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GDP clustering: A reappraisal

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  • Battisti, Michele
  • Parmeter, Christopher F.

Abstract

This note explores clustering in cross country GDP per capita using recently developed model based clustering methods for panel data. Previous research characterizing the components of the overall distribution of output either use ad hoc methods, or methods which ignore/subvert the panel nature of the data. These new methods allow the characterization of the possible autoregressive relationship of output between time points. We show that traditional static clustering decade by decade gives mixed results regarding clustering over time, while the application of longitudinal mixtures presents three distinct clusters at all periods of time.

Suggested Citation

  • Battisti, Michele & Parmeter, Christopher F., 2012. "GDP clustering: A reappraisal," Economics Letters, Elsevier, vol. 117(3), pages 837-840.
    • Handle: RePEc:eee:ecolet:v:117:y:2012:i:3:p:837-840
    DOI: 10.1016/j.econlet.2012.08.038
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    References listed on IDEAS

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    1. Quah, Danny, 1993. "Empirical cross-section dynamics in economic growth," European Economic Review, Elsevier, vol. 37(2-3), pages 426-434, April.
    2. Pittau, Maria Grazia & Zelli, Roberto & Johnson, Paul, "undated". "Mixture Models and Convergence Clubs," Vassar College Department of Economics Working Paper Series 91, Vassar College Department of Economics.
    3. Fraley C. & Raftery A.E., 2002. "Model-Based Clustering, Discriminant Analysis, and Density Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 611-631, June.
    4. Michele Battisti & Christopher F. Parmeter, 2011. "Income Polarization, Convergence Tools and Mixture Analysis," Working Papers 2011-17, University of Miami, Department of Economics.
    5. Maria Grazia Pittau & Roberto Zelli & Paul A. Johnson, 2010. "Mixture Models, Convergence Clubs, And Polarization," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 56(1), pages 102-122, March.
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    Citations

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    Cited by:

    1. Battisti, Michele & Delgado, Michael S. & Parmeter, Christopher F., 2015. "Evolution of the global distribution of carbon dioxide: A finite mixture analysis," Resource and Energy Economics, Elsevier, vol. 42(C), pages 31-52.
    2. Yao, Feng & Wang, Taining & Tian, Jinjing & Kumbhakar, Subal C., 2018. "Estimation of a smooth coefficient zero-inefficiency panel stochastic frontier model: A semiparametric approach," Economics Letters, Elsevier, vol. 166(C), pages 25-30.
    3. Battisti, Michele & Parmeter, Christopher F., 2013. "Clustering and polarization in the distribution of output: A multivariate perspective," Journal of Macroeconomics, Elsevier, vol. 35(C), pages 144-162.
    4. Tsionas, Mike G., 2019. "Transition and limiting distributions when covariates are available," Economics Letters, Elsevier, vol. 183(C), pages 1-1.
    5. Carlos Mendez, 2019. "Lack of Global Convergence and the Formation of Multiple Welfare Clubs across Countries: An Unsupervised Machine Learning Approach," Economies, MDPI, vol. 7(3), pages 1-17, July.
    6. Kindberg-Hanlon,Gene & Okou,Cedric Iltis Finafa, 2020. "Productivity Convergence : Is Anyone Catching Up?," Policy Research Working Paper Series 9378, The World Bank.

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    More about this item

    Keywords

    Mixture densities; Output; Autoregressive; Isotropic;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration
    • O16 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Financial Markets; Saving and Capital Investment; Corporate Finance and Governance
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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