Analysing Convergence through the Distribution Dynamics Approach: Why and How?

41 Pages Posted: 5 Sep 2007

See all articles by Stefano Magrini

Stefano Magrini

Ca Foscari University of Venice - Dipartimento di Economia

Date Written: September 2007

Abstract

The convergence hypothesis has stimulated a heated debate within the growth literature. The present paper compares the two most commonly adopted empirical approaches, the regression approach and the distribution dynamics approach, and argues that the former fails to uncover important features of the dynamics that might characterise the convergence process. Next, it provides an in depth description of the features and underlying assumptions of the distribution dynamics approach as well as a detailed discussion of some important aspects related to the estimate of stochastic kernels via kernel density estimators. Finally, the empirical section allows to emphasises the interpretational advantages stemming from the use of stochastic kernels to capture the evolution of the entire cross-sectional income distribution. Incidentally, through a comparison between the results obtained from alternative sets of Italian regions, it suggest that the use of administrative regions could lead to ambiguous results.

Keywords: Distribution Dynamics, Stochastic Kernel, Kernel Density Estimation, Regions

JEL Classification: C14, C20, O40, O52, R10

Suggested Citation

Magrini, Stefano, Analysing Convergence through the Distribution Dynamics Approach: Why and How? (September 2007). University Ca' Foscari of Venice, Dept. of Economics Research Paper Series No. 13/WP/2007, Available at SSRN: https://ssrn.com/abstract=1011946 or http://dx.doi.org/10.2139/ssrn.1011946

Stefano Magrini (Contact Author)

Ca Foscari University of Venice - Dipartimento di Economia ( email )

Cannaregio 873
Venice, 30121
Italy

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