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Modelling the Dynamics of a Public Health Care System: Evidence from Time-Series Data

Author

Listed:
  • Fabrizio Iacone

    (Department of Economics and Related Studies, University of York)

  • Steve Martin

    (Department of Economics and Related Studies, University of York)

  • Luigi Siciliani

    (Centre for Health Economics, University of York)

  • Peter C Smith

    (Centre for Health Economics, University of York)

Abstract

The English National Health Service was established in 1948, and has therefore yielded some long time series data on health system performance. Waiting times for inpatient care have been a persistent cause of policy concern since the creation of the NHS. This paper develops a theoretical model of the dynamic interaction between key indicators of health system performance. It then investigates empirically the relationship between hospital activity, waiting times and population characteristics using aggregate time-series data for the NHS over the period 1952-2005. Structural Vector Auto-Regression suggests that in the long run: a) higher activity is associated with lower waiting times (elasticity = -0.9%); b) a higher proportion of old population is associated with higher waiting times (elasticity = 1.6%). In the short run, higher lagged waiting time leads to higher activity (elasticity = 0.2%). We also find that shocks in waiting times are countered by higher activity, so the effect is only temporary, while shocks in activity have a permanent effect. We conclude that policies to reduce waiting times should focus on initiatives that increase hospital activity.

Suggested Citation

  • Fabrizio Iacone & Steve Martin & Luigi Siciliani & Peter C Smith, 2007. "Modelling the Dynamics of a Public Health Care System: Evidence from Time-Series Data," Working Papers 029cherp, Centre for Health Economics, University of York.
  • Handle: RePEc:chy:respap:29cherp
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    Cited by:

    1. Reibling, Nadine, 2013. "The international performance of healthcare systems in population health: Capabilities of pooled cross-sectional time series methods," Health Policy, Elsevier, vol. 112(1), pages 122-132.

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    More about this item

    Keywords

    Waiting times; Dynamics; Vector Auto-Regression.;
    All these keywords.

    JEL classification:

    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • H42 - Public Economics - - Publicly Provided Goods - - - Publicly Provided Private Goods
    • H52 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Education

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