The FAO-GAEZ productivity data are widely used in Economics. However, the empirical literature rarely discusses measurement error. We use two proxies to derive novel analytical bounds around the effect of agricultural productivity in a setting with nonclassical measurement error. These bounds rely on assumptions that are weaker than the ones imposed in empirical studies and exhaust the information contained in the first two moments of the data. We reevaluate three influential studies, documenting that measurement error matters and that the impact of agricultural productivity may be smaller than previously reported. Our methodology has broad applications in empirical research involving mismeasured variables.