Due to data constraints, the intergenerational income elasticity (IGE)—the workhorse measure of economic mobility—has very often been estimated with short-run income measures drawn from two independent samples and using the Two-Sample Two-Stage Least Squares (TSTSLS) estimator. The IGE conventionally estimated in the mobility literature, however, has been widely misinterpreted as pertaining to the conditional expectation of children’s income when in fact it pertains to its conditional geometric mean. In line with recent work, this article focuses almost exclusively on the IGE of expected income. It (a) proposes that estimation of this IGE in the two-sample context be based on a recently advanced two-sample generalized method of moments (GMM) estimator of the exponential regression model, and (b) introduces the user-written program igetwos, which implements that estimator as well as a GMM version of the TSTSLS estimator. The new program allows to use Stata to estimate both the IGE of the expectation and the IGE of the geometric mean when the income information for parents and children is available in two independent samples.