
handle: 10419/270551
Empirical studies show that years of schooling are positively correlated with good health, and that education is better correlated with health than with variables like occupation and income. This can be explained in different ways as the implication may go from education to health, from health to education, and there may be variables that influence health and education in the same direction. The effect of different policy instruments to reduce the social gradient in health will depend on the strength of these causalities. In this paper we formalize a model that simultaneously determines an individual’s demand for knowledge and health based on the mentioned causal effects. We study the impacts on both health and education of different policy instruments such as subsidies on medical care, subsidizing schooling, income tax reduction, lump sum transfers and improving health at young age. Our results indicate that income transfers such as distributional policies may be the best instrument to improve welfare, while subsidies to medical care is the best instrument for longevity. However, subsidies to medical care or education would require large imperfections in the markets for health and education to be more welfare improving than distributional policies. Finally, our simulations suggest that underlying factors that impact both health and education is the main explanation for the correlation shown empirically.
CINCH working paper series, vol. 2015, no. 06
330, 610, Demand for health -- Demand for education -- Human capital -- Numerical modeling -- Causality, Periodical, Numerical modeling, D91, Demand for health, Demand for education, Human capital, Numerical modeling, Causality, Human capital, Fakultät für Wirtschaftswissenschaften, Demand for health; Demand for education; Human capital; Numerical modeling; Causality, ddc:610, ddc:330, I12, Causality, C61, Demand for education, Demand for health, I21, jel: jel:C61, jel: jel:I21, jel: jel:D91, jel: jel:I12
330, 610, Demand for health -- Demand for education -- Human capital -- Numerical modeling -- Causality, Periodical, Numerical modeling, D91, Demand for health, Demand for education, Human capital, Numerical modeling, Causality, Human capital, Fakultät für Wirtschaftswissenschaften, Demand for health; Demand for education; Human capital; Numerical modeling; Causality, ddc:610, ddc:330, I12, Causality, C61, Demand for education, Demand for health, I21, jel: jel:C61, jel: jel:I21, jel: jel:D91, jel: jel:I12
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