Economic statistics are frequently produced at an administrative level such as the sub-national division. However, these measures may not adequately capture the local variation in the economic activities that is useful for analyzing local economic development patterns and the exposure to natural...

This paper examines two new methods to generate gridded agricultural Gross Domestic Product (GDP) and compares the results with a traditional method. In the case of Brazil, these two new methods of spatial disaggregation and cross-entropy outperform the prediction of agricultural GDP from the...

The literature suggests a wide range of impacts of improved transport connectivity on agricultural growth. Still, the infrastructure-growth nexus remains somewhat mysterious, particularly in the African context, because many rural farmers do not have their own transport means. Using data from...

Spatial analysis in economics is becoming increasingly important as more spatial data and innovative data mining technologies are developed. Even in Africa, where data often crucially lack quality analysis, a variety of spatial data have recently been developed, such as highly disaggregated crop...

Large gaps exist in our knowledge of the current geographic distribution and spatial patterns of performance of crops, and these gaps are unlikely to be filled. In addition, even the spatial scale of many sub-national statistical reporting units remains too coarse to capture patterns of spatial...

We describe a new crop allocation model that adds further methodological and data enhancements to the available crop downscaling modeling. The model comprises the estimates of crop area, yield and production for 20 major crops under four rainfed and irrigated production systems across a global...