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Using simulation-based inference with panel data in health economics

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Author Info
Paul Contoyannis (Centre for Health Economics and Policy Analysis, McMaster University, UK)
Andrew M. Jones (Department of Economics and Related Studies, University of York, UK)
Roberto Leon-Gonzalez (Centre for Health Economics & Department of Economics and Related Studies, University of York, UK)

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Abstract

Panel datasets provide a rich source of information for health economists, offering the scope to control for individual heterogeneity and to model the dynamics of individual behaviour. However the qualitative or categorical measures of outcome often used in health economics create special problems for estimating econometric models. Allowing a flexible specification of the autocorrelation induced by individual heterogeneity leads to models involving higher order integrals that cannot be handled by conventional numerical methods. The dramatic growth in computing power over recent years has been accompanied by the development of simulation-based estimators that solve this problem. This review uses binary choice models to show what can be done with conventional methods and how the range of models can be expanded by using simulation methods. Practical applications of the methods are illustrated using data on health from the British Household Panel Survey (BHPS). Copyright © 2003 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/hec.811
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Publisher Info
Article provided by John Wiley & Sons, Ltd. in its journal Health Economics.

Volume (Year): 13 (2004)
Issue (Month): 2 ()
Pages: 101-122
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:wly:hlthec:v:13:y:2004:i:2:p:101-122

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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/5749

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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Robinson, Peter M, 1982. "On the Asymptotic Properties of Estimators of Models Containing Limited Dependent Variables," Econometrica, Econometric Society, vol. 50(1), pages 27-41, January. [Downloadable!] (restricted)
  2. Partha Deb, 2001. "A discrete random effects probit model with application to the demand for preventive care," Health Economics, John Wiley & Sons, Ltd., vol. 10(5), pages 371-383. [Downloadable!]
  3. Chamberlain, Gary, 1984. "Panel data," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 22, pages 1247-1318 Elsevier. [Downloadable!] (restricted)
  4. Geweke, John, 1996. "Monte carlo simulation and numerical integration," Handbook of Computational Economics, in: H. M. Amman & D. A. Kendrick & J. Rust (ed.), Handbook of Computational Economics, edition 1, volume 1, chapter 15, pages 731-800 Elsevier. [Downloadable!] (restricted)
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  5. Arellano, Manuel & Honore, Bo, 2001. "Panel data models: some recent developments," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 53, pages 3229-3296 Elsevier. [Downloadable!] (restricted)
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  6. Paul Contoyannis & Andrew M. Jones & Nigel Rice, 2004. "Simulation-based inference in dynamic panel probit models: An application to health," Empirical Economics, Springer, vol. 29(1), pages 49-77, January. [Downloadable!] (restricted)
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  7. William Greene, 2001. "Fixed and Random Effects in Nonlinear Models," Working Papers 01-01, New York University, Leonard N. Stern School of Business, Department of Economics. [Downloadable!]
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  8. Chamberlain, Gary, 1980. "Analysis of Covariance with Qualitative Data," Review of Economic Studies, Blackwell Publishing, vol. 47(1), pages 225-38, January. [Downloadable!] (restricted)
  9. Chib S. & Jeliazkov I., 2001. "Marginal Likelihood From the Metropolis-Hastings Output," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 270-281, March. [Downloadable!] (restricted)
  10. Butler, J S & Moffitt, Robert, 1982. "A Computationally Efficient Quadrature Procedure for the One-Factor Multinomial Probit Model," Econometrica, Econometric Society, vol. 50(3), pages 761-64, May. [Downloadable!] (restricted)
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Timothy J Halliday, 2005. "Heterogeneity, State Dependence and Health," Working Papers 200503, University of Hawaii at Manoa, Department of Economics. [Downloadable!]
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  2. Shiko Maruyama, 2008. "Measuring the Welfare Effect of Entry in Differentiated Product Markets: The Case of Medicare HMOs," Discussion Papers 2008-01, School of Economics, The University of New South Wales. [Downloadable!]
  3. Shiko Maruyama, 2006. "Welfare Analysis Incorporating a Structural Entry-Exit Model: A Case Study of Medicare HMOs," Hi-Stat Discussion Paper Series d06-166, Institute of Economic Research, Hitotsubashi University. [Downloadable!]
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