Select the valid and relevant moments: An information-based LASSO for GMM with many moments

Journal of Econometrics

Volumn 186, Issue 2, 2015, Pages 443-464

  Cheng, Xu ^a   Liao, Zhipeng ^b  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Adaptive penalty; GMM; Many moments; Moment selection; Oracle properties; Shrinkage estimation

Indexed keywords

ASYMPTOTIC ANALYSIS; METHOD OF MOMENTS;

ADAPTIVE PENALTY; GMM; MANY MOMENTS; ORACLE PROPERTIES; SHRINKAGE ESTIMATIONS;

SHRINKAGE;

EID: 84929175974     PISSN: 03044076     EISSN: 18726895     Source Type: Journal    
DOI: 10.1016/j.jeconom.2015.02.019     Document Type: Conference Paper

References (53)

1. D.W.K. Andrews Empirical process methods in econometrics R.F. Engle, D. McFadden, Handbook of Econometrics vol. IV 1994 North-Holland Amsterdam
2. D.W.K. Andrews Consistent moment selection procedures for generalized method of moments estimation Econometrica 67 3 1999 543 563
3. D.W.K. Andrews Generalized method of moments estimation when a parameter is on a boundary J. Bus. Econom. Statist. 20 4 2002 530 544
4. D.W.K. Andrews, and P. Guggenberger Hybrid and size-corrected subsampling methods Econometrica 77 3 2009 721 762
5. D.W.K. Andrews, and P. Guggenberger Asymptotic size and a problem with subsampling with the m out of n bootstrap Econometric Theory 26 2010 426 468
6. D.W.K. Andrews, and B. Lu Consistent model and moment selection procedures for GMM estimation with application to dynamic panel data models J. Econometrics 101 1 2001 123 164
7. J. Bai, and S. Ng Selecting instrumental variables in a data rich environment J. Time Ser. Econom. 1 1 2009
8. R. Bhatia Matrix Analysis 1997 Springer New York
9. A. Belloni, D. Chen, V. Chernozhukov, and C. Hansen Sparse models and methods for optimal instruments with an application to eminent domain Econometrica 80 2012 2369 2429
10. Belloni, A., Chernozhukov, V., Hansen, C., 2010. LASSO Methods for Gaussian Instrumental Variables Models. Preprint, arXiv:1012.1297.
11. Belloni, A., Chernozhukov, V., Hansen, C., 2011. Inference on Treatment Effects After Selection amongst High-dimensional Controls. Preprint, arXiv:1201.0224.
12. D. Berkowitz, M. Caner, and Y. Fang The validity of instruments revisited J. Econometrics 166 2 2012 255 266
13. T. Breusch, H. Qian, P. Schmidt, and D. Wyhowski Redundancy of moment conditions J. Econometrics 91 1999 89 111
14. Caner, M., Han, X., Lee, Y., 2013. Bias-Corrected Semiparametrically Efficient High Dimensional GMM Estimator with Many Invalid Moment Conditions: An Application to Dynamic Panel Data Models, MIMEO.
15. Caner, M., Zhang, H., 2012. Adaptive Elastic Net for Generalized Methods of Moments. Unpublished Manuscript.
16. M. Carrasco A regularization approach to the many instruments problem J. Econometrics 170 2 2012 383 398
17. G. Chamberlain, and G.W. Imbens Random effects estimators with many instrumental variables Econometrica 72 2004 295 306
18. X. Chen, O. Linton, and I. van Keilegom Estimation of semiparametric models when the criterion function is not smooth Econometrica 71 5 2003 1591 1608
19. T.G. Conley, C.B. Hansen, and P.E. Rossi Plausibly exogenous Rev. Econ. Statist. 94 1 2012 260 272
20. DiTraglia, F., 2012. Using Invalid Instruments on Purpose: Focused Moment Selection and Averaging for GMM, University of Pennsylvania, Working Paper.
21. Doko Tchatoka, F., Dufour, J.-M., 2012. Identification-robust Inference for Endogeneity Parameters in Linear Structural Models, MPRA Paper 40695, University Library of Munich, Germany.
22. S.G. Donald, G.W. Imbens, and W.K. Newey Choosing instrumental variables in conditional moment restriction models J. Econometrics 152 1 2009 28 36
23. S.G. Donald, and W.K. Newey Choosing the number of instruments Econometrica 69 5 2001 1161 1191
24. M.S. Eichenbaum, L.P. Hansen, and K.J. Singleton A time series analysis of representative agent models of consumption and leisure choice under uncertainty Quart. J. Econ. 103 1 1988 51 78
25. Fan, J., Liao, Y., 2011. Ultra High dimensional Variable Selection with Endogenous Covariates, Princeton University and University of Maryland, Working Paper.
26. Gautier, E., Tsybakov, A.B., 2011. High-dimensional Instrumental Variables Regression and Confidence Sets. Preprint, arXiv:1105.2454v2.
27. P. Guggenberger The impact of a hausman pretest on the asymptotic size of a hypothesis test Econometric Theory 26 2010 369 382
28. P. Guggenberger On the asymptotic size distortion of tests when instruments locally violate the exogeneity assumption Econometric Theory 28 2 2012 387 421
29. A.R. Hall, A. Inoue, K. Jana, and C. Shin Information in generalized method of moments estimation and entropy based moment selection J. Econometrics 138 2 2007 488 512
30. A.R. Hall, A. Inoue, J.M. Nason, and B. Rossi Information criteria for impulse response function matching estimation of DSGE models J. Econometrics 170 2 2012 499 518
31. A.R. Hall, and F.P.M. Peixe A consistent method for the selection of relevant instruments Econometric Rev. 22 3 2003 269 288
32. L.P. Hansen Large sample properties of generalized method of moments estimators Econometrica 50 4 1982 1029 1054
33. H. Hong, B. Preston, and M. Shum Generalized empirical likelihood-based model selection criteria for moment condition models Econometric Theory 19 6 2003 923 943
34. K.S. Im, S.C. Ahn, P. Schmidt, and J.M. Wooldridge Efficient estimation of panel data models with strictly exogenous explanatory variables J. Econometrics 93 1 1999 177 201
35. A. Inoue A bootstrap approach to moment selection Econom. J. 9 1 2006 48 75
36. Kuersteiner, G.M., 2002. Mean Square Error Reduction for GMM Estimators of Linear Time Series Models. UC Davis, Working Paper.
37. G.M. Kuersteiner, and R. Okui Constructing optimal instruments by first-stage prediction averaging Econometrica 78 2 2010 697 718
38. Lee, Y., Zhou, Y., 2011. Averaged Instrumental Variable Estimator. University of Michigan, Working Paper.
39. H. Leeb, and B.M. Pötscher Model selection and inference: Facts and fiction Econometric Theory 21 1 2005 21 59
40. H. Leeb, and B.M. Pötscher Sparse estimators and the oracle property, or the return of the hodges estimator J. Econometrics 142 1 2008 201 211
41. Z. Liao Adaptive GMM shrinkage estimation with consistent moment selection Econometric Theory 29 2013 1 48
42. McCloskey, A., 2012. Bonferroni-based Size-correction for Nonstandard Testing Problems. Brown University, Working Paper.
43. W.K. Newey Convergence rates and asymptotic normality for series estimators J. Econometrics 79 1997 147 168
44. A. Nevo, and A. Rosen Identification with imperfect instruments Rev. Econ. Stat. 93 3 2012 659 671
45. R. Okui Instrumental variable estimation in the presence of many moment conditions J. Econometrics 165 1 2011 70 86
46. A. Pakes, and D. Pollard Simulation and the asymptotics of optimization estimators Econometrica 57 1989 1027 1057
47. D. Pollard Convergence of Stochastic Processes 1984 Springer-Verlag New York
48. D. Pollard Asymptotics via empirical processes Statist. Sci. 4 4 1989 341 354
49. J. Sargan The estimation of economic relationships using instrumental variables Econometrica 26 3 1958 393 415
50. M. Schmidt Graphical Model Structure Learning with L1-regularization (Thesis) 2010 University of British Columbia
51. X. Shen On methods of sieves and penalization Ann. Statist. 25 1997 2555 2591
52. A.W. van der Vaart, and J.A. Wellner Weak Convergence and Empirical Processes 1996 Springer New York
53. H. Zou The adaptive lasso and its oracle properties J. Amer. Statist. Assoc. 101 476 2006 1418 1429