Bootstrap bias-adjusted GMM estimators
The ability of six alternative bootstrap methods to reduce the bias of GMM parameter estimates is examined in an instrumental variable framework using Monte Carlo analysis. Promising results were found for the two bootstrap estimators suggested in the paper.
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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.
- Brown, Bryan W & Newey, Whitney K, 2002. "Generalized Method of Moments, Efficient Bootstrapping, and Improved Inference," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 507-517, October.
- Hall, Peter & Horowitz, Joel L, 1996. "Bootstrap Critical Values for Tests Based on Generalized-Method-of-Moments Estimators," Econometrica, Econometric Society, vol. 64(4), pages 891-916, July.
- Ramalho Joaquim J.S., 2005. "Small Sample Bias of Alternative Estimation Methods for Moment Condition Models: Monte Carlo Evidence for Covariance Structures," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(1), pages 1-20, March.
- Joel L. Horowitz, 1998. "Bootstrap Methods for Covariance Structures," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 39-61. Full references (including those not matched with items on IDEAS)