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.

翻译：FAO-GAEZ生产力数据在经济学研究中被广泛使用，但现有实证文献鲜少讨论其测量误差问题。本文利用两个代理变量，在非经典测量误差框架下推导出农业生产力效应新颖的解析边界。这些边界所依赖的假设条件弱于现有实证研究中的设定，且充分利用了数据一阶矩与二阶矩所包含的信息。通过对三项具有重要影响的研究进行重新评估，本文证实测量误差具有显著影响，且农业生产力的实际效应可能低于既往报告的估计值。本方法对涉及变量误测的实证研究具有广泛适用性。