Standard measures of productivity display enormous dispersion across farms in Africa. Crop yields and input intensities appear to vary greatly, seemingly in conflict with a model of efficient allocation across farms. In this paper, we present a theoretical framework for distinguishing between measurement error, unobserved heterogeneity, and potential misallocation. Using rich panel data from farms in Tanzania and Uganda, we estimate our model using a flexible specification in which we allow for several kinds of measurement error and heterogeneity. We find that measurement error and heterogeneity together account for a large fraction of the dispersion in measured productivity.

We examine the economic impact of high-yielding crop varieties (HYVs) in developing countries 1960-2000. We use time variation in the development and diffusion of HYVs of 10 major crops, spatial variation in agro-climatically suitability for growing them, and a differences-in-differences strategy to identify the causal effects of adoption. In a sample of 84 counties, we estimate that a 10 percentage points increase in HYV adoption increases GDP per capita by about 15 percent. This effect is fully accounted for by the direct effect on crop yields, factor adjustment, and structural transformation. We also find that HYV adoption reduced both fertility and mortality.