IDEAS home Printed from https://ideas.repec.org/a/wly/hlthec/v31y2022i8p1590-1617.html
   My bibliography  Save this article

Are firms with ‘deep pockets’ more responsive to tort liability? Evidence from nursing homes

Author

Listed:
  • James A. Brickley
  • Susan F. Lu
  • Gerard J. Wedig

Abstract

We provide time series evidence of tort reform's impact on inputs and quality in the nursing home industry. Between 2000 and 2010, 11 state reforms capped noneconomic damages for health care services. Small chain and unaffiliated nursing homes enjoyed “judgment proof standing” and were less apt to be sued, prior to reform. We find that the managers of such homes were relatively unresponsive to the implementation of state caps on noneconomic damages. Large “deep‐pocketed” chain‐affiliated homes lacked judgment proof standing and implemented greater reductions in their nursing inputs in the aftermath of tort relief. However, we find little evidence of service quality erosion across four measured dimensions of care outcomes. Our findings are consistent with a “defensive care” model in which large chain homes employ unproductive inputs in an effort to meet a negligence standard of care.

Suggested Citation

  • James A. Brickley & Susan F. Lu & Gerard J. Wedig, 2022. "Are firms with ‘deep pockets’ more responsive to tort liability? Evidence from nursing homes," Health Economics, John Wiley & Sons, Ltd., vol. 31(8), pages 1590-1617, August.
    • Handle: RePEc:wly:hlthec:v:31:y:2022:i:8:p:1590-1617
    DOI: 10.1002/hec.4528
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/hec.4528
    Download Restriction: no
    File URL: https://libkey.io/10.1002/hec.4528?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. Ronen Avraham, 2007. "An Empirical Study of the Impact of Tort Reforms on Medical Malpractice Settlement Payments," The Journal of Legal Studies, University of Chicago Press, vol. 36(S2), pages 183-229, June.
    2. Wooldridge, Jeffrey M., 1995. "Selection corrections for panel data models under conditional mean independence assumptions," Journal of Econometrics, Elsevier, vol. 68(1), pages 115-132, July.
    3. 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.
    4. Semykina, Anastasia & Wooldridge, Jeffrey M., 2010. "Estimating panel data models in the presence of endogeneity and selection," Journal of Econometrics, Elsevier, vol. 157(2), pages 375-380, August.
    5. A. Colin Cameron & Douglas L. Miller, 2015. "A Practitioner’s Guide to Cluster-Robust Inference," Journal of Human Resources, University of Wisconsin Press, vol. 50(2), pages 317-372.
    6. Jonathan Klick & Thomas Stratmann, 2007. "Medical Malpractice Reform and Physicians in High-Risk Specialties," The Journal of Legal Studies, University of Chicago Press, vol. 36(S2), pages 121-142, June.
    7. David H. Autor, 2003. "Outsourcing at Will: The Contribution of Unjust Dismissal Doctrine to the Growth of Employment Outsourcing," Journal of Labor Economics, University of Chicago Press, vol. 21(1), pages 1-42, January.
    8. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    9. Steven Shavell, 2004. "Minimum Asset Requirements and Compulsory Liability Insurance As Solutions to the Judgment-Proof Problem," NBER Working Papers 10341, National Bureau of Economic Research, Inc.
    10. Daniel P. Kessler, 2011. "Evaluating the Medical Malpractice System and Options for Reform," Journal of Economic Perspectives, American Economic Association, vol. 25(2), pages 93-110, Spring.
    11. Atanasov, Vladimir & Black, Bernard, 2016. "Shock-Based Causal Inference in Corporate Finance and Accounting Research," Critical Finance Review, now publishers, vol. 5(2), pages 207-304, December.
    12. Marianne Bertrand & Esther Duflo & Sendhil Mullainathan, 2004. "How Much Should We Trust Differences-In-Differences Estimates?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 119(1), pages 249-275.
    13. Susan F. Lu & Gerard J. Wedig, 2013. "Clustering, Agency Costs and Operating Efficiency: Evidence from Nursing Home Chains," Management Science, INFORMS, vol. 59(3), pages 677-694, May.
    14. Harrington, C. & Woolhandler, S. & Mullan, J. & Carrillo, H. & Himmelstein, D.U., 2001. "Does investor ownership of nursing homes compromise the quality of care?," American Journal of Public Health, American Public Health Association, vol. 91(9), pages 1452-1455.
    15. Amy Finkelstein, 2007. "The Aggregate Effects of Health Insurance: Evidence from the Introduction of Medicare," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(1), pages 1-37.
    16. Thomas N. Hubbard, 2004. "Affiliation, integration, and information: ownership incentives and industry structure," Journal of Industrial Economics, Wiley Blackwell, vol. 52(2), pages 201-227, June.
    17. Shavell, S., 1986. "The judgment proof problem," International Review of Law and Economics, Elsevier, vol. 6(1), pages 45-58, June.
    18. Avi Dor & Sarah Duffy & Herbert Wong, 1997. "Expense Preference Behavior and Contract‐Management: Evidence from U.S. Hospitals," Southern Economic Journal, John Wiley & Sons, vol. 64(2), pages 542-554, October.
    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. Hansen, Bruce E. & Lee, Seojeong, 2019. "Asymptotic theory for clustered samples," Journal of Econometrics, Elsevier, vol. 210(2), pages 268-290.
    2. Bruno Ferman & Cristine Pinto, 2019. "Inference in Differences-in-Differences with Few Treated Groups and Heteroskedasticity," The Review of Economics and Statistics, MIT Press, vol. 101(3), pages 452-467, July.
    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. 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.
    5. Slawa Rokicki & Jessica Cohen & Gunther Fink & Joshua Salomon & Mary Beth Landrum, 2018. "Inference with difference-in-differences with a small number of groups: a review, simulation study and empirical application using SHARE data," CHaRMS Working Papers 18-01, Centre for HeAlth Research at the Management School (CHaRMS).
    6. Diane Coffey & Michael Geruso & Dean Spears, 2018. "Sanitation, Disease Externalities and Anaemia: Evidence From Nepal," Economic Journal, Royal Economic Society, vol. 128(611), pages 1395-1432, June.
    7. Johanna Catherine Maclean & Brendan Saloner, 2019. "The Effect of Public Insurance Expansions on Substance Use Disorder Treatment: Evidence from the Affordable Care Act," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 38(2), pages 366-393, March.
    8. Aleksey Oshchepkov & Anna Shirokanova, 2020. "Multilevel Modeling For Economists: Why, When And How," HSE Working papers WP BRP 233/EC/2020, National Research University Higher School of Economics.
    9. Effrosyni Adamopoulou & Ezgi Kaya, 2020. "Not just a work permit: EU citizenship and the consumption behaviour of documented and undocumented immigrants," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 53(4), pages 1552-1598, November.
    10. 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.
    11. James G. MacKinnon & Matthew D. Webb, 2020. "When and How to Deal with Clustered Errors in Regression Models," Working Paper 1421, Economics Department, Queen's University.
    12. Burbano, Vanessa C. & Ostler, James, 2021. "Differences in consumer-benefiting misconduct by nonprofit, for-profit, and public organizations," Organizational Behavior and Human Decision Processes, Elsevier, vol. 166(C), pages 117-136.
    13. Li, Haoran & Wan, Xibo & Zhang, Wendong, 2020. "How do Firms Respond to Political Tensions? Evidence from Chinese Food Importers," ISU General Staff Papers 202011250800001118, Iowa State University, Department of Economics.
    14. Massimo Bordignon & Silvia Coretti & Massimiliano Piacenza & Gilberto Turati, 2020. "Hardening subnational budget constraints via administrative subordination: The Italian experience of recovery plans in regional health services," Health Economics, John Wiley & Sons, Ltd., vol. 29(11), pages 1378-1399, November.
    15. Hagemann, Andreas, 2019. "Placebo inference on treatment effects when the number of clusters is small," Journal of Econometrics, Elsevier, vol. 213(1), pages 190-209.
    16. 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.
    17. Isabella Giorgetti & Matteo Picchio, 2021. "One billion euro programme for early childcare services in Italy," Metroeconomica, Wiley Blackwell, vol. 72(3), pages 460-492, July.
    18. Carpenter, Christopher S. & Churchill, Brandyn F. & Marcus, Michelle, 2023. "Bad lighting: Effects of youth indoor tanning prohibitions," Journal of Health Economics, Elsevier, vol. 88(C).
    19. Dana C. Andersen, 2016. "Credit Constraints, Technology Upgrading, and the Environment," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 3(2), pages 283-319.
    20. Meinhofer, Angélica & Witman, Allison E. & Hinde, Jesse M. & Simon, Kosali, 2021. "Marijuana liberalization policies and perinatal health," Journal of Health Economics, Elsevier, vol. 80(C).

    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:hlthec:v:31:y:2022:i:8:p:1590-1617. 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://www3.interscience.wiley.com/cgi-bin/jhome/5749 .

    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.