A Semiparametric Derivative Estimator in Log Transformation Models
This paper considers a regression model with a log-transformed dependent variable. The log transformed model is estimated by simple least squares, but computing the conditional mean of the dependent variable on the original scale given the explanatory variables analytically requires knowing the conditional distribution of the error term in the transformed model. We show how to obtain a consistent estimator for the conditional mean and its derivatives without specifying the conditional distribution of the error term. The asymptotic distribution of the estimator is derived. The proposed procedure is then illustrated with health expenditure data from the Medical Expenditure Panel Survey.
|Date of creation:||Jul 2006|
|Contact details of provider:|| Postal: HEDG/HERC, Department of Economics and Related Studies, University of York, York, YO10 5DD, United Kingdom|
Phone: (0)1904 323776
Web page: https://www.york.ac.uk/economics/postgrad/herc/hedg/
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:yor:hectdg:06/06. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Jane Rawlings)
If references are entirely missing, you can add them using this form.