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...

Inference based on cluster-robust standard errors is known to fail when the number of clusters is small, and the wild cluster bootstrap fails dramatically when the number of treated clusters is very small. We propose a family of new procedures called the sub- cluster wild bootstrap. In the case...