Many studies estimate the Frisch elasticity via two-stage least squares (2SLS) regression of hours changes on wage changes. However, 2SLS suffers from a power asymmetry problem that makes estimates far away from ordinary least squares appear spuriously imprecise. Hence, it is difficult for t-tests to detect a positive Frisch elasticity. We illustrate the problem using NLSY97 data. We estimate an elasticity of 0.60 for young men, but the t-test indicates that it is insignificant. The Anderson-Rubin (AR) test, which avoids the power asymmetry problem, indicates that it is highly significant. We argue that the AR test should be widely adopted in lieu of the t-test in instrumental variable applications.