Semiparametric Nonlinear Least Square Estimation of Truncated Regression Models
1990-02
Loading...
View/Download File
Persistent link to this item
Statistics
View StatisticsJournal Title
Journal ISSN
Volume Title
Title
Semiparametric Nonlinear Least Square Estimation of Truncated Regression Models
Authors
Published Date
1990-02
Publisher
Center for Economic Research, Department of Economics, University of Minnesota
Type
Working Paper
Abstract
This article provides a semi parametric method for the estimation of truncated regression
models where the disturbances are independent with the regressors before truncation. This independency
property provides useful information on the identification and estimation of the model.
Our estimate is shown to be Vn-consistent and asymptotically normal. 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.
Description
Related to
Replaces
License
Series/Report Number
Funding information
Isbn identifier
Doi identifier
Previously Published Citation
Lee, L., (1990), "Semiparametric Nonlinear Least Square Estimation of Truncated Regression Models", Discussion Paper No. 254, Center for Economic Research, Department of Economics, University of Minnesota.
Other identifiers
Suggested citation
Lee, Lung-Fei. (1990). Semiparametric Nonlinear Least Square Estimation of Truncated Regression Models. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/55533.
Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.