We introduce the package ddml for Double/Debiased Machine Learning (DDML) in Stata. Estimators of causal parameters for five different econometric models are supported, allowing for flexible estimation of causal effects of endogenous variables in settings with unknown functional forms and/or...

Montero (2022) explores a discontinuity in a land reform in El Salvador and reports two main findings. First, relative to outside-owned haciendas operated by contract workers, the productivity of worker-owned cooperatives is higher for staple crops and lower for cash-crop. Second, cooperative...

We examine the health impacts of long commute time by exploiting a large-scale placed-based policy in South Korea. The policy relocated public employers in the capital area to disadvantaged cities. However, some public employees kept their residences in the capital area and spend long hours...

In this paper, we describe a computational implementation of the Synthetic difference-in-differences (SDID) estimator of Arkhangelsky et al. (2021) for Stata. Synthetic difference-in-differences can be used in a wide class of circumstances where treatment effects on some particular policy or...

This paper proposes a time-weighted difference-in-differences (TWDID) estimation approach that is robust against interactive fixed effects in short T panels. Time weighting substantially reduces both bias and variance compared to conventional DID estimation through balancing the pre-treatment...

The Credibility Revolution advances quantitative research designs intended to identify causal effects from observed data. The ensuing emphasis on internal validity however has enabled the neglect of construct and external validity. This article develops a framework we call causal specification....