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Le verifiche empiriche dell'ipotesi di convergenza

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  • Rosa Capolupo

    () (University of Bari)

Abstract

This paper is a selective review of the literature on the conditional convergence prediction implied by the neoclassical Ramsey-Cass Koopmans version of the growth model. The new stylized facts of increasing disparity and variations of income per capita and growth rates across countries and across time seem to support the theoretical predictions of the competing endogenous growth models. In the ongoing debate the correspondence of the theoretical predictions of both theories to basic facts of growth is left to the empirical analysis. After reviewing the most significant econometric studies which found convergence by running cross section growth regressions, we conclude that the criticism to which these estimates have been subjected are methodologically founded. Progress on this central issue can be made through new empirical estimates bases on the time series approach.

Suggested Citation

  • Rosa Capolupo, 1999. "Le verifiche empiriche dell'ipotesi di convergenza," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 58(3-4), pages 377-421, December.
  • Handle: RePEc:gde:journl:gde_v58_n3-4_377-421
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    More about this item

    Keywords

    convergenza; modelli di crescita; test cross-sezionali; serie temporali;

    JEL classification:

    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General
    • O41 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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