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Does Self-Assessed Health Reflect the True Health State?

Pavitra Paul, Ulrich Nguemdjo, Natalia Kovtun and Bruno Ventelou
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Pavitra Paul: CNRS, UMIFRE 20 CSH, CNRS-MAE - Partenaires INRAE, Yerevan State Medical University
Ulrich Nguemdjo: AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique, LPED - Laboratoire Population-Environnement-Développement - IRD - Institut de Recherche pour le Développement - AMU - Aix Marseille Université
Natalia Kovtun: Taras Shevchenko National University of Kyiv

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Abstract: Self-assessed health (SAH) is a widely used tool to estimate population health. However, the debate continues as to what exactly this ubiquitous measure of social science research means for policy conclusions. This study is aimed at understanding the tenability of the construct of SAH by simultaneously modelling SAH and clinical morbidity. Using data from 17 waves (2001–2017) of the Russian Longitudinal Monitoring Survey, which captures repeated response for SAH and frequently updates information on clinical morbidity, we operationalise a recursive semi-ordered probit model. Our approach allows for the estimation of the distributional effect of clinical morbidity on perceived health. This study establishes the superiority of inferences from the recursive model. We illustrated the model use for examining the endogeneity problem of perceived health for SAH, contributing to population health research and public policy development, in particular, towards the organisation of health systems.

Keywords: clinical morbidity; endogeneity; perceived health; recursive; semi-ordered; Russia (search for similar items in EconPapers)
Date: 2021-11
New Economics Papers: this item is included in nep-cis, nep-hea and nep-tra
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Published in International Journal of Environmental Research and Public Health, 2021, 18 (21), pp.11153. ⟨10.3390/ijerph182111153⟩

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DOI: 10.3390/ijerph182111153

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