Modelling firm-size distribution using Box-Cox heteroscedastic regression
AbstractUsing 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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Bibliographic InfoArticle provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.
Volume (Year): 21 (2006)
Issue (Month): 5 ()
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Web page: http://www.interscience.wiley.com/jpages/0883-7252/
Other versions of this item:
- Zhenlin Yang & Yiu Kuen Tse, 2004. "Modeling Firm-Size Distribution Using Box-Cox Heteroscedastic Regression," Working Papers 10-2004, Singapore Management University, School of Economics.
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
- C5 - Mathematical and Quantitative Methods - - Econometric Modeling
- L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
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- 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.
- 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.
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