This paper explores the consequences for parametric and non-parametric efficiency levels and rankings when using grouped instead of individual Decision Making Units (DMU). The bias results due to the differences of the grouped DMUs frontier compared to the individual DMUs frontier. Monte Carlo...

The evaluation of interventions such as active labor market policies or medical programs by means of a randomized controlled trial is often considered the gold standard. However, randomized experiments might face severe shortcomings especially if performed at the group level. One such problem is...

Inference using difference-in-differences with clustered data requires care. Previous research has shown that t tests based on a cluster-robust variance estimator (CRVE) severely over-reject when there are few treated clusters, that different variants of the wild cluster bootstrap can...