Health-related non-response in the BHPS and ECHP: using inverse probability weighted estimators in nonlinear models
AbstractThis paper considers health-related non-response in the first eleven waves of the British Household Panel Survey (BHPS) and the full eight waves of the European Community Household Panel (ECHP) and explores its consequences for dynamic models of the association between socioeconomic status and self-assessed health (SAH). We describe the pattern of health-related non-response revealed by the BHPS and ECHP data. We both test and correct for non-response in empirical models of the impact of socioeconomic status on self-assessed health. Descriptive evidence shows that there is health-related non-response in the data, with those in very poor initial health more likely to drop out, and variable addition tests provide evidence of nonresponse bias in the panel data models of SAH. Nevertheless a comparison of estimates - based on the balanced sample, the unbalanced sample and corrected for non-response using inverse probability weights (IPW) – shows that, on the whole, there are not substantive differences in the average partial effects (APE) of the variables of interest. The main differences are between unweighted and one form of IPW-weighted estimates for the APE of income and education in those countries that have fewer than eight waves of data. Similar findings have been reported concerning the limited influence of non-response bias in models of various labour market outcomes; we discuss possible explanations for our results.
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Bibliographic InfoPaper provided by HEDG, c/o Department of Economics, University of York in its series Health, Econometrics and Data Group (HEDG) Working Papers with number 05/05.
Date of creation: Jun 2005
Date of revision:
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Postal: HEDG/HERC, Department of Economics and Related Studies, University of York, York, YO10 5DD, United Kingdom
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Web page: http://www.york.ac.uk/economics/postgrad/herc/hedg/
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Self-assessed health; attrition; non-response; non-participation; selection on observables; inverse probability weighting; BHPS; ECHP;
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