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Rationing the Public Provision of Health Care in the Presence of Private Supplements: Evidence from the Italian NHS

Author

Listed:
  • Daniele Fabbri
  • Chiara Monfardini

Abstract

In this paper we assess the relative effectiveness of user charges and administrative waiting times as a tool for rationing public healthcare in Italy. We measure demand elasticities by estimating a simultaneous equation model of GP primary care visits, public specialist consultations and private specialist consultations, as if they were part of an incomplete system of demand. We find that own price elasticity of the demand for public specialist consultation is about -0.3, while administrative waiting time plays a less important role. No substitution exists between the demand for public and private specialists, so that user charges act as a net deterrent for over-consumption. The public provision of healthcare does not induce the wealthy to opt out. Moreover our evidence suggests that user charges and waiting lists do not serve redistributive purposes.

Suggested Citation

  • Daniele Fabbri & Chiara Monfardini, 2006. "Rationing the Public Provision of Health Care in the Presence of Private Supplements: Evidence from the Italian NHS," Health, Econometrics and Data Group (HEDG) Working Papers 06/14, HEDG, c/o Department of Economics, University of York.
  • Handle: RePEc:yor:hectdg:06/14
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    2. Luigi Siciliani & Tor Iversen, 2012. "Waiting Times and Waiting Lists," Chapters, in: Andrew M. Jones (ed.), The Elgar Companion to Health Economics, Second Edition, chapter 24, Edward Elgar Publishing.
    3. 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.
    4. Michela Ponzo & Vincenzo Scoppa, 2016. "Cost-Sharing and Use of Health Services in Italy: Evidence from a Fuzzy Regression Discontinuity Design," CSEF Working Papers 440, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    5. Sharma, Anurag & Siciliani, Luigi & Harris, Anthony, 2013. "Waiting times and socioeconomic status: Does sample selection matter?," Economic Modelling, Elsevier, vol. 33(C), pages 659-667.
    6. Christine A. Yee & Kyle Barr & Taeko Minegishi & Austin Frakt & Steven D. Pizer, 2022. "Provider supply and access to primary care," Health Economics, John Wiley & Sons, Ltd., vol. 31(7), pages 1296-1316, July.
    7. Daniele Fabbri & Chiara Monfardini, 2016. "Opt Out or Top Up? Voluntary Health Care Insurance and the Public vs. Private Substitution," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(1), pages 75-93, February.
    8. 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.
    9. Elsa Marques & Sian Noble & Ashley W. Blom & William Hollingworth, 2014. "Disclosing Total Waiting Times For Joint Replacement: Evidence From The English Nhs Using Linked Hes Data," Health Economics, John Wiley & Sons, Ltd., vol. 23(7), pages 806-820, July.
    10. Haizhen Mou, 2012. "The political economy of public health expenditure and wait times in a public‐private mixed health care system," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 45(4), pages 1640-1666, November.
    11. Geraci Andrea & Fabbri Daniele & Monfardini Chiara, 2018. "Testing Exogeneity of Multinomial Regressors in Count Data Models: Does Two-stage Residual Inclusion Work?," Journal of Econometric Methods, De Gruyter, vol. 7(1), pages 1-19, January.
    12. Del Vecchio, Mario & Fenech, Lorenzo & Prenestini, Anna, 2015. "Private health care expenditure and quality in Beveridge systems: Cross-regional differences in the Italian NHS," Health Policy, Elsevier, vol. 119(3), pages 356-366.
    13. 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.
    14. 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, University of Chicago Press, vol. 4(1), pages 26-50, Winter.
    15. Davide Pianori & Elisa Maietti & Jacopo Lenzi & Mattia Quargnolo & Stefano Guicciardi & Kadjo Yves Cedric Adja & Maria Pia Fantini & Federico Toth, 2020. "Sociodemographic and health service organizational factors associated with the choice of the private versus public sector for specialty visits: Evidence from a national survey in Italy," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-12, May.
    16. Andrea Riganti & Luigi Siciliani & Carlo V. Fiorio, 2017. "The effect of waiting times on demand and supply for elective surgery: Evidence from Italy," Health Economics, John Wiley & Sons, Ltd., vol. 26(S2), pages 92-105, September.
    17. Silvia Balia & Rinaldo Brau, 2014. "A Country For Old Men? Long‐Term Home Care Utilization In Europe," Health Economics, John Wiley & Sons, Ltd., vol. 23(10), pages 1185-1212, October.
    18. Cici McNamara & Natalia Serna, 2022. "The impact of a national formulary expansion on diabetics," Health Economics, John Wiley & Sons, Ltd., vol. 31(11), pages 2311-2332, November.

    More about this item

    Keywords

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    JEL classification:

    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets

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