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

A-Tier
Journal: Review of Economics and Statistics
Year: 2015
Volume: 97
Issue: 1
Pages: 210-233

Authors (2)

Score contribution per author:

2.011 = (α=2.01 / 2 authors) × 2.0x A-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

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

Technical Details

RePEc Handle
repec:tpr:restat:v:97:y:2015:i:1:p:210-233
Journal Field
General
Author Count
2
Added to Database
2026-01-29