A bootstrap approach to moment selection

Econometrics Journal

Volumn 9, Issue 1, 2006, Pages 48-75

  Inoue, Atsushi ^a  

^a NORTH CAROLINA STATE UNIVERSITY   (United States)

Author keywords

Edgeworth expansions; Instrumental variables

Indexed keywords

EID: 33845411675     PISSN: 13684221     EISSN: 1368423X     Source Type: Journal    
DOI: 10.1111/j.1368-423X.2006.00176.x     Document Type: Article

References (25)

1. Anderson, T. and B. Sorensen (1996). GMM estimation of a stochastic volatility model: A Monte Carlo study. Journal of Business and Economic Statistics 14, 328-52.
2. Anderson, T. W. (1974). An asymptotic expansion of the distribution of the limited information maximum likelihood estimate of a coefficient in a simultaneous equation system. Journal of the American Statistical Association 69, 565-73.
3. Andrews, D. W. K. (1999). Consistent moment selection procedures for generalized method of moments estimation. Econometrica 67, 543-64.
4. Andrews, D. W. K. (2002). Higher-order improvements of a computationally attractive k-step bootstrap for extremum estimators. Econometrica 70, 119-62.
5. Andrews, D. W. K. and B. Lu (2001). Consistent model and moment selection criteria for gmm estimation with applications to dynamic panel models. Journal of Econometrics 101, 123-64.
6. Bekker, P. A. (1994). Alternative approximations to the distributions of instrumental variable estimators. Econometrica 62, 657-81.
7. Buse, A. (1992). The bias of instrumental variable estimators. Econometrica 60, 173-80.
8. Carlstein, E. (1986). The use of subseries methods for estimating the variance of a general statistic from a stationary time series. Annals of Statistics 14, 1171-79.
9. Donald, S. G. and W.K. Newey (2001). Choosing the number of instruments. Econometrica 69, 1161-92.
10. Donald, S. G., G. Imbens and W.K. Newey (2005). Choosing the number of moments in conditional moment restrictions models, manuscript, University of Texas, University of California, and MIT.
11. Götze, F., and H.R. Künsch (1996). Second-order correctness of the blockwise bootstrap for stationary observations. Annals of Statistics 24, 1914-33.
12. Hall, A. R., A. Inoue, K. Jana and C. Shin (2005). Information in generalized method of moments estimation and entropy based moment selection. forthcoming, Journal of Econometrics.
13. Hall, A. R. and F.P.M. Peixe (2003). A consistent method for the selection of relevant instruments in linear models. Econometric Reviews 22, 269-87.
14. Hall, P. (1992). The Bootstrap and Edgeworth Expansion. Springer-Verlag: New York.
15. Hall, P. and J.L. Horowitz (1996). Bootstrap critical values for tests based on generalized method of moments estimators. Econometrica 64, 891-916.
16. Inoue, A. and M. Shintani (2005). Bootstrapping GMM estimators for time series. Journal of Econometrics forthcoming.
17. Kuersteiner, G. M. (2002). Rate-adaptive GMM estimators for linear time series models. manuscript, MIT.
18. Künsch, H. R. (1989). The jackknife and the bootstrap for general stationary observations. Annals of Statistics 17, 1217-41.
19. Morimune, K. (1983). Approximate distributions of k-class estimators when the degree of overidentifiability is large compared with the sample size. Econometrica 51, 821-41.
20. Newey, W. K. (1990). Effecient instrumental variables estimation of nonlinear models. Econometrica 58, 809-37.
21. Newey, W. K. and F. Windmeijer (2005). Many weak moment asymptotics for generalized empirical likelihood estimators, mimeograph, M.I.T. and Institute for Fiscal Studies.
22. Rothenberg, T. J. (1984). Approximating the distributions of econometric estimators and test statistics, Handbook of Econometrics, Vol. 2, Elsevier: Amsterdam, pp. 881-935.
23. Tauchen, G. (1986). Statistical properties of generalized method-of-moments estimators of structural parameters obtained from financial market data. Journal of Business and Economic Statistics 4, 397-416.
24. Stock, J. H., J.H. Wright and M. Yogo (2002). A survey of weak instruments and weak identification in generalized method of moments. Journal of Business and Economic Statistics 20, 518-29.
25. West, K. D. (2001). On optimal instrumental variables estimation of stationary time series models. International Economic Review 42, 1043-50.