Specification Testing in Models with Many Instruments
This paper studies the asymptotic validity of the Anderson-Rubin (AR) test and the J test of overidentifying restrictions in linear models with many instruments. When the number of instruments increases at the same rate as the sample size, we establish that the conventional AR and J tests are asymptotically incorrect. Some versions of these tests, that are developed for situations with moderately many instruments, are also shown to be asymptotically invalid in this framework. We propose modifications of the AR and J tests that deliver asymptotically correct sizes. Importantly, the corrected tests are robust to the numerosity of the moment conditions in the sense that they are valid for both few and many instruments. The simulation results illustrate the excellent properties of the proposed tests.
|Date of creation:||Sep 2008|
|Date of revision:|
|Contact details of provider:|| Postal: 117418 Russia, Moscow, Nakhimovsky pr., 47, office 720|
Phone: +7 (495) 105 50 02
Fax: +7 (495) 105 50 03
Web page: http://www.cefir.ru
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Ledoit, Olivier & Wolf, Michael, 2000.
"A well conditioned estimator for large dimensional covariance matrices,"
DES - Working Papers. Statistics and Econometrics. WS
10087, Universidad Carlos III de Madrid. Departamento de Estadística.
- Ledoit, Olivier & Wolf, Michael, 2004. "A well-conditioned estimator for large-dimensional covariance matrices," Journal of Multivariate Analysis, Elsevier, vol. 88(2), pages 365-411, February.
- Donald, Stephen G. & Imbens, Guido W. & Newey, Whitney K., 2003. "Empirical likelihood estimation and consistent tests with conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 117(1), pages 55-93, November.
- Joshua D. Angrist & Alan B. Keueger, 1991.
"Does Compulsory School Attendance Affect Schooling and Earnings?,"
The Quarterly Journal of Economics,
Oxford University Press, vol. 106(4), pages 979-1014.
- Joshua D. Angrist & Alan B. Krueger, 1990. "Does Compulsory School Attendance Affect Schooling and Earnings?," NBER Working Papers 3572, National Bureau of Economic Research, Inc.
- Harry H. Kelejian & Ingmar R. Prucha, 1999.
"On the Asymptotic Distribution of the Moran I Test Statistic with Applications,"
Electronic Working Papers
99-002, University of Maryland, Department of Economics.
- H. Kelejian, Harry & Prucha, Ingmar R., 2001. "On the asymptotic distribution of the Moran I test statistic with applications," Journal of Econometrics, Elsevier, vol. 104(2), pages 219-257, September.
- John C. Chao & Norman Rasmus Swanson, 2004.
"Consistent Estimation with a Large Number of Weak Instruments,"
Yale School of Management Working Papers
ysm374, Yale School of Management.
- John C. Chao & Norman R. Swanson, 2005. "Consistent Estimation with a Large Number of Weak Instruments," Econometrica, Econometric Society, vol. 73(5), pages 1673-1692, 09.
- Chao, John Chao & Norman R. Swanson, 2003. "Consistent Estimation with a Large Number of Weak Instruments," Cowles Foundation Discussion Papers 1417, Cowles Foundation for Research in Economics, Yale University.
- John Chao & Norman Swanson, 2004. "Consistent Estimation with a Large Number of Weak Instruments," Departmental Working Papers 200421, Rutgers University, Department of Economics.
- Andersen, Torben G & Sorensen, Bent E, 1996.
"GMM Estimation of a Stochastic Volatility Model: A Monte Carlo Study,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 14(3), pages 328-52, July.
- Torben G. Andersen & Hyung-Jin Chung & Bent E. Sorensen, . "EMM Estimation of a Stochastic Volatility Model: A Monte Carlo Study," Computing in Economics and Finance 1997 6, Society for Computational Economics.
- Torben G. Andersen & Bent E. Sorensen, 1995. "GMM Estimation of a Stochastic Volatility Model: A Monte Carlo Study," Discussion Papers 95-19, University of Copenhagen. Department of Economics.
- Burnside, Craig & Eichenbaum, Martin S, 1996. "Small-Sample Properties of GMM-Based Wald Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 294-308, July.
- Koenker, Roger & Machado, Jose A. F., 1999. "GMM inference when the number of moment conditions is large," Journal of Econometrics, Elsevier, vol. 93(2), pages 327-344, December.
- Bekker, Paul A, 1994. "Alternative Approximations to the Distributions of Instrumental Variable Estimators," Econometrica, Econometric Society, vol. 62(3), pages 657-81, May.
- Andrews, Donald W.K. & Stock, James H., 2007. "Testing with many weak instruments," Journal of Econometrics, Elsevier, vol. 138(1), pages 24-46, May.
When requesting a correction, please mention this item's handle: RePEc:cfr:cefirw:w0124. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Julia Babich)
If references are entirely missing, you can add them using this form.