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Clustering and polarization in the distribution of output: A multivariate perspective

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  • Battisti, Michele
  • Parmeter, Christopher F.

Abstract

Modeling the cross-country distribution of per capita income using mixture analysis provides a natural platform for the detection of clubs of countries. Unfortunately, these mixture methods, when based on a strictly univariate approach are limiting towards one’s ability to learn about the underlying process of the emergence of what constitutes a club. This paper takes a fresh look at the constitution of the emerging clubs in the distribution of cross-country output using bivariate and multivariate mixture analysis. Our results suggest that clubs are also forming in the main Solowian determinants of economic growth.

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  • 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.
    • Handle: RePEc:eee:jmacro:v:35:y:2013:i:c:p:144-162
    DOI: 10.1016/j.jmacro.2012.10.003
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    Cited by:

    1. Tsionas, Mike G., 2019. "Transition and limiting distributions when covariates are available," Economics Letters, Elsevier, vol. 183(C), pages 1-1.
    2. Antonello Maruotti & Pierfrancesco Alaimo Di Loro, 2023. "CO2 emissions and growth: A bivariate bidimensional mean‐variance random effects model," Environmetrics, John Wiley & Sons, Ltd., vol. 34(5), August.
    3. Shana M. Sundstrom & Craig R. Allen & David G. Angeler, 2020. "Scaling and discontinuities in the global economy," Journal of Evolutionary Economics, Springer, vol. 30(2), pages 319-345, April.
    4. 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.
    5. Amini, Shahram & Battisti, Michele & Parmeter, Christopher F., 2017. "Decomposing changes in the conditional variance of GDP over time," Economic Modelling, Elsevier, vol. 61(C), pages 376-387.
    6. 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.
    7. Paul Johnson & Chris Papageorgiou, 2020. "What Remains of Cross-Country Convergence?," Journal of Economic Literature, American Economic Association, vol. 58(1), pages 129-175, March.
    8. Inmaculada C. Alvarez & Javier Barbero & Luis Orea & Andrés Rodríguez-Pose, 2023. "How institutions shape the economic returns of public investment in European regions," JRC Working Papers on Territorial Modelling and Analysis 2023-08, Joint Research Centre.
    9. Michal Bernardelli & Mariusz Prochniak & Bartosz Witkowski, 2017. "The application of hidden Markov models to the analysis of real convergence," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 17, pages 59-80.
    10. Michele Battisti & Tamara Fioroni & Andrea Mario Lavezzi, 2014. "World Interest Rates, Inequality and Growth: an Empirical Analysis of the Galor-Zeira Model," Discussion Papers 2014/184, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.
    11. 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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