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State and self investments in health

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  • Fichera1, E
  • Sutton, M

Abstract

We consider how individuals' decisions on their health behaviours depend on the level of investment in their health provided by the State. We develop the model provided by Ehrlich and Becker (1972) and Peltzman (1975) and we show that higher levels of protection provided by the State (either through the increased availability or effectiveness of medical care) can crowd out or reinforce self-insurance. We apply this model to the smoking cessation decision made by individuals diagnosed with a cardiovascular disease in waves of the Health Survey of England between 1993 and 2006. There has been a considerable increase in the proportion of these individuals who receive prescriptions of statins from the State, a highly effective drug that reduces the probability of further heart attacks and premature death. We nd that the probability of quitting smoking is increased by four percentage points amongst those individuals prescribed statins. This result is robust to allowing for the direct effects of smoking advice. When the potential endogeneity of doctors' decision to prescribe statins is dealt with using variables in national guidelines, we find that unobservable characteristics which make people more prone to stop smoking reduce the probability of receiving statins and the evidence of the complementarity between quitting smoking and prescription of statins is confirmed.

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  • Fichera1, E & Sutton, M, 2010. "State and self investments in health," Health, Econometrics and Data Group (HEDG) Working Papers 10/23, HEDG, c/o Department of Economics, University of York.
    • Handle: RePEc:yor:hectdg:10/23
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    Cited by:

    1. Fichera, Eleonora & Emsley, Richard & Sutton, Matt, 2016. "Is treatment “intensity” associated with healthier lifestyle choices? An application of the dose response function," Economics & Human Biology, Elsevier, vol. 23(C), pages 149-163.
    2. John Mullahy, 2011. "Marginal Effects in Multivariate Probit and Kindred Discrete and Count Outcome Models, with Applications in Health Economics," NBER Working Papers 17588, National Bureau of Economic Research, Inc.
    3. Paul Andres Rodriguez-Lesmes, 2017. "Early diagnosis of chronic conditions and lifestyle modification," Documentos de Trabajo 15639, Universidad del Rosario.
    4. Fichera, Eleonora & Banks, James & Siciliani, Luigi & Sutton, Matt, 2018. "Does patient health behaviour respond to doctor effort?," Journal of Economic Behavior & Organization, Elsevier, vol. 156(C), pages 225-251.
    5. Mullahy, John, 2011. "Marginal Effects in Multivariate Probit and Kindred Discrete and Count Outcome Models," Working Papers 201135, Geary Institute, University College Dublin.
    6. Michael Kuhn & Alexia Prskawetz & Uwe Sunde, 2014. "Health, education, and retirement over the prolonged life cycle: a selective survey of recent research," Vienna Yearbook of Population Research, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna, vol. 12(1), pages 1-22.
    7. Abraham Abebe Asfaw, 2019. "The effect of prescription drug insurance on health behavior: Evidence from Medicare Part D," Health Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 403-418, March.
    8. Eleonora Fichera & James Banks & Matt Sutton, 2014. "Health behaviours and the patient-doctor interaction: The double moral hazard problem," Economics Discussion Paper Series 1415, Economics, The University of Manchester.
    9. Eleonora Fichera & James Banks & Luigi Siciliani & Matt Sutton, 2017. "Does Patient Health Behaviour respond to Doctor’s Effort?," Department of Economics Working Papers 62/17, University of Bath, Department of Economics.
    10. Fichera, Eleonora & Gray, Ewan & Sutton, Matt, 2016. "How do individuals’ health behaviours respond to an increase in the supply of health care? Evidence from a natural experiment," Social Science & Medicine, Elsevier, vol. 159(C), pages 170-179.
    11. Giovanni Bruno & Orietta Dessy, 2014. "Average partial effects in multivariate probit models with latent heterogeneity: Monte Carlo experiments and an application to immigrants' ethnic identity and economic performance," Italian Stata Users' Group Meetings 2014 10, Stata Users Group.

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    More about this item

    Keywords

    Crowding-out; moral hazard; preventative behaviour; drugs;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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