EconPapers    
Economics at your fingertips  
 

Semiparametic Nonlinear Least-Squares Estimation of Truncated Regression Models

Lung-Fei Lee

Econometric Theory, 1992, vol. 8, issue 1, 52-94

Abstract: This article provides a semiparametric method for the estimation of truncated regression models where the disturbances are independent of the regressors before truncation. This independence property provides useful information on model identification and estimation. Our estimate is shown to be -consistent and asymptotically normal. A consistent estimate of the asymptotic covariance matrix of the estimator is provided. Monte Carlo experiments are performed to investigate some finite sample properties of the estimator.

Date: 1992
References: Add references at CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
https://www.cambridge.org/core/product/identifier/ ... type/journal_article link to article abstract page (text/html)

Related works:
Working Paper: Semiparametric Nonlinear Least Square Estimation of Truncated Regression Models (1990)
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:cup:etheor:v:8:y:1992:i:01:p:52-94_01

Access Statistics for this article

More articles in Econometric Theory from Cambridge University Press Cambridge University Press, UPH, Shaftesbury Road, Cambridge CB2 8BS UK.
Bibliographic data for series maintained by Kirk Stebbing ().

 
Page updated 2025-03-19
Handle: RePEc:cup:etheor:v:8:y:1992:i:01:p:52-94_01