This paper by using Data Envelopment Analysis (DEA) and statistical inference evaluates the citation performance of 229 economic journals. The paper categorizes the journals into four main categories (A to D) based on their efficiency levels. The results are then compared to the 27 "core...

We consider efficiency measurement methods in the presence of uncertain input and output data, and without the (empirically problematic) assumption of convexity of the production technology. In particular, we perform a simulation study in order to contrast two well-established methods, IDEA and...

Levels of CO2 emissions from electricity generation in the U.S. have changed considerably in the last decade. This development can be attributed to two factors. First, the shale gas revolution has reduced gas prices significantly, leading to a crowding out of the more CO2-intensive coal for...

Research on productive efficiency at the firm level has developed as an important and active strand of research the last decades, both within operations research, management science and economics. However, the interests pursued within the fields have had some differences regarding sound...

Some models are presented in this paper which extend the concept of measuring superefficiency to the useful case of variable returns-to-scales (VRS), thus enabling the ranking of efficient as well as inefficient units. Two models, namely the Universal Radial Model and the Universal Additive...

The standard indicators used to compare cross-country innovation are in the Global Competitiveness Report (GCR). But there are problems with aggregation and response bias with these largely self-reported measures (Hollanders and van Cruysen, 2008). We propose a theory-based metric using Data...

Dieser Aufsatz dient dem Versuch, ein konsistentes wirtschaftspolitisches Bewertungsverfahren zur Analyse der Leistungsfähigkeit der genossenschaftlichen Bankunternehmung zu entwickeln. Dafür wird das auf linearer Programmierung beruhende Schätzverfahren "Data Envelopment Analysis (DEA)"...

Since the introduction of bootstrap DEA there is a growing literature on applications which use this method, mainly for hypothesis testing. It is therefore important to establish the consistency and evaluate the performance of bootstrap DEA. The few Monte Carlo experiments in the literature...

Bootstrapping non-parametric models is a fairly complicated exercise which is associated with implicit assumptions or requirements that are not always obvious to the non-expert user. Bootstrap DEA is a significant development of the past decade; however, some of its assumptions and properties are...

Data Envelopment Analysis (DEA) based cost norms have attractive properties in the regulation of natural monopolies. However, they are also sensitive to the choice of cost drivers. When some of the cost drivers are discretionary, this may lead to suboptimal incentives. When a regulated firm...