Bias-corrected Moment-based Estimators for Parametric Models under Endogenous Stratified Sampling
AbstractThis paper provides an integrated approach for estimating parametric models from endogenous stratified samples. We discuss several alternative ways of removing the bias of the moment indicators usually employed under random sampling for estimating the parameters of the structural model and the proportion of the strata in the population. Those alternatives give rise to a bunch of moment-based estimators which are appropriate for both cases where the marginal strata probabilities are known and unknown. The derivation of our estimators is very simple and intuitive and incorporates as particular cases most of the likelihood-based estimators existing in the literature.
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Bibliographic InfoPaper provided by University of Évora, Department of Economics (Portugal) in its series Economics Working Papers with number 11_2005.
Length: 29 pages
Date of creation: 2005
Date of revision:
Endogenous Stratified Sampling; Bias correction; GMM; Parametric models;
Other versions of this item:
- Esmeralda Ramalho & Joaquim Ramalho, 2006. "Bias-Corrected Moment-Based Estimators for Parametric Models Under Endogenous Stratified Sampling," Econometric Reviews, Taylor and Francis Journals, vol. 25(4), pages 475-496.
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
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- Prokhorov, Artem & Schmidt, Peter, 2009.
"GMM redundancy results for general missing data problems,"
Journal of Econometrics,
Elsevier, vol. 151(1), pages 47-55, July.
- Artem Prokhorov & Peter Schmidt, 2008. "GMM Redundancy Results for General Missing Data Problems," Working Papers 08003, Concordia University, Department of Economics.
- Esmeralda Ramalho, 2009.
"Covariate Measurement Error:Bias Reduction under Response-based Sampling,"
CEFAGE-UE Working Papers
2009_15, University of Evora, CEFAGE-UE (Portugal).
- Ramalho Esmeralda A., 2010. "Covariate Measurement Error: Bias Reduction under Response-Based Sampling," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-34, September.
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