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Stochastic Convergence or Divergence of Total Factor Productivity and GDP of Italian Regions. Re-examing the Evidence

Author

Listed:
  • Oreste Napolitano

    (Department of Business and Economic Studies, University of Naples Parthenope)

  • Mariafortuna Pietroluongo

    (Department of Business and Economic Studies, University of Naples Parthenope)

  • Konstantinos Kounetas

    (Department of Economics University of Patra, Greece - Visiting professor University of Parthenope)

Abstract

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.

Suggested Citation

  • Oreste Napolitano & Mariafortuna Pietroluongo & Konstantinos Kounetas, 2018. "Stochastic Convergence or Divergence of Total Factor Productivity and GDP of Italian Regions. Re-examing the Evidence," Economics Bulletin, AccessEcon, vol. 38(4), pages 1857-1863.
    • Handle: RePEc:ebl:ecbull:eb-18-00523
    as

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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Total Factor Productivity; Stochastic Kernel; Convergence; Italian Regions.;
    All these keywords.

    JEL classification:

    • D2 - Microeconomics - - Production and Organizations
    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity

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