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Description: We seek to quantify the significance and magnitude of the effect of measurement error in satellite weather data on modeling agricultural production, agricultural productivity, and resilience outcomes. In order to provide rigor to our approach, we combine geo-spatial weather data from a variety of remote sensing sources with the geo-referenced household survey data from seven sub-Saharan African countries that are part of the World Bank Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA) initiative. Our goal is to provide systematic evidence on which weather metrics have strong predictive power over a large set of crops and countries and which metrics are only useful in highly specific settings.
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