by Andrés Erosa, Tatyana Koreshkova and Diego Restuccia
We develop a quantitative theory of human capital investments in order to evaluate the magnitude of cross-country differences in total factor productivity (TFP) that explains the variation in per-capita incomes across countries. We build a heterogeneous-agent economy with cross-sectional variation in ability, schooling, and expenditures on schooling quality. By embedding our analysis in a growth model with tradable and non-tradable sectors, we model sectorial productivity differences across countries, as documented in Hsieh and Klenow (2007). The parameters governing human capital production and random ability and taste processes are restricted by a set of cross-sectional data moments such as variances and intergenerational correlations of earnings and schooling, as well as slope coefficient and R2 in a Mincer regression. Our main finding is that human capital accumulation strongly amplifies TFP differences across countries: To explain a 20-fold difference in the output per worker the model requires a 5-fold difference in the TFP of the tradable sector, versus an 18-fold difference if human capital is fixed across countries. Moreover, we find that sectorial productivity differences play a prominent role in quantitative implications of the theory.
There is plenty of empirical literature trying to establish the importance of human capital in cross-country income differences, usually neglecting that human capital may be endogenous. Clearly, a more structural approach is warranted and this paper delivers this, along with a very rich model. Will this paper convince the cross-country regression enthousiasts?