Second Order Bias of Quasi-MLE for Covariance Structure Models
Several recent papers (e.g., Newey et al., 2005; Newey and Smith, 2004; Anatolyev, 2005) derive general expressions for the second-order bias of the GMM estimator and its first-order equivalents such as the EL estimator. Except for some simulation evidence, it is unknown how these compare to the second-order bias of QMLE of covariance structure models. The paper derives the QMLE bias formulas for this general class of models. The bias -- identical to the EL second-order bias under normality -- depends on the fourth moments of data and remains the same as for EL even for non-normal data so long as the condition for equal asymptotic efficiency of QMLE and GMM derived in Prokhorov (2009) is satisfied.
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- 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 K. 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.
- Altonji, Joseph G & Segal, Lewis M, 1996. "Small-Sample Bias in GMM Estimation of Covariance Structures," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 353-366, July.
- Joseph G. Altonji & Lewis M. Segal, 1994. "Small sample bias in GMM estimation of covariance structures," Working Paper Series, Macroeconomic Issues 94-8, Federal Reserve Bank of Chicago.
- Joseph G. Altonji & Lewis M. Segal, 1994. "Small Sample Bias in GMM Estimation of Covariance Structures," NBER Technical Working Papers 0156, National Bureau of Economic Research, Inc.
- Prokhorov, Artem, 2009. "On relative efficiency of quasi-MLE and GMM estimators of covariance structure models," Economics Letters, Elsevier, vol. 102(1), pages 4-6, January.
- Artem Prokhorov, 2008. "On relative efficiency of Quasi-MLE and GMM estimators of covariance structure models," Working Papers 08004, Concordia University, Department of Economics.
- Chamberlain, Gary, 1984. "Panel data," Handbook of Econometrics,in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 22, pages 1247-1318 Elsevier.
- Clark, Todd E, 1996. "Small-Sample Properties of Estimators of Nonlinear Models of Covariance Structure," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 367-373, July.
- Todd E. Clark, 1995. "Small sample properties of estimators of non-linear models of covariance structure," Research Working Paper 95-01, Federal Reserve Bank of Kansas City.
- Joel L. Horowitz, 1998. "Bootstrap Methods for Covariance Structures," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 39-61.
- Rilstone, Paul & Srivastava, V. K. & Ullah, Aman, 1996. "The second-order bias and mean squared error of nonlinear estimators," Journal of Econometrics, Elsevier, vol. 75(2), pages 369-395, December.
- Haruhiko Ogasawara, 2004. "Asymptotic biases in exploratory factor analysis and structural equation modeling," Psychometrika, Springer;The Psychometric Society, vol. 69(2), pages 235-256, June.
- Satorra, Albert & Neudecker, Heinz, 1994. "On the Asymptotic Optimality of Alternative Minimum-Distance Estimators in Linear Latent-Variable Models," Econometric Theory, Cambridge University Press, vol. 10(05), pages 867-883, December.
- Albert Satorra, 1993. "On the asymptotic optimality of alternative minimum-distance estimators in linear latent-variable models," Economics Working Papers 35, Department of Economics and Business, Universitat Pompeu Fabra.
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