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Parametric variability in cross-country growth regressions: An application of quantile-regression methodology

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  • Ram, Rati

Abstract

Quantile-regression estimates of Solow-type growth models indicate [beta]-convergence rate in the bottom quartile to be much smaller than that for the top quartile. Some other coefficients also show sizable differences. The methodology appears useful for studying the important aspect of parametric differences across high-growth and low-growth countries.

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  • Ram, Rati, 2008. "Parametric variability in cross-country growth regressions: An application of quantile-regression methodology," Economics Letters, Elsevier, vol. 99(2), pages 387-389, May.
    • Handle: RePEc:eee:ecolet:v:99:y:2008:i:2:p:387-389
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    Cited by:

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    4. Lijuan Huo & Tae-Hwan Kim & Yunmi Kim, 2015. "Revisiting growth empirics based on IV panel quantile regression," Applied Economics, Taylor & Francis Journals, vol. 47(36), pages 3859-3873, August.
    5. Deng, Wen-Shuenn & Lin, Yi-Chen & Gong, Jinguo, 2012. "A smooth coefficient quantile regression approach to the social capital–economic growth nexus," Economic Modelling, Elsevier, vol. 29(2), pages 185-197.
    6. Philip Kostov & Julie Le Gallo, 2018. "What role for human capital in the growth process: new evidence from endogenous latent factor panel quantile regressions," Scottish Journal of Political Economy, Scottish Economic Society, vol. 65(5), pages 501-527, November.
    7. Mohammadi, Hassan & Ram, Rati, 2012. "Cross-country convergence in energy and electricity consumption, 1971–2007," Energy Economics, Elsevier, vol. 34(6), pages 1882-1887.
    8. Gadea Rivas, Maria Dolores & Sanz Villarroya, Isabel, 2017. "Testing the convergence hypothesis for OECD countries: A reappraisal," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 11, pages 1-22.

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