IDEAS home Printed from https://ideas.repec.org/p/yor/hectdg/11-32.html
   My bibliography  Save this paper

Measuring the effects of removing subsidies for private insurance on public expenditure for health care

Author

Listed:
  • Chai Cheng, T.

Abstract

This paper investigates the effects of removing subsidies for private health insurance on public sector expenditure for hospital care. An econometric framework using simultaneous equation models is developed to analyse the interrelated decisions on the intensity and type of health care use and insurance. The results indicate that while privately insured individuals are more likely to seek hospital care as a private patient, they do not differ in their intensity of hospital care use compared with those without private insurance. The simulation results suggest that eliminating subsides could potentially yield substantial public sector savings.

Suggested Citation

  • Chai Cheng, T., 2011. "Measuring the effects of removing subsidies for private insurance on public expenditure for health care," Health, Econometrics and Data Group (HEDG) Working Papers 11/32, HEDG, c/o Department of Economics, University of York.
  • Handle: RePEc:yor:hectdg:11/32
    as

    Download full text from publisher

    File URL: https://www.york.ac.uk/media/economics/documents/herc/wp/11_32.pdf
    File Function: Main text
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Keane, Michael P., 2010. "Structural vs. atheoretic approaches to econometrics," Journal of Econometrics, Elsevier, vol. 156(1), pages 3-20, May.
    2. Fabbri, Daniele & Monfardini, Chiara, 2009. "Rationing the public provision of healthcare in the presence of private supplements: Evidence from the Italian NHS," Journal of Health Economics, Elsevier, vol. 28(2), pages 290-304, March.
    3. López Nicolás, Ángel & Vera-Hernández, Marcos, 2008. "Are tax subsidies for private medical insurance self-financing? Evidence from a microsimulation model," Journal of Health Economics, Elsevier, vol. 27(5), pages 1285-1298, September.
    4. Chai Cheng, T & Vahid, F, 2010. "Demand for hospital care and private health insurance in a mixed publicprivate system: empirical evidence using a simultaneous equation modeling approach," Health, Econometrics and Data Group (HEDG) Working Papers 10/25, HEDG, c/o Department of Economics, University of York.
    5. Murat K. Munkin & Pravin K. Trivedi, 1999. "Simulated maximum likelihood estimation of multivariate mixed-Poisson regression models, with application," Econometrics Journal, Royal Economic Society, vol. 2(1), pages 29-48.
    6. Savage, Elizabeth & Wright, Donald J., 2003. "Moral hazard and adverse selection in Australian private hospitals: 1989-1990," Journal of Health Economics, Elsevier, vol. 22(3), pages 331-359, May.
    7. Andreas Million & Regina T. Riphahn & Achim Wambach, 2003. "Incentive effects in the demand for health care: a bivariate panel count data estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 387-405.
    8. H.E. Frech Iii & Sandra Hopkins & Garry Macdonald, 2003. "The Australian Private Health Insurance Boom: Was It Subsidies Or Liberalised Regulation?," Economic Papers, The Economic Society of Australia, vol. 22(1), pages 58-64, March.
    9. Marquis, M. Susan & Long, Stephen H., 1995. "Worker demand for health insurance in the non-group market," Journal of Health Economics, Elsevier, vol. 14(1), pages 47-63, May.
    10. Terza, Joseph V., 1998. "Estimating count data models with endogenous switching: Sample selection and endogenous treatment effects," Journal of Econometrics, Elsevier, vol. 84(1), pages 129-154, May.
    11. Deb, Partha & Trivedi, Pravin K., 2002. "The structure of demand for health care: latent class versus two-part models," Journal of Health Economics, Elsevier, vol. 21(4), pages 601-625, July.
    12. Atella, Vincenzo & Deb, Partha, 2008. "Are primary care physicians, public and private sector specialists substitutes or complements? Evidence from a simultaneous equations model for count data," Journal of Health Economics, Elsevier, vol. 27(3), pages 770-785, May.
    13. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    14. Cameron, A. Colin & Trivedi, Pravin K., 1991. "The role of income and health risk in the choice of health insurance : Evidence from Australia," Journal of Public Economics, Elsevier, vol. 45(1), pages 1-28, June.
    15. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    16. Bhat, Chandra R., 2001. "Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 677-693, August.
    17. van Ophem, Hans, 2000. "Modeling Selectivity in Count-Data Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(4), pages 503-511, October.
    18. Mark Stabile, 2001. "Private insurance subsidies and public health care markets: evidence from Canada," Canadian Journal of Economics, Canadian Economics Association, vol. 34(4), pages 921-942, November.
    19. Propper, Carol, 2000. "The demand for private health care in the UK," Journal of Health Economics, Elsevier, vol. 19(6), pages 855-876, November.
    20. Gowrisankaran, Gautam & Town, Robert J., 1999. "Estimating the quality of care in hospitals using instrumental variables," Journal of Health Economics, Elsevier, vol. 18(6), pages 747-767, December.
    21. A. C. Cameron & P. K. Trivedi & Frank Milne & J. Piggott, 1988. "A Microeconometric Model of the Demand for Health Care and Health Insurance in Australia," Review of Economic Studies, Oxford University Press, vol. 55(1), pages 85-106.
    22. Marquis, M. Susan & Louis, Thomas A., 2002. "On using sample selection methods in estimating the price elasticity of firms' demand for insurance," Journal of Health Economics, Elsevier, vol. 21(1), pages 137-145, January.
    23. Jörgen Hellström, 2006. "A bivariate count data model for household tourism demand," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(2), pages 213-226.
    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. Damien S. Eldridge & Ilke Onur & Malathi Velamuri, 2017. "The impact of private hospital insurance on the utilization of hospital care in Australia," Applied Economics, Taylor & Francis Journals, vol. 49(1), pages 78-95, January.
    2. Cheng, Terence Chai, 2014. "Measuring the effects of reducing subsidies for private insurance on public expenditure for health care," Journal of Health Economics, Elsevier, vol. 33(C), pages 159-179.
    3. Terence C. Cheng & Joan Costa-Font & Nattavudh Powdthavee, 2018. "Do You Have to Win It to Fix It? A Longitudinal Study of Lottery Winners and Their Health-Care Demand," American Journal of Health Economics, MIT Press, vol. 4(1), pages 26-50, Winter.
    4. Terence C. Cheng & Alfons Palangkaraya & Jongsay Yong, 2014. "Hospital utilization in mixed public--private system: evidence from Australian hospital data," Applied Economics, Taylor & Francis Journals, vol. 46(8), pages 859-870, March.
    5. Nathan Kettlewell, 2016. "Policy Choice and Product Bundling in a Complicated Health Insurance Market: Do People get it Right?," Discussion Papers 2016-16, School of Economics, The University of New South Wales.

    More about this item

    Keywords

    Demand for Hospital Care; Private Insurance; Bivariate count data models; Simultaneous equation models; Policy simulation;

    JEL classification:

    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • H42 - Public Economics - - Publicly Provided Goods - - - Publicly Provided Private Goods
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:yor:hectdg:11/32. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Jane Rawlings). General contact details of provider: http://edirc.repec.org/data/deyoruk.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.