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Comparative Spatial Dynamics of Regional Systems

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Progress in Spatial Analysis

Part of the book series: Advances in Spatial Science ((ADVSPATIAL))

Abstract

Research on the question of regional income convergence has gone through two phases over the past two decades. The first generation of regional convergence studies began to appear as growth theorists turned their attention away from international analyses of country growth patterns having discovered the region as a new unit of analysis (Barro and Sala-i-Martin 1991). This change in scale had a key advantage of increasing (in some cases substantially) the number of cross-sectional observations available for model estimation and hypothesis testing. While the scale of the analysis shifted, these first generation studies relied on the same underlying theoretical and empirical frameworks used in the international literature. In the second phase, the underlying geographical dimensions of the data in convergence studies began to attract attention (Rey and Montouri 1999). This was reflected in several developments. The first saw the increasing application of the methods of spatial econometrics and spatial data analysis to regional case studies. These applications have generated abundant evidence that the spatial effects of dependence and heterogeneity tend to be the rule rather than the exception in practice, and as such their consideration should form a crucial component of empirical analysis. Thus the second generation of regional convergence studies is those characterized by concerns with spatial effects.

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Notes

  1. 1.

    For recent overviews of this literature see Rey and Le Gallo (2008), Rey and Janikas (2006), Abreu et al. (2005) and Fingleton (2003).

  2. 2.

    While China’s official GDP statistics are sometimes regarded as of questionable quality (Rawski 2001), the NSB (National Statistical Bureau of China) published adjusted GDP data to deal with both overestimates and underestimates of provincial GDP data for the years before 2004 (Fan and Sun 2008). For a recent discussion justifying using per capita GDP as a valid and reliable indicator of provincial economic development and well-being in China, see Fan and Sun (2008).

  3. 3.

    The national trends in both system have been removed from the regional data sets here as the income values are expressed as percentages of the national means for the given year.

  4. 4.

    Under the random labeling approach, the null hypothesis is that mobility rates are the same in the two countries.

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Authors and Affiliations

  1. Department of Geography, San Diego State University and School of Geographical Sciences, Arizona State University, 875302, Tempe, AZ, 85287, USA

    Sergio J. Rey

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  1. Sergio J. Rey
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  2. Xinyue Ye
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Correspondence to Sergio J. Rey .

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Editors and Affiliations

  1. School of Geography & Earth Sciences, McMaster University, Main Street West 1280, Hamilton, L8S 4K1, Canada

    Antonio Páez

  2. CRESE, Universite de Franche Comti, avenue de l'observatoire 45D, Besancon CX, 25030, France

    Julie Gallo

  3. Dept. Geography, University of Toronto, Mississauga, Mississauga Road N. 3359, Mississauga, L5L 1C6, Canada

    Ron N. Buliung

  4. Regional Economics Applications, University of Illinois, S. Mathews Ave. 220 607, Urbana, 61801-3671, U.S.A.

    Sandy Dall'erba

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Rey, S.J., Ye, X. (2010). Comparative Spatial Dynamics of Regional Systems. In: Páez, A., Gallo, J., Buliung, R., Dall'erba, S. (eds) Progress in Spatial Analysis. Advances in Spatial Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03326-1_20

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