As a quick econometric solution to handle potential endogeneity issues in panel data models, the Arellano-Bond/Blundell-Bond generalized method of moments (GMM) estimator continues to gain popularity in IS research. Despite this estimator’s sensitivity to model specifications and estimation strategies, a noticeable number of IS studies that have employed this method have failed to report the detailed model specifications, robustness check results with different model specifications and estimation strategies, or test statistics, which render their empirical results less credible. Using simulated data and real data, we empirically demonstrate that passing the commonly required tests, such as the m2 test and the Sargan/Hansen test, does not guarantee the estimate’s validity because its size and statistical significance can largely depend on the estimation procedure and moment restrictions that researchers choose. We urge researchers to not only report the results of significant focal variables but also explicitly discuss model specifications and estimation strategies and provide robustness checks with different model specifications along with their complete test results
