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

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  • Stefano Magrini

    ()
    (Department of Economics, University Of Venice Cà Foscari)

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.

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Bibliographic Info

Paper provided by Department of Economics, University of Venice "Ca' Foscari" in its series Working Papers with number 2007_13.

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Length: 40 pages
Date of creation: 2007
Date of revision:
Handle: RePEc:ven:wpaper:2007_13

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Keywords: Distribution Dynamics; Stochastic Kernel; Kernel Density Estimation; beta-convergence; Regions;

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References

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Cited by:
  1. Silvia Dal Bianco, 2009. "A Reassessment of Italian Regional Convergence through a Non-Parametric Approach," Quaderni di Dipartimento 099, University of Pavia, Department of Economics and Quantitative Methods.
  2. Daniele, Vittorio, 2009. "Regional convergence and public spending in Italy. Is there a correlation?," MPRA Paper 14334, University Library of Munich, Germany.

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