Testing in GMM Models without Truncation
AbstractThis paper proposes a new approach to testing in the generalized method of moments (GMM) framework. The new tests are constructed using heteroskedasticity autocorrelation (HAC) robust standard errors computed using nonparametric spectral density estimators without truncation. While such standard errors are not consistent, a new asymptotic theory shows that they lead to valid tests nonetheless. In an over-identified linear instrumental variables model, simulations suggest that the new tests and the associated limiting distribution theory provide a more accurate first order asymptotic null approximation than standard HAC robust tests. Finite sample power of the new tests is shown to be comparable to standard tests. Because use of a truncation lag equal to the sample requires no additional choices for practitioners, the new approach could potentially lead to a standard of practice (which does not currently exist) for the computation of HAC robust standard errors in GMM models.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Cornell University, Center for Analytic Economics in its series Working Papers with number 01-12.
Date of creation: Jun 2001
Date of revision:
Contact details of provider:
Postal: 402 Uris Hall, Ithaca, NY 14853
Phone: (607) 255-9901
Fax: (607) 255-2818
Web page: http://www.arts.cornell.edu/econ/CAE/workingpapers.html
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.:
- Karim M. Abadir & Paolo Paruolo, 1997. "Two Mixed Normal Densities from Cointegration Analysis," Econometrica, Econometric Society, vol. 65(3), pages 671-680, May.
- Shin-Kun Peng & Takatoshi Tabuchi, 2007.
"Spatial Competition in Variety and Number of Stores,"
Journal of Economics & Management Strategy,
Wiley Blackwell, vol. 16(1), pages 227-250, 03.
- Shin-Kun Peng & Takatoshi Tabuchi, 2005. "Spatial Competition in Variety and Number of Stores," CIRJE F-Series CIRJE-F-360, CIRJE, Faculty of Economics, University of Tokyo.
- Shin-Kun Peng & Takatoshi Tabuchi, 2006. "Spatial Competition in Variety and Number of Stores," IEAS Working Paper : academic research 06-A002, Institute of Economics, Academia Sinica, Taipei, Taiwan.
- Wei-Ming Lee & Chung-Ming Kuan & Yu-Chin Hsu, 2014.
"Testing Over-Identifying Restrictions without Consistent Estimation of the Asymptotic Covariance Matrix,"
IEAS Working Paper : academic research
14-A001, Institute of Economics, Academia Sinica, Taipei, Taiwan.
- Wei-Ming Lee & Chung-Ming Kuan, 2006. "Testing Over-Identifying Restrictions without Consistent Estimation of the Asymptotic Covariance Matrix," IEAS Working Paper : academic research 06-A009, Institute of Economics, Academia Sinica, Taipei, Taiwan.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ().
If references are entirely missing, you can add them using this form.