A note on the use of quantile regression in beta convergence analysis
AbstractWe discuss how to interpret conflicting results obtained by the use of quantile regression methods in growth regression tests of ÃÂ²-convergence hypothesis and the results obtained by nonparametric methods. We show that the assumption of linearity may cause the non-rejection of the ÃÂ²-convergence hypothesis by quantile regression. We also show that using a nonparametric form of quantile regression, we can reject the hypothesis of ÃÂ²-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.
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Bibliographic InfoPaper provided by Insper Working Paper, Insper Instituto de Ensino e Pesquisa in its series Insper Working Papers with number wpe_95.
Date of creation: Oct 2007
Date of revision:
Other versions of this item:
- Marcio Laurini, 2007. "A note on the use of quantile regression in beta convergence analysis," Economics Bulletin, AccessEcon, vol. 3(52), pages 1-8.
- C5 - Mathematical and Quantitative Methods - - Econometric Modeling
This paper has been announced in the following NEP Reports:
- NEP-ALL-2008-05-17 (All new papers)
- NEP-EDU-2008-05-17 (Education)
- NEP-HRM-2008-05-17 (Human Capital & Human Resource Management)
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