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

Antonio Pacifico ()
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Antonio Pacifico: University of Macerata

The European Journal of Health Economics, 2023, vol. 24, issue 4, No 6, 557-574

Abstract: Abstract 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.

Keywords: Bayesian inference; MCMC algorithms; Density forecasts; Heterogeneous effects; Healthcare Statistics; Work productivity (search for similar items in EconPapers)
JEL-codes: A1 C01 E02 H3 N01 O4 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10198-022-01493-3

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