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Modelling firm-size distribution using Box-Cox heteroscedastic regression

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  • Y. K. Tse

    (School of Economics and Social Sciences, Singapore Management University, 90 Stamford Road, Singapore 178903)

  • Z. L. Yang

    (School of Economics and Social Sciences, Singapore Management University, 90 Stamford Road, Singapore 178903)

Abstract

Using the Box-Cox regression model with heteroscedasticity (BCHR), we re-examine the size distribution of the Portuguese manufacturing firms studied by Machado and Mata (2000) using the Box-Cox quantile regression (BCQR) method. We show that the BCHR model compares favourably against the BCQR method. In particular, the BCHR model can answer the key questions addressed by the BCQR method, with the advantage that the estimated quantile functions are monotonic. Furthermore, estimation of the BCHR model is straightforward and the confidence intervals of the BCHR regression quantiles are easy to compute. Copyright © 2006 John Wiley & Sons, Ltd.

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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.

Volume (Year): 21 (2006)
Issue (Month): 5 ()
Pages: 641-653

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Handle: RePEc:jae:japmet:v:21:y:2006:i:5:p:641-653

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  1. Moshe Buchinsky, 1998. "Recent Advances in Quantile Regression Models: A Practical Guideline for Empirical Research," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 88-126.
  2. Jose A. F. Machado & Jose Mata, 2000. "Box-Cox quantile regression and the distribution of firm sizes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(3), pages 253-274.
  3. Buchinsky, Moshe, 1995. "Quantile regression, Box-Cox transformation model, and the U.S. wage structure, 1963-1987," Journal of Econometrics, Elsevier, vol. 65(1), pages 109-154, January.
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