Tightly knit extended families, in which people often give money to and get money from relatives, characterize many developing countries. These intra-family flows mean that public policies may affect a very different group of people than the one they target. To assess the empirical importance of...

Many papers use fixed effects (FE) to identify causal impacts of an intervention. In this paper we show that when the treatment status only varies within some groups, this design can induce non-random selection of groups into the identifying sample, which we term selection into identification...

We study the extent to which ML techniques can be used to improve tax auditing efficiency using administrative data, without the need of randomized audits. Using Italy's population data on sole proprietorship tax returns, audits and their outcome, we develop a new approach to address the so...