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Oreste Napolitano, Mariafortuna Pietroluongo and Konstantinos Kounetas
''Stochastic Convergence or Divergence of Total Factor Productivity and GDP of Italian Regions. Re-examing the Evidence.''
( 2018, Vol. 38 No.4 )
In this paper, we apply the non-parametric method proposed by Quah to examine convergence hypothesis for Italian regions using GDP and total factor productivity measured by the Malmquist index. Using the stochastic kernel approach, this study suggests that the measure of total factor productivity is a crucial precondition for the estimation of a region's growth. Our results applied to the 20 Italian regions show no convergence for both GDP and TFP variables. For the GDP case, it confirms the Italian divide but for the TFP variable, it reveals the creation of three clubs. However, looking at the long-run density, it reveals that the shape of the ergodic density distribution, for the TFP, is clearly unimodal and it could imply a long-run convergence of regional productivity in Italy.
Keywords: Total Factor Productivity, Stochastic Kernel, Convergence, Italian Regions.
JEL: D2 - Production and Organizations: General
O4 - Economic Growth and Aggregate Productivity: General
Manuscript Received : Jun 24 2018 Manuscript Accepted : Oct 10 2018

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