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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Paper provided by University of Venice "Ca' Foscari", Department of Economics in its series Working Papers with number
2007_13.
Find related papers by JEL classification: C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General O40 - Economic Development, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General O52 - Economic Development, Technological Change, and Growth - - Economywide Country Studies - - - Europe R10 - Urban, Rural, and Regional Economics - - General Regional Economics - - - General
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