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Is there convergence across countries? A spatial approach

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Abstract

We analyze convergence across countries over the last half century as a result of globalizing forces. Drawing on theories of modernization, dependency, the world-system, political trade blocs, and the world-society, we consider economic, demographic, knowledge, financial, and political dimensions of convergence. Using a new methodology, we calculate the minimum volume ellipsoid encompassing different groupings of countries, finding that during the 1960–2009 period, countries have not evolved significantly closer or similar to one another, although groups of countries based on their core-periphery status or membership in trade blocs exhibit increasing internal convergence and divergence between one another.

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Notes

  1. k is in general different for each distance dimension.

  2. In empirical studies on convergence in the economics literature, it is common to use either a regression of growth rates (the beta measure) to examine whether countries are converging to the same steady-state levels (Barro, 1997) or coefficients of variation (the sigma measure) of economic data over time (Ertur, LeGallo, & Baumont, 2006; Magrini, 2004). The approach we adopt in this paper is closer to economic studies that have examined coefficients of variation, but we include a broader definition (beyond economic variables) of how countries can differ. In addition, we incorporate a spatial dimension into our analysis by constructing an MVE measure, which determines the extent to which country points compress or expand over time.

  3. Mathematically, this property is derived from the fact that the MVE measure is invariant to affine transformations of V t . If we were to premultiply each v∈∪V t by the same fixed, non-singular matrix and add a k-vector to each product, the resultant volumes would not be affected except perhaps by a constant multiple. Since the MVE measure is an index, the constant multiple is irrelevant and would not affect our inference (proof available upon request).

  4. One important point about the MVE method is that it assumes an ellipsoidal form. There are good reasons to assume an ellipsoid as opposed to other shapes. First, as mentioned above, the MVE is not affected by time-invariant issues of correlation and scale (covariance and variance). Consider the following example. A country’s university enrollments, the number of patents a country issues, and the number of scientific articles a country publishes are highly correlated. If we are using all of these variables to determine the world’s volume, we would ideally like to measure the volume on a de-correlated scale. Otherwise, the distance between countries would be artificially inflated (or deflated) and this would in turn artificially inflate (deflate) the volume. The MVE volume is not susceptible to this problem. Also, the variables are measured on different scales (enrollments per 10,000 population, patents per million population, and articles per million population) and thus may not be directly comparable. The MVE volume measure is not susceptible to this issue either.

  5. A regression of volumes on time shows similar patterns of rejection. Kendall’s tau, however, is less restrictive due to its ordinal nature.

  6. The correlations between the MVE and median-based volumes for the economic, demographic, knowledge, financial, and political distance dimensions are, respectively: 0.87, 0.42, 0.79, 0.72, and −0.39.

  7. For all subcomponents, we calculate the Kendall’s tau trend tests restricting the years to 1985–2009. The rejection patterns are similar to the full set of volumes (1960–2009), indicating a lack of evidence for recent convergence.

  8. We calculated the Mahalanobis distance between each country point and the arithmetic mean of all NAFTA country points. We used the maximum of these distances as the hypersphere’s radius.

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Acknowledgements

We thank Associate Editor Ulf Andersson, anonymous referees, Jason Beckfield, Bruce Carruthers, Nitsan Chorev, Frank Dobbin, Vit Henisz, Paul Ingram, Paul DiMaggio, and participants in the World Bank Seminar for helpful comments on earlier versions of this paper. This research received support from the Population Research Training grant (NIH T32 HD007242) from the National Institutes of Health’s (NIH)’s Eunice Kennedy Shriver National Institute of Child Health and Human Development and from the Demography of Aging grant (NIH T32 AG000177) from the National Institutes of Health’s (NIH)’s National Institute on Aging awarded to the Population Studies Center at the University of Pennsylvania. We also acknowledge funding from the Penn Lauder CIBER institute for the collection of the data used in this paper.

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Authors and Affiliations

  1. George Washington University School of Business, Washington DC, USA

    Heather Berry

  2. The Wharton School, University of Pennsylvania, Philadelphia, USA

    Mauro F Guillén

  3. Population Studies Center, University of Pennsylvania, Philadelphia, USA

    Arun S Hendi

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  1. Heather Berry
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  2. Mauro F Guillén
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Correspondence to Heather Berry.

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Accepted by Ulf Andersson, Area Editor, 17 December 2013. This paper has been with the authors for two revisions.

APPENDIX

APPENDIX

Table A1

Table A1 Trade bloc member states
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Berry, H., Guillén, M. & Hendi, A. Is there convergence across countries? A spatial approach. J Int Bus Stud 45, 387–404 (2014). https://doi.org/10.1057/jibs.2013.72

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