This paper combines panel data from nationally representative household-level surveys in Nigeria with long-term satellite-based spatial data on temperature and precipitation using geo-referenced information related to households.

We combine nationally representative data from Nigeria with spatiotemporal data from remote sensing and other sources to study how young migrants respond to observable characteristics of potential destinations, both in absolute terms and relative

Based on experiments to bring about comprehensive crop insurance coverage over the last 50 years, the Indian government introduced a new crop insurance program, called Pradhan Mantri Fasal Bima Yojana (PMFBY), in April 2016.

This paper applies a recurrent neural network (RNN) method to forecast cotton and oil prices. We show how these new tools from machine learning, particularly Long-Short Term Memory (LSTM) models, complement traditional methods.

Policy-making processes in developing countries often continue to operate devoid of evidence.

Since Amartya Sen’s famous work on Poverty and Famines, economists have understood that policy responses to food market shocks should be guided by changes in households’ incomes and access to food, rather than by overall food availability.

Understanding the global distribution of agricultural production provides valuable context for policymaking concerning development, wellbeing, and climate change.