Asymptotic F Test in a GMM Framework with Cross Sectional Dependence
The paper develops an asymptotically valid F test that is robust to spatial autocorrelation in a GMM framework. The test is based on the class of series covariance matrix estimators and ?fixed-smoothing asymptotics. The fi?xed-smoothing asymptotics and F approximation are established under mild sufficient conditions for a central limit theorem. These conditions can accommodate a wide range of spatial processes. This is in contrast with the standard arguments, which often impose very restrictive assumptions so that a functional central limit theorem holds. The proposed F test is very easy to implement, as critical values are from a standard F distribution. To a great extent, the asymptotic F test achieves triple robustness: it is asymptotically valid regardless of the spatial autocorrelation, the sampling region, and the limiting behavior of the smoothing parameter. Simulation shows that the F test is more accurate in size than the conventional chi-square tests, and it has the same size accuracy and power property as nonstandard tests that require computationally intensive simulation or bootstrap.
|Date of creation:||Jun 2012|
|Date of revision:|
|Contact details of provider:|| Postal: 350 Victoria Street, Toronto, Ontario, M5B 2K3|
Phone: (416) 979-5092
Fax: (415) 979-5273
Web page: http://www.ryerson.ca/economics/
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.:
- Conley, T. G., 1999. "GMM estimation with cross sectional dependence," Journal of Econometrics, Elsevier, vol. 92(1), pages 1-45, September.
- Kiefer, Nicholas M. & Vogelsang, Timothy J., 2005.
"A New Asymptotic Theory for Heteroskedasticity-Autocorrelation Robust Tests,"
05-08, Cornell University, Center for Analytic Economics.
- Kiefer, Nicholas M. & Vogelsang, Timothy J., 2005. "A New Asymptotic Theory For Heteroskedasticity-Autocorrelation Robust Tests," Econometric Theory, Cambridge University Press, vol. 21(06), pages 1130-1164, December.
- Sun, Yixiao, 2011. "Robust trend inference with series variance estimator and testing-optimal smoothing parameter," Journal of Econometrics, Elsevier, vol. 164(2), pages 345-366, October.
- Jenish, Nazgul & Prucha, Ingmar R., 2009. "Central limit theorems and uniform laws of large numbers for arrays of random fields," Journal of Econometrics, Elsevier, vol. 150(1), pages 86-98, May.
- Kim, Min Seong & Sun, Yixiao, 2011. "Spatial heteroskedasticity and autocorrelation consistent estimation of covariance matrix," Journal of Econometrics, Elsevier, vol. 160(2), pages 349-371, February.
- Kelejian, Harry H. & Prucha, Ingmar R., 2007. "HAC estimation in a spatial framework," Journal of Econometrics, Elsevier, vol. 140(1), pages 131-154, September.
When requesting a correction, please mention this item's handle: RePEc:rye:wpaper:wp032. 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: (Maurice Roche)
If references are entirely missing, you can add them using this form.