The effects of self-assessed health: Dealing with and understanding misclassification bias

Linkun Chen, Philip M. Clarke, Dennis Petrie and Kevin Staub

Journal of Health Economics, 2021, vol. 78, issue C

Abstract: Self-assessed health (SAH) is often used in health econometric models as the key explanatory variable or as a control variable. However, there is evidence questioning its test-retest reliability, with up to 30% of individuals changing their response. Building on recent advances in the econometrics of misclassification, we develop a way to consistently estimate and account for misclassification in reported SAH by using data from a large representative longitudinal survey where SAH was elicited twice. From this we gain new insights into the nature of SAH misclassification and its potential for biasing health econometric estimates. The results from applying our approach to nonlinear models of long-term mortality and chronic morbidities reveal that there is substantial heterogeneity in misclassification patterns. We find that adjusting for misclassification is important for estimating the impact of SAH. For other explanatory variables of interest, we find significant but generally small changes to their estimates when SAH misclassification is ignored.

Keywords: Misreporting; Measurement error; Multinomial regressor; Discrete and limited dependent variables; Subjective health; Mortality; Chronic conditions (search for similar items in EconPapers)
JEL-codes: C35 I12 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Working Paper: The effects of self-assessed health: Dealing with and understanding misclassification bias (2018)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jhecon:v:78:y:2021:i:c:s0167629621000485

DOI: 10.1016/j.jhealeco.2021.102463

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