Expenditure data mapping

Impact evaluation is one of the most widespread practices in quantitative social sciences, and it always requires data on an intervention and a relevant outcome. Despite its generalised adoption, impact evaluation is limited to a reduced number of policy domains where data are available. Ironically, in many countries, there exist government expenditure data across thousands of policies that are not linked to relevant outcome variables. Manually mapping expenditure into indicators can be prohibitively expensive to many governments, severely limiting their ability to integrate impact evaluation in the policy cycle. In this research area, Daniele Guariso and I investigate different computational approaches to alleviate this problem and to provide automated mapping tool.