Using simulation-based inference with panel data in health economics.

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).

journal_name

Health Econ

journal_title

Health economics

authors

Contoyannis P,Jones AM,Leon-Gonzalez R

doi

10.1002/hec.811

keywords:

subject

Has Abstract

pub_date

2004-02-01 00:00:00

pages

101-22

issue

2

eissn

1057-9230

issn

1099-1050

journal_volume

13

pub_type

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