Using Satellite Remote Sensing Data in a Spatially Explicit Price Model: Vegetation Dynamics and Millet Prices

Molly E. Brown, Jorge E. Pinzon and Stephen D. Prince

Abstract

Famine early warning organizations use data from multiple disciplines to assess food insecurity of communities and regions in less-developed parts of the world. Here we present a model that integrates information on the suitability of the growing season and millet prices in the dry central and northern areas of West Africa. The model is used to create spatially continuous maps of millet prices. By coupling the model with remote sensing vegetation data estimated one to four months into the future, we create a leading indicator of potential price movements for early warning of food crises. (JEL Q13)

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