Covariate Measurement Error in Endogenous Stratified Samples
AbstractIn this paper we propose a general framework to deal with the presence of covariate mea-surement error in endogenous stratifield samples. Using Chesher?s (2000) methodology, we develop approximately consistent estimators for the parameters of the structural model, in the sense that their inconsistency is of smaller order than that of the conventional estimators which ignore the existence of covariate measurement error. The approximate bias corrected estimators are obtained by applying the generalized method of moments (GMM) to a modifeld version of the moment indicators suggested by Imbens and Lancaster (1996) for endogenous stratified samples. Only the specification of the conditional distribution of the response vari-able given the latent covariates and the classical additive measurement error model assumption are required, the availability of information on both the marginal probability of the strata in the population and the variance of the measurement error not being essential. A score test to detect the presence of covariate measurement error arises as a by-product of this approach. Monte Carlo evidence is presented which suggests that, in endogenous stratified samples of moderate sizes, the modified GMM estimators perform well.
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 InfoPaper provided by University of Évora, Department of Economics (Portugal) in its series Economics Working Papers with number 2_2004.
Length: 38 pages
Date of creation: 2004
Date of revision:
endogenous stratified samples; covariate measurement error; generalized method of moments estimation; score tests;
Find related papers by JEL classification:
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
This paper has been announced in the following NEP Reports:
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Esmerelda A. Ramalho & Richard Smith, 2003.
"Discrete choice non-response,"
CeMMAP working papers
CWP07/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Maria Aurora Murcho Galego).
If references are entirely missing, you can add them using this form.