Health Investment and Long run Macroeconomic Performance:a quantile regression approach
This paper analyses the relationship between health human capital and economic growth for a maximum sample of 92 countries over the period 1980-2010 applying the methodology proposed by Canay (2011) for regression by quantiles (Koenker 1978; 2004; 2012a,b) in a panel framework. This approach allows for the identification of different impacts of the explanatory variables across the growth rate distribution. According to Mello & Perelli (2003), quantile regression allows to capture countries’ heterogeneity and assess how policy variables affect different countries according to their position on the conditional growth distribution. Quantile regression analysis allows us to identify those growth determinants that do not have the expected relationship with growth and hence determine the policy implications specifically for under-performing versus over achieving countries in terms of output growth. Our findings indicate that better health is positively and robustly related to growth at all quantiles, but the quantitative importance of the respective coefficients differs across quantiles in some cases, with the sign of the relationship greater for countries that recorded lower growth rates. These results apply to both positive (life expectancy, consumption of calories per person per day) and negative (infant mortality rate, prevalence of undernourishment in populations) health status indicators. Given the predominantly public nature of health funding, cuts in health expenditures should thus be carefully balanced even in times of public finances sustainability problems, particularly in times of growth slowdowns, since a decrease in the stock of health human capital can be particularly harmful for growth for under achievers.
health; human capital; economic growth; quantile regression.