A Note on Implementing Box-Cox Quantile Regression
نویسندگان
چکیده
The Box-Cox quantile regression model using the two stage method suggested by Chamberlain (1994) and Buchinsky (1995) provides a flexible and numerically attractive extension of linear quantile regression techniques. However, the objective function in stage two of the method may not exists. We suggest a simple modification of the estimator which is easy to implement. The modified estimator is still √ n–consistent and we derive its asymptotic distribution. A simulation study confirms that the modified estimator works well in situations, where the original estimator is not well defined.
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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...
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