Effcient M-estimators with auxiliary information
This paper introduces a new class of M-estimators based on generalised empirical likelihood estimation with some auxiliary information available in the sample. The resulting class of estimators is efficient in the sense that it achieves the same asymptotic lower bound as that of the efficient generalised method of moment-based M-estimator with the same auxiliary information. The results of the paper are quite general and apply to M-estimators defined by both smooth and nonsmooth estimating equations. Simulations show that the proposed estimators perform well in finite samples, and can be less biased and more precise than standard M-estimators within China.
|Date of creation:||Aug 2008|
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- Guido W. Imbens & Richard H. Spady & Phillip Johnson, 1998.
"Information Theoretic Approaches to Inference in Moment Condition Models,"
Econometric Society, vol. 66(2), pages 333-358, March.
- Imbens, G.W. & Johnson, P. & Spady, R.H., 1995. "Information Theoretic Approaches to Inference in Movement Condition Models," Economics Papers 99, Economics Group, Nuffield College, University of Oxford.
- Guido W Imbens, Phillip Johnson & Richard H Spady, . "Information theoretic approaches to inference in moment condition model," Economics Papers W12., Economics Group, Nuffield College, University of Oxford.
- Guido W. Imbens & Phillip Johnson & Richard H. Spady, 1995. "Information Theoretic Approaches to Inference in Moment Condition Models," NBER Technical Working Papers 0186, National Bureau of Economic Research, Inc.
- Guido W. Imbens & Phillip Johnson & Richard H. Spady, 1995. "Information Theoretic Approaches to Inference in Moment Condition Models," Harvard Institute of Economic Research Working Papers 1736, Harvard - Institute of Economic Research.
- Whitney K. Newey & Richard J. Smith, 2004.
"Higher Order Properties of Gmm and Generalized Empirical Likelihood Estimators,"
Econometric Society, vol. 72(1), pages 219-255, 01.
- Whitney Newey & Richard Smith, 2003. "Higher order properties of GMM and generalised empirical likelihood estimators," CeMMAP working papers CWP04/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
- Guido W. Imbens & Judith K. Hellerstein, 1996.
"Imposing Moment Restrictions from Auxiliary Data by Weighting,"
NBER Technical Working Papers
0202, National Bureau of Economic Research, Inc.
- Judith K. Hellerstein & Guido W. Imbens, 1999. "Imposing Moment Restrictions From Auxiliary Data By Weighting," The Review of Economics and Statistics, MIT Press, vol. 81(1), pages 1-14, February.
- Parente, Paulo M.D.C. & Smith, Richard J., 2011.
"Gel Methods For Nonsmooth Moment Indicators,"
Cambridge University Press, vol. 27(01), pages 74-113, February.
- Donald W.K. Andrews, 1993.
"Empirical Process Methods in Econometrics,"
Cowles Foundation Discussion Papers
1059, Cowles Foundation for Research in Economics, Yale University.
- Bruce Brown & Song Chen, 1998. "Combined and Least Squares Empirical Likelihood," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 50(4), pages 697-714, December.
- Chamberlain, Gary, 1987. "Asymptotic efficiency in estimation with conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 34(3), pages 305-334, March.
- Smith, Richard J, 1997. "Alternative Semi-parametric Likelihood Approaches to Generalised Method of Moments Estimation," Economic Journal, Royal Economic Society, vol. 107(441), pages 503-19, March.
- Imbens, G.W. & Lancaster, T., 1991.
"Combining Micro and Macro Data in Microeconometric Models,"
Harvard Institute of Economic Research Working Papers
1578, Harvard - Institute of Economic Research.
- Guido W. Imbens & Tony Lancaster, 1994. "Combining Micro and Macro Data in Microeconometric Models," Review of Economic Studies, Oxford University Press, vol. 61(4), pages 655-680.
- P. Hall & B. Presnell, 1999. "Intentionally biased bootstrap methods," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(1), pages 143-158.
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