Solving linear programs by using entropic penalization has recently attracted new interest in
the optimization community, since this strategy forms the basis for the fastest-known …

This paper proposes new estimators for the propensity score that aim to maximize the
covariate distribution balance among different treatment groups. Heuristically, our proposed …

We analyze the properties of matching estimators when there are few treated, but many
control observations. We show that, under standard assumptions, the nearest neighbor …

The reform of the capital market registration system will affect not only the pricing of issuance
in the primary market but also the pricing of circulation in the secondary market. This article …

We consider two recent suggestions for how to perform an empirically motivated Monte
Carlo study to help select a treatment effect estimator under unconfoundedness. We show …

There is no agreement regarding the role of fresh fruit and vegetables' affordability,
accessibility and availability, or access in general, on obesity rates. In this article we …

This study estimates the effect of between-class ability grouping on Chilean secondary
students' academic achievement. We rely on a structural feature of the school system: A …

The synthetic control estimator (Abadie et al., 2010) is asymptotically unbiased assuming
that the outcome is a linear function of the underlying predictors and that the treated unit can …

Currently there is little practical advice on which treatment effect estimator to use when trying
to adjust for observable differences. A recent suggestion is to compare the performance of …

The blopmatching estimator for average treatment effects in observational studies is a
nonparametric matching estimator proposed by Díaz, Rau, and Rivera (2015, Review of …