Policy makers and city planning professionals who work on transit-oriented development are often interested in evaluating the quality of physical environment around metro stations. How to carry out this task comprehensively, effectively and repeatedly, with limited time and budget? Under the GEF...

Proxy means test (PMT) poverty targeting tools have become common tools for beneficiary targeting and poverty assessment where full means tests are costly. Currently popular estimation procedures for generating these tools prioritize minimization of in-sample prediction errors; however, the...

Many households in developing countries lack formal financial histories, making it difficult for firms to extend credit, and for potential borrowers to receive it. However, many of these households have mobile phones, which generate rich data about behavior. This article shows that behavioral...

This paper proposes a methodology for identifying urban areas that combines subjective assessments with machine learning, and applies it to India, a country where several studies see the official urbanization rate as an under-estimate. For a representative sample of cities, towns and villages,...

To overcome the constraints for policy and practice posed by limited availability of data on crop rotation, this paper applies machine learning to freely available satellite imagery to identify the rotational practices of more than 7,000 villages in Ukraine. Rotation effects estimated based on...

This paper uses Multiple Indicator Cluster Surveys data from the Republic of Congo and Sao Tome and Principe to study the relationships between child stature, mother's years of education, and indicators of early childhood development. The relationships are contrasted between two empirical...

With all the recent attention focused on big data, it is easy to overlook that basic vital statistics remain difficult to obtain in most of the world. This project set out to test whether an openly available dataset (Twitter) could be transformed into a resource for urban planning and...

This paper proposes a set of new methods to estimate inequality of opportunity based on conditional inference regression trees. It illustrates how these methods represent a substantial improvement over existing empirical approaches to measure inequality of opportunity. First, the new methods...

This paper implements a machine learning approach to estimate intra-generational economic mobility using cross-sectional data. A Least Absolute Shrinkage and Selection Operator (Lasso) procedure is applied to explore poverty dynamics and household-level welfare growth in the absence of panel...

Country-level census data are typically collected once every 10 years. However, conflict, migration, urbanization, and natural disasters can cause rapid shifts in local population patterns. This study uses Sri Lankan data to demonstrate the feasibility of a bottom-up method that combines...