Implementing Box-Cox Quantile Regression
The Box-Cox quantile regression model introduced by Powell (1991) is a flexible and numerically attractive extension of linear quantile regression techniques. Chamberlain (1994) and Buchinsky (1995) suggest a two stage estimator for this model but the objective function in stage two of their method may not be defined in an application. We suggest a modification of the estimator which is easy to implement. A simulation study demonstrates that the modified estimator works well in situations, where the original estimator is not well defined.
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Volume (Year): 29 (2010)
Issue (Month): 2 (April)
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"Censored Quantile Regressions and the Length of Unemployment Periods in West Germany,"
ZEW Discussion Papers
04-57, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
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