The Difference and System generalized method of moments (GMM) estimators are growing in popularity, thanks in part to specialized software. But as implemented in these packages, the estimators easily generate results by default that are at once invalid yet appear valid in specification tests. The culprit is their tendency to generate instruments that are a) numerous and, in System GMM, b) suspect. A large collection of instruments, even if individually valid, can be collectively invalid in finite samples because they overfit endogenous variables. They also weaken the Hansen test of overidentifying restrictions, which is commonly relied upon to check instrument validity. This paper reviews the evidence on the effects of instrument proliferation, and describes and simulates simple ways to control it. It illustrates the dangers by replicating two early applications to economic growth: Forbes (2000) on income inequality and Levine, Loayza, and Beck (2000) on financial sector development. Results in both papers appear driven by previously undetected endogeneity
