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A note on the use of quantile regression in beta convergence analysis

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  • Marcio Laurini

    (Ibmec Sao Paulo and IMECC-Unicamp)

Abstract

We discuss how to interpret conflicting results obtained by the use of quantile regression methods in growth regression tests of β-convergence hypothesis and the results obtained by nonparametric methods. We show that the assumption of linearity may cause the non-rejection of the β-convergence hypothesis by quantile regression. We also show that using a nonparametric form of quantile regression, we can reject the hypothesis of β-convergence and confirm the results of divergence and formation of convergence clubs. We illustrate the discussion by using the conflicting results on convergence found in the dataset of per-capita income of Brazilian municipalities between 1970 and 1996.

Suggested Citation

  • Marcio Laurini, 2007. "A note on the use of quantile regression in beta convergence analysis," Economics Bulletin, AccessEcon, vol. 3(52), pages 1-8.
    • Handle: RePEc:ebl:ecbull:eb-07c50003
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    References listed on IDEAS

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    2. Túlio Cravo & Guilherme Resende, 2013. "Economic growth in Brazil: a spatial filtering approach," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 50(2), pages 555-575, April.
    3. Takahashi, Kazushi, 2013. "Pro-poor growth or poverty trap? : estimating intergenerational income mobility in rural Philippines," IDE Discussion Papers 382, Institute of Developing Economies, Japan External Trade Organization(JETRO).
    4. João Sousa Andrade & Adelaide Duarte & Marta Simões, 2014. "A Quantile Regression Analysis of Growth and Convergence in the EU: Potential Implications for Portugal," Notas Económicas, Faculty of Economics, University of Coimbra, issue 39, pages 48-72, June.
    5. Bernardi, Mauro & Bottone, Marco & Petrella, Lea, 2018. "Bayesian quantile regression using the skew exponential power distribution," Computational Statistics & Data Analysis, Elsevier, vol. 126(C), pages 92-111.
    6. Julio Cesar Araujo da Silva Junior, 2017. "An S-Shaped Crude Oil Price Return-Implied Volatility Relation: Parametric and Nonparametric Estimations," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 9(12), pages 54-70, December.

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