Estimation of a Tobit model with unknown censoring threshold
AbstractConventional wisdom suggests that only the estimated intercept is affected by imposition of a zero censoring threshold on a Tobit model. This is true for Heckman-Lee estimation. For maximum likelihood (ML) estimation, however, it is only true if the censoring threshold is known and is subtracted from the dependent variable. Failure to properly transform the dependent variable prior to ML estimation of a zero threshold Tobit model will generally bias the coefficient estimates. A long neglected topic is ML estimation of a Tobit model with common, but unknown, censoring threshold. This paper shows that the ML estimator of the censoring threshold is the minimum order statistic from the observed subsample, and that existing software for estimation of a zero-threshold Tobit model is easily adapted to include estimation of the censoring threshold.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Applied Economics.
Volume (Year): 35 (2003)
Issue (Month): 10 ()
Contact details of provider:
Web page: http://www.tandfonline.com/RAEC20
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Yasuhiro Omori & Koji Miyawaki, 2008.
"Tobit Model with Covariate Dependent Thresholds,"
CIRJE-F-594, CIRJE, Faculty of Economics, University of Tokyo.
- Harman, Yvette S. & Zuehlke, Thomas W., 2007. "Nonlinear duration dependence in stock market cycles," Review of Financial Economics, Elsevier, vol. 16(4), pages 350-362.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty).
If references are entirely missing, you can add them using this form.