The Box-Cox regression transformation has been widely used in applied economics. However, there has been very limited discussion of this transformation when data are truncated. This paper considers an alternative family of power transformation, called the Dual Power Transformation, to overcome the truncation problem of the Box-Cox power transformation. It generates a rich family of distributions that is seen to be very useful in modeling and analysis of economic applications. Empirical results presented are more favorable to the alternative transformation than to the Box-Cox power transformation in terms of model fit.
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