for transactional de-dollarization: A laboratory study," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 31-54.
    6. Arjan Trinks & Erik Hille, 2023. "Carbon costs and industrial firm performance: Evidence from international microdata," CPB Discussion Paper 445, CPB Netherlands Bureau for Economic Policy Analysis.
    7. MacKinnon, James G. & Nielsen, Morten Ørregaard & Webb, Matthew D., 2023. "Testing for the appropriate level of clustering in linear regression models," Journal of Econometrics, Elsevier, vol. 235(2), pages 2027-2056.
    8. Doko Tchatoka, Firmin & Wang, Wenjie, 2021. "Size-corrected Bootstrap Test after Pretesting for Exogeneity with Heteroskedastic or Clustered Data," MPRA Paper 110899, University Library of Munich, Germany.
    9. Wang, Wenjie & Zhang, Yichong, 2024. "Wild bootstrap inference for instrumental variables regressions with weak and few clusters," Journal of Econometrics, Elsevier, vol. 241(1).
    10. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2023. "Leverage, influence, and the jackknife in clustered regression models: Reliable inference using summclust," Stata Journal, StataCorp LP, vol. 23(4), pages 942-982, December.
    11. Goussé, Marion & Leturcq, Marion, 2022. "More or less unmarried. The impact of legal settings of cohabitation on labour market outcomes," European Economic Review, Elsevier, vol. 149(C).
    12. James G. MacKinnon & Morten {O}rregaard Nielsen & Matthew D. Webb, 2024. "Cluster-robust jackknife and bootstrap inference for binary response models," Papers 2406.00650, arXiv.org.
    13. Òscar Jordà & Alan M. Taylor, 2024. "Local Projections," NBER Working Papers 32822, National Bureau of Economic Research, Inc.
    14. Gerard, Andrew & Lopez, Maria Claudia & Mason, Nicole M. & Bizoza, Alfred R., 2022. "Do government zoning policies improve buyer-farmer relationships? Evidence from Rwanda’s coffee sector," Food Policy, Elsevier, vol. 107(C).
    15. Delesalle, Esther, 2021. "The effect of the Universal Primary Education program on consumption and on the employment sector: Evidence from Tanzania," World Development, Elsevier, vol. 142(C).
    16. Havlik, Annika, 2020. "Political budget cycles in European public procurement," ZEW Discussion Papers 20-069, ZEW - Leibniz Centre for European Economic Research.
    17. Fabienne Helfer & Volker Grossmann & Aderonke Osikominu, 2023. "How does immigration affect housing costs in Switzerland?," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 159(1), pages 1-31, December.
    18. Jeffrey D. Michler & Anna Josephson, 2022. "Recent developments in inference: practicalities for applied economics," Chapters, in: A Modern Guide to Food Economics, chapter 11, pages 235-268, Edward Elgar Publishing.
    19. Steinberg, Philip J. & Urbig, Diemo & Procher, Vivien D. & Volkmann, Christine, 2021. "Knowledge transfer and home-market innovativeness: A comparison of emerging and advanced economy multinationals," Journal of International Management, Elsevier, vol. 27(4).
    20. Kamila Cygan-Rehm, 2022. "Lifetime Consequences of Lost Instructional Time in the Classroom: Evidence from Shortened School Years," CESifo Working Paper Series 9892, CESifo.

    More about this item

    Keywords

    Policy stringency; Self-assessed health; Covid-19 infection; European elderly; Interaction effects;
    All these keywords.

    JEL classification:

    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • H12 - Public Economics - - Structure and Scope of Government - - - Crisis Management
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

    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:socmed:v:349:y:2024:i:c:s0277953624003228. 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.elsevier.com/wps/find/journaldescription.cws_home/315/description#description .

    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.