Differences-in-Differences (DID) is one of the most widely used identification strategies in applied economics. However, inference in DID models when there are few treated groups is still an open question. We show that usual inference methods used in DID models might not perform well when there...

Differences-in-Differences (DID) is one of the most widely used identification strategies in applied economics. However, inference in DID models when there are few treated groups remains an open question. We show that the usual inference methods used in DID models might not perform well when...

We study the impacts of a program that introduced a computer-assisted learning platform into regular math classes using a randomized control trial in Brazilian primary public schools. Once a week, teachers would take their students to the school's computer lab and teach using a dynamically...

Differences-in-Differences (DID) is one of the most widely used identification strategies in applied economics. However, how to draw inferences in DID models when there are few treated groups remains an open question. We show that the usual inference methods used in DID models might not perform...

The synthetic control (SC) method has been recently proposed as an alternative to estimate treatment effects in comparative case studies. The SC relies on the assumption that there is a weighted average of the control units that reconstructs the potential outcome of the treated unit in the...

The synthetic control (SC) method has been recently proposed as an alternative to estimate treatment effects in comparative case studies. In this paper, we revisit the SC method in a linear factor model setting and consider the asymptotic properties of the SC estimator when the number of...

The synthetic control (SC) method has been recently proposed as an alternative to estimate treatment effects in comparative case studies. In this paper, we revisit the SC method in a linear factor model setting and derive conditions under which the SC estimator is asymptotically unbiased when...

The synthetic control (SC) method has been recently proposed as an alternative to estimate treatment effects in comparative case studies. An important feature of the SC method is the inferential procedures based on placebo studies, suggested in Abadie et al. (2010). In this paper, we evaluate...

We show that a lack of guidance on how to choose the matching variables used in the Synthetic Control (SC) estimator creates specification-searching opportunities in SC applications. This undermines one of the potential advantages of the method, which is providing a transparent way of choosing...

We analyze the properties of matching estimators when the number of treated observations is fixed while the number of treated observations is large. We show that, under standard assumptions, the nearest neighbor matching estimator for the average treatment effect on the treated is asymptotically...