Alberto Abadie

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Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program Alberto Abadie, Alexis Diamond & Jens Hainmueller a Alberto Abadie is Professor, John F. Kennedy School of Government, Harvard University, 79 John F. Kennedy Street, Cambridge, MA 02138 . Alexis Diamond is Evaluation Officer, The(More)
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This article considers the problem of assessing the distributional consequence s of a treatment on some outcome variable of interest when treatment intake is (possibly) nonrandomized , but there is a binary instrument available for the researcher. Such a scenario is common in observationa l studies and in randomized experiments with imperfect compliance.(More)
This paper presents an implementation of matching estimators for average treatment effects in Stata. The nnmatch command allows you to estimate the average effect for all units or only for the treated or control units; to choose the number of matches; to specify the distance metric; to select a bias adjustment; and to use heteroskedastic-robust variance(More)
This article introduces a new class of instrumental variable (IV) estimators for linear and nonlinear treatment response models with covariates. The rationale for focusing on nonlinear models is that, if the dependent variable is binary or limited, or if the e(ect of the treatment varies with covariates, a nonlinear model is appropriate. In the spirit of(More)
The difference-in-differences (DID) estimator is one of the most popular tools for applied research in economics to evaluate the effects of public interventions and other treatments of interest on some relevant outcome variables. However, it is well-known that the DID estimator is based on strong identifying assumptions. In particular, the conventional DID(More)
This article provides an empirical investigation of the determinants of terrorism at the country level. In contrast with the previous literature on this subject, which focuses on transnational terrorism only, I use a new measure of terrorism that encompasses both domestic and transnational terrorism. In line with the results of some recent studies, this(More)
In the regression-discontinuity (RD) design, units are assigned to treatment based on whether their value of an observed covariate exceeds a known cutoff. In this design, local polynomial estimators are now routinely employed to construct confidence intervals for treatment effects. The performance of these confidence intervals in applications, however, may(More)
In Abadie and Imbens (2006), it was shown that simple nearest-neighbor matching estimators include a conditional bias term that converges to zero at a rate that may be slower than N1/2. As a result, matching estimators are not N1/2-consistent in general. In this article, we propose a bias correction that renders matching estimators N1/2-consistent and(More)