The Mismeasure of Weather : Using Remotely Sensed Earth Observation Data in Economic Contexts

The availability of weather data from remotely sensed Earth observation data has reduced the cost of including weather variables in econometric models. Weather variables are common instrumental variables used to predict economic outcomes and serve as an input in modeling crop yields for rainfed agriculture. The use of Earth observation data in econometric applications has only recently been met with critical assessment of the suitability and quality of these data in economics. This paper quantifies the significance and magnitude of the effect of measurement error in Earth observation data in the context of smallholder agricultural productivity. The paper shows that different Earth observation sources use different measurement methods. The findings are not robust to the choice of Earth observation dataset, and the outcomes are not simply affine transformations of one another. Thus, the paper suggests that researchers should exercise caution in using these data and include robustness checks that test alternative sources of Earth observation data.