When benchmarking production units by non-parametric methods like data envelopment analysis (DEA), an assumption has to be made about the returns to scale of the underlying technology. Moreover, it is often also relevant to compare the frontiers across samples of producers. Until now, no exact...

Permutation techniques, where one recompute the test statistic over permutations of data, have a long history in statistics and have become increasingly useful as the availability of computational power has increased. Until now, no permutation tests for examining returns to scale assumptions,...

It can be argued that the competitiveness of an industry consists of two main parts: The production conditions and the utilization of these. The production conditions are largely determined by factors exogenous to the firms comprising the industry, including the economic environment, regulatory...

Data Envelopment Analysis (DEA) is often used by regulators to create a pseudo-competitive environment for sectors with natural monopolies. In addition to develop a theoretically well-behaved model, regulators need to take into account several other factors, such as the political agenda and the...

The Danish water regulator uses, among other things, Data Envelopment Analysis to create a pseudo-competitive environment for the water companies. The benchmarking results are used to set an individual revenue cap for each company. The benchmarking model is currently criticized for not including...

Researchers and practitioners who use Data Envelopment Analysis often want to incorporate several inputs and outputs in their model to consider as much relevant information as possible. However, too many inputs and outputs can result in the well-known dimensionality problem referred to as the...