Obesity and labour market outcomes in Italy: a dynamic panel data evidence with correlated random effects.

Autor: Pacifico A; Applied Statistics and Econometrics, University of Macerata, Macerata, Italy. antonio.pacifico@unimc.it.
Jazyk: angličtina
Zdroj: The European journal of health economics : HEPAC : health economics in prevention and care [Eur J Health Econ] 2023 Jun; Vol. 24 (4), pp. 557-574. Date of Electronic Publication: 2022 Jul 22.
DOI: 10.1007/s10198-022-01493-3
Abstrakt: This paper investigates the effects of obesity, socio-economic variables, and individual-specific factors on work productivity across Italian regions. A dynamic panel data with correlated random effects is used to jointly deal with incidental parameters, endogeneity issues, and functional forms of misspecification. Methodologically, a hierarchical semiparametric Bayesian approach is involved in shrinking high dimensional model classes, and then obtaining a subset of potential predictors affecting outcomes. Monte Carlo designs are addressed to construct exact posterior distributions and then perform accurate forecasts. Cross-sectional Heterogeneity is modelled nonparametrically allowing for correlation between heterogeneous parameters and initial conditions as well as individual-specific regressors. Prevention policies and strategies to handle health and labour market prospects are also discussed.
(© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)
Databáze: MEDLINE
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