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ANDREA MARIO LAVEZZI

On the Determinants of Distribution Dynamics

Abstract

n this paper we propose a novel approach to identify the impact of growth determinants on the distribution dynamics of productivit y. Our approach integrates counterfactual analysis with the estima tion of stochastic kernels. The counterfactuals are constructed from a semi-parametric growth regression, in which the cross-section heterogeneity 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 proposed methodology by an application to a cross-section of countries, which highlights the significant impact on inequality and polarization in the world productivity distribution of growth determinants from an augmented Solow model.