Asymptotic F-Test in a GMM Framework with Cross-Sectional Dependence

Yixiao Sun and Min Seong Kim ()
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Min Seong Kim: Ryerson University

The Review of Economics and Statistics, 2015, vol. 97, issue 1, 210-233

Abstract: The paper develops an asymptotically valid F-test that is robust to spatial autocorrelation in a GMM framework. The validity of the F-test is established under mild conditions that can accommodate a wide range of spatial processes. The proposed F-test is very easy to implement, as critical values are from a standard F-distribution. The 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 also shows that the F-test has good size and power properties in finite samples. © 2015 The President and Fellows of Harvard College and the Massachusetts Institute of Technology

Keywords: F-test; GMM framework; asymptotically valid; spatial autocorrelation; sampling region; limiting behavior (search for similar items in EconPapers)
JEL-codes: B00 (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (12)

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Working Paper: Asymptotic F Test in a GMM Framework with Cross Sectional Dependence (2012)
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