Year: 2013
Type: preprint
Abstract: In this paper we propose a novel approach to identify the impact of growth deter-minants on the distribution dynamics of productivity. Our approach integrates coun-terfactual analysis with the estimation of stochastic kernels. The counterfactuals are constructed from a semiparametric growth regression, in which the cross-section het-erogeneity in the growth determinants is removed. The methodology also allows us to test for potential distributional effects in the residuals. We illustrate the usefulness of the proposedmethodology by an application to a cross-section of countries, which high-lights the significant impact on inequality and polarization in the world productivity distribution of growth determinants from an augmented Solow model.
Institution: University of Pisa
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W600522137