EMPIRICALLY ESTIMATING THE IMPACT OF WEATHER ON AGRICULTURE
This research explores the consequences of measurement error in satellite weather data on estimates of agricultural production. We combine plot-level production data from the Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMS-ISA) with weather data from seven different satellite sources to explore the consequences of several types of measurement error. These include inaccuracies due to measurement technology, due to the spatial resolution of the data, due to obfuscation of household GPS coordinates, and due to the use of inappropriate weather metrics.
Collaborators: Anna Josephson (University of Arizona), Talip Kilic (World Bank), and Siobhan Murray (World Bank)
Funding: World Bank Group
 
21ST CENTURY TECHNOLOGIES FOR IMPROVES WEATHER FORECASTING AND FARMER DECISION-MAKING
New technological advances in remote sensing, cellular microwave links (CMLs), and machine learning provide a leapfrog opportunity for weather forecasting. This research explores the potential for one of these technologies, CMLs, to provide accurate, near real-time rainfall data to farmers. Using a randomized control trial, we are conducting a pilot project to investigate the use of CML data by smallholder farmers, how best to deliver actionable weather forecasts, and how farmers use these data in production decision-making.
Collaborators: Tom Evans (University of Arizona) and Anna Josephson (University of Arizona)
Funding: U of A Early Career Faculty Seed Grant

Back to my research