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Alternative approaches to regional convergence exploiting both spatial and temporal information

Author

Listed:
  • ARBIA, G.

    (University "G. D´annunzio" (Italy) and USI (CH))

Abstract

The standard approaches used in the empirical literature to test economic convergence-divergence between countries and regions are all grounded on the Mankiw-Romer-Weil and Barro-Sala-i-Martin contributions that led to the celebrated b-convergence model. Such a model, however, presents strong limitations related to the fact that it compares two situations in two different moments of time rather than monitoring the entire time path of the regional GDP. This is a major drawback because very different situations may lead to the same results in terms of the speed of convergence and this may cause problems in interpreting the results and in using them when programming regional politics and when targeting spatial re-equilibrating resources. This paper reviews some of the approaches proposed in the literature that seek to overcome this obstacle and aim to capture the full dynamics of the economic convergence process. Four approaches are reviewed. The first is based on the theory of space-time processes, the second is a spatial versions of panel data modelling, the third is grounded on a spatially adjusted continuous time specification and the fourth on the concept of stochastic convergence as it was developed in the time series literature. Las aproximaciones estándar utilizadas en la literatura empírica para contrastar la convergencia-divergencia económica entre los países y regiones están todas relacionadas con las contribuciones de Mankiw-Romer-Weil y Barro-Sala-i-Martin que llevan al celebrado modelo de ? convergencia. Tal modelo, sin embargo, presenta fuertes limitaciones relacionadas al hecho de que compara dos situaciones en dos momentos diferentes de tiempo en lugar de supervisar la senda temporal entera del PIB regional. Ésta es una desventaja importante porque situaciones muy diferentes pueden llevar a los mismos resultados por lo que se refiere a la velocidad de convergencia y esto puede causar problemas al interpretar los resultados y al utilizarlos cuando se programan políticas regionales. Este papel revisa algunas de las aproximaciones propuestas en la literatura que buscan superar este obstáculo y que tienen por objetivo capturar las dinámicas completas del proceso de convergencia económico. Se revisan cuatro aproximaciones. La primera está basada en la teoría de procesos espacio-temporales, la segunda es una versión espacial de la modelización de datos panel, la tercera se basa en una especificación temporal continua ajustada espacialmente y la cuarta en el concepto de convergencia estocástica, tal y como se ha desarrollado en la literatura de series temporales.

Suggested Citation

  • Arbia, G., 2004. "Alternative approaches to regional convergence exploiting both spatial and temporal information," Estudios de Economía Aplicada, Estudios de Economía Aplicada, vol. 22, pages 1-18, Diciembre.
  • Handle: RePEc:lrk:eeaart:22_3_3
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    References listed on IDEAS

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    1. Hashem Pesaran, M., 2007. "A pair-wise approach to testing for output and growth convergence," Journal of Econometrics, Elsevier, vol. 138(1), pages 312-355, May.
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    More about this item

    Keywords

    Regional convergence; Stochastic convergence; Spatial panel data models; Spatial dependence modeling; Continuous time econometrics; Unit-roots; Systems of differential equationsd;

    JEL classification:

    • 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
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes

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