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Multimodality in the distribution of GDP and the absolute convergence hypothesis

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Abstract

This article shows that, contrary to common wisdom, the insurgence of a multiplicity of clusters in the distribution of income is not necessarily against the hypothesis of absolute convergence. Using data for the world economies, the US states, the EU regions, and the Italian regions, we find that despite the distribution of income per capita for both the world economies and for the Italian regions is multimodal, only in the former case absolute convergence can be rejected. Similarly, although the distributions for the EU regions and the US states are both unimodal, convergence is unambiguously taking place in the latter case only. We show that these results are consistent with the neoclassical model of growth in the presence of non-convexities in production. We conclude that polarization in the distribution of per capita incomes is neither a sufficient nor a necessary condition to reject the absolute convergence hypothesis.

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References

  • Abramovitz M (1986) Catching up, forging ahead and falling behind. J Econ Hist 46: 385–406

    Article  Google Scholar 

  • Barro RJ, Sala-i-Martin X (1991) Convergence across States and Regions. Brookings Paper Econ Act 1: 1107–1182

    Google Scholar 

  • Barro RJ, Sala-i-Martin X (1992) Convergence. J Polit Econ 100: 223–251

    Article  Google Scholar 

  • Baumol WJ (1986) Productivity growth, convergence, and welfare: what the long run data show. Am Econ Rev 75: 1072–1085

    Google Scholar 

  • Beaudry P, Collard F, Green D (2005) Changes in the world distribution of output-per-capita 1960–98: how a standard decomposition tells an unorthodox story. Rev Econ Stat 87: 741–753

    Article  Google Scholar 

  • Bianchi M (1997) Testing for convergence: evidence from non-parametric multimodality test. J Appl Econ 12: 393–409

    Article  Google Scholar 

  • Duclos J-Y, Esteban J, Ray D (2004) Polarization: concepts, measurement and estimation. Econometrica 72: 1737–1772

    Article  Google Scholar 

  • Galor O (1996) Convergence? Inference from theoretical models. Econ J 106: 1056–1069

    Article  Google Scholar 

  • Islam N (2003) What have we learnt from the convergence debate. J Econ Surv 17: 309–362

    Article  Google Scholar 

  • Johnson PA (2000) A nonparametric analysis of income convergence across the US states. Econ Lett 69: 219–223

    Article  Google Scholar 

  • Johnson NL, Kotz S, Balakrishnan N (1994) Continuous univariate distributions, Vol 1, 2nd edn. Wiley Series in Probability and Mathematical Statistics, New York

    Google Scholar 

  • Jones C (1997) On the evolution of the world income distribution. J Econ Perspect 11: 19–36

    Article  Google Scholar 

  • Leonida L (2004) On the effects of industrialization processes on growth and convergence dynamics: evidence from Italian regions, Discussion paper series no 15, University of York

  • Marron JS, Schmitz HP (1992) Simultaneous density estimation of several income distributions. Econ Theory 8: 476–488

    Article  Google Scholar 

  • Paap R, Van Dijk HK (1998) Distribution and mobility of wealth of nations. Eur Econ Rev 42: 135–165

    Google Scholar 

  • Pittau MG, Zelli R (2006) Empirical evidence of income dynamics across EU regions. J Appl Econ 21: 605–628

    Article  Google Scholar 

  • Quah D (1993) Galton’s Fallacy and tests of the convergence hypothesis. Scand J Econ 95: 427–443

    Article  Google Scholar 

  • Quah D (1996a) Convergence empirics across economies with (some) capital mobility. J Econ Growth 1: 95–124

    Article  Google Scholar 

  • Quah D (1996b) Regional convergence clusters across Europe. Eur Econ Rev 40(5): 951–958

    Article  Google Scholar 

  • Quah D (1997) Empirics for growth and distribution: stratification, polarization and convergence clubs. J Econ Growth 2: 27–59

    Article  Google Scholar 

  • Scheater SJ, Jones MC (1992) A reliable data-based bandwidth selection method for kernel density estimation. J R Stat Soc B 53: 683–690

    Google Scholar 

  • Silverman BW (1981) Using Kernel density to investigate multimodality. J R Stat Soc B 43: 97–99

    Google Scholar 

  • Terrasi M (1999) Convergence and divergence across Italian regions. Ann Reg Sci 4: 491–511

    Article  Google Scholar 

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Correspondence to Giovanni Caggiano.

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Caggiano, G., Leonida, L. Multimodality in the distribution of GDP and the absolute convergence hypothesis. Empir Econ 44, 1203–1215 (2013). https://doi.org/10.1007/s00181-012-0574-4

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  • DOI: https://doi.org/10.1007/s00181-012-0574-4

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