Propensity score matching estimators have two advantages. One is that they overcome the curse of dimensionality of covariate matching, and the other is that they are nonparametric. However, the propensity score is usually unknown and needs to be estimated. If we estimate it nonparametrically, we...

When considering multiple hypothesis tests simultaneously, standard statistical techniques will lead to over-rejection of null hypotheses unless the multiplicity of the testing framework is explicitly considered. In this paper we discuss the Romano-Wolf multiple hypothesis correction, and...

We discuss methods for calculating multivariate normal probabilities by simulation and two new Stata programs for this purpose: - mdraws - for deriving draws from the standard uniform density using either Halton or pseudo-random sequences, and an egen function - mvnp() - for calculating the...

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...

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...

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 estimators in simulations that somehow mimic the empirical context. Two ways to run such 'empirical Monte...

Based on a sequence of reforms in the Norwegian unemployment insurance (UI) system, weshow that activity-oriented UI regimes – i.e., regimes with a high likelihood of requiredparticipation in active labor market programs, duration limitations on unconditional UIentitlements, and high sanction...

We examine empirically the impacts of labor market policies - in terms of unemployment insurance (UI) and active labor market programs (ALMP) - on the duration and outcome of job search and on the quality of a subsequent job. We find that time invested in job search tends to pay off in the form...

Based on a sequence of reforms in the Norwegian unemployment insurance (UI) system, we show that activity-oriented UI regimes - i.e., regimes with a high likelihood of required participation in active labor market programs, duration limitations on unconditional UI entitlements, and high sanction...

This paper builds on the Empirical Monte Carlo simulation approach developed by Huber et al. (2013) to study the estimation of Timing-of-Events (ToE) models. We exploit rich Swedish data of unemployed job-seekers with information on participation in a training program to simulate placebo...