Assessing misallocation in agriculture: Plots versus farms
利用乌干达农户数据，研究发现地块层面计算的资源错配程度远高于农场层面，且地块层面潜在农业生产力提升高达562%，提示数据聚合水平会影响错配评估。
We examine empirically whether the level of data aggregation affects the assessment of misallocation in agriculture. Using data from Ugandan farmers, we document a substantial discrepancy between misallocation measures calculated at the plot and at the farm levels. Estimates of misallocation at the plot level are much higher than those obtained with the same data but aggregated at the farm level. Even after accounting for measurement error and unobserved heterogeneity, estimates of misallocation at the plot level are extremely high, with potential nationwide agricultural productivity gains of 562%. Furthermore, we find suggestive evidence that granular data may be more susceptible to measurement error in survey data and that data aggregation can attenuate the relative magnitude of measurement error in misallocation measures. Our findings suggest caution in generalizing insights on measurement error and misallocation from plot-level analysis to those at the farm level.