Testing in GMM Models without Truncation
This 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.
|Date of creation:||Jun 2001|
|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
References listed on IDEAS
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.
When requesting a correction, please mention this item's handle: RePEc:ecl:corcae:01-12. 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: ()
If references are entirely missing, you can add them using this form.