Semiparametric estimation of a truncated regression model
Songnian Chen and
Xianbo Zhou
Journal of Econometrics, 2012, vol. 167, issue 2, 297-304
Abstract:
This paper proposes a new semiparametric estimator for the truncated regression model under the independence restriction. Many existing approaches such as those in Lee (1992) and Honoré and Powell (1994) are moment-based methods, whereas our approach makes use of the entire truncated distribution. As a result, our approach is expected to require weaker identification and to have more favorable performance. Our simulation results suggest that our estimator outperforms that of Lee (1992) and Honoré and Powell (1994) in a variety of designs. Our estimator is shown to be consistent and asymptotically normal.
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304407611001977
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:167:y:2012:i:2:p:297-304
DOI: 10.1016/j.jeconom.2011.09.016
Access Statistics for this article
Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson
More articles in Journal of Econometrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().