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 number of moment-based estimators that 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 previously suggested by other authors.
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Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Econometric Reviews.
Volume (Year): 25 (2006)
Issue (Month): 4 ()
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Other versions of this item:
- Joaquim J.S. Ramalho & Esmeralda Ramalho, 2005. "Bias-corrected Moment-based Estimators for Parametric Models under Endogenous Stratified Sampling," Economics Working Papers 11_2005, University of Évora, Department of Economics (Portugal).
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
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- 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.
- Esmeralda Ramalho, 2009. "Covariate Measurement Error:Bias Reduction under Response-based Sampling," CEFAGE-UE Working Papers 2009_15, University of Evora, CEFAGE-UE (Portugal).
- 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.
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