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Panel data methods and applications to health economics

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  • Andrew M. Jones

Abstract

Much of the empirical analysis done by health economists seeks to estimate the impact of specific health policies and the greatest challenge for successful applied work is to find appropriate sources of variation to identify the treatment effects of interest. Estimation can be prone to selection bias, when the assignment to treatments is associated with the potential outcomes of the treatment. Overcoming this bias requires variation in the assignment of treatments that is independent of the outcomes. One source of independent variation comes from randomised controlled experiments. But, in practice, most economic studies have to draw on non-experimental data. Many studies seek to use variation across time and events that takes the form of a quasi-experimental design, or “natural experiment”, that mimics the features of a genuine experiment. This chapter reviews the data and methods that are used in applied health economics with a particular emphasis on the use of panel data. The focus is on nonlinear models and methods that can accommodate unobserved heterogeneity. These include conditional estimators, maximum simulated likelihood, Bayesian MCMC, finite mixtures and copulas.

Suggested Citation

  • Andrew M. Jones, 2007. "Panel data methods and applications to health economics," Health, Econometrics and Data Group (HEDG) Working Papers 07/18, HEDG, c/o Department of Economics, University of York.
  • Handle: RePEc:yor:hectdg:07/18
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    Cited by:

    1. Pierre Koning & Dinand Webbink & Nicholas Martin, 2015. "The effect of education on smoking behavior: new evidence from smoking durations of a sample of twins," Empirical Economics, Springer, vol. 48(4), pages 1479-1497, June.
    2. Péter Elek & Balázs Váradi & Márton Varga, 2015. "Effects of Geographical Accessibility on the Use of Outpatient Care Services: Quasi‐Experimental Evidence from Panel Count Data," Health Economics, John Wiley & Sons, Ltd., vol. 24(9), pages 1131-1146, September.
    3. Laudicella, Mauro & Cookson, Richard & Jones, Andrew M. & Rice, Nigel, 2009. "Health care deprivation profiles in the measurement of inequality and inequity: An application to GP fundholding in the English NHS," Journal of Health Economics, Elsevier, vol. 28(6), pages 1048-1061, December.
    4. Schneider Brit S. & Schneider Udo & Ulrich Volker, 2007. "Health and the Decision to Invest in Education," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 227(5-6), pages 725-746, October.
    5. Giorgio Vittadini & Paolo Berta & Gianmaria Martini & Giuditta Callea, 2012. "The effect of a law limiting upcoding on hospital admissions: evidence from Italy," Empirical Economics, Springer, vol. 42(2), pages 563-582, April.
    6. Terence C. Cheng & Pravin K. Trivedi, 2015. "Attrition Bias in Panel Data: A Sheep in Wolf's Clothing? A Case Study Based on the Mabel Survey," Health Economics, John Wiley & Sons, Ltd., vol. 24(9), pages 1101-1117, September.
    7. Manuel Gomes & Richard Grieve & Richard Nixon & Edmond S.‐W. Ng & James Carpenter & Simon G. Thompson, 2012. "Methods For Covariate Adjustment In Cost‐Effectiveness Analysis That Use Cluster Randomised Trials," Health Economics, John Wiley & Sons, Ltd., vol. 21(9), pages 1101-1118, September.
    8. Bhavani Shankar & Jose Brambila‐Macias & Bruce Traill & Mario Mazzocchi & Sara Capacci, 2013. "An Evaluation Of The Uk Food Standards Agency'S Salt Campaign," Health Economics, John Wiley & Sons, Ltd., vol. 22(2), pages 243-250, February.
    9. Cubi-Molla, P. & Jofre-Bonet, M. & Serra-Sastre, V., 2013. "Adaptation to Health States: A Micro-Econometric Approach," Working Papers 13/02, Department of Economics, City University London.
    10. Dimitrios Rovithis, 2013. "Do health economic evaluations using observational data provide reliable assessment of treatment effects?," Health Economics Review, Springer, vol. 3(1), pages 1-7, December.
    11. Moran, Valerie & Jacobs, Rowena, 2013. "An international comparison of efficiency of inpatient mental health care systems," Health Policy, Elsevier, vol. 112(1), pages 88-99.
    12. Song, Jia & Cheng, Terence C., 2020. "How do gender differences in family responsibilities affect doctors' labour supply? Evidence from Australian panel data," Social Science & Medicine, Elsevier, vol. 265(C).
    13. Jones, A.M, 2010. "Models For Health Care," Health, Econometrics and Data Group (HEDG) Working Papers 10/01, HEDG, c/o Department of Economics, University of York.
    14. 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.
    15. Miszczyńska Katarzyna M. & Miszczyński Piotr M., 2020. "Inpatient Costs in the Perspective of Polish Health Policy: Scenario Analysis," South East European Journal of Economics and Business, Sciendo, vol. 15(2), pages 43-56, December.
    16. Carro, Jesús M. & Traferri, Alejandra, 2009. "Correcting the bias in the estimation of a dynamic ordered probit with fixed effects of self-assessed health status," UC3M Working papers. Economics we094021, Universidad Carlos III de Madrid. Departamento de Economía.
    17. Udo Schneider & Jürgen Zerth, 2011. "Improving Prevention Compliance through Appropriate Incentives: Theoretical Modelling and Empirical Evidence," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 147(I), pages 71-106, March.
    18. Schneider, Udo & Zerth, Jürgen, 2008. "Improving prevention compliance through appropriate incentives," MPRA Paper 8280, University Library of Munich, Germany.
    19. Jones A.M & Rice N, 2009. "Econometric Evaluation of Health Policies," Health, Econometrics and Data Group (HEDG) Working Papers 09/09, HEDG, c/o Department of Economics, University of York.
    20. Gomes, M & Grieve, R, 2011. "Estimating the Effects of Friendship Networks on Health Behaviors of Adolescents," Health, Econometrics and Data Group (HEDG) Working Papers 11/14, HEDG, c/o Department of Economics, University of York.

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