Suchergebnisse

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 historical context of the regulation. This sometimes results in some unconventional approaches, which furthermore are not easily changed. In this paper, we discuss the model used for DEA-based benchmark regulation of the Danish water sector. More specifically, we look at the characteristics of the method the regulator uses to take into account differences in the companies' environmental conditions. We show how the approach currently used to control for differences in environmental conditions seemingly does not sufficiently control for the actual differences as intended since second stage analysis still reveals significant correlations between the efficiency scores and these external factors. To explain this, we reconsider the second stage analysis, using permutation-based approaches and also accounting for the fact that only those companies that in the DEA assign weights to those output measures adjusted for environmental conditions, will benefit from the adjustments.

Die wachsende Nachfrage der Gebergemeinschaft führt in Lateinamerika zu einem Boom von Umweltschutzaktivitäten Nichtstaatlicher Organisationen und zu wesentlichen Veränderungen der institutionellen Rahmenbedingungen, wie die Fallstudie zu der von USAID geförderten "Fundacion Nature" in Ekuador belegt. Der Beitrag diskutiert Ansätze einer Theorie der Non-Profit-Organisationen als ökonomischer Einheiten im Prozeß des endogenen institutionellen Wandels. (DSE)

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 historical context of the regulation. This sometimes results in some unconventional approaches, which furthermore are not easily changed. In this paper, we discuss the model used for DEA-based benchmark regulation of the Danish water sector. More specifically, we look at the characteristics of the method the regulator uses to take into account differences in the companies' environmental conditions. We show how the approach currently used to control for differences in environmental conditions seemingly does not sufficiently control for the actual differences as intended since second stage analysis still reveals significant correlations between the efficiency scores and these external factors. To explain this, we reconsider the second stage analysis, using permutation-based approaches and also accounting for the fact that only those companies that in the DEA assign weights to those output measures adjusted for environmental conditions, will benefit from the adjustments.

Glyphosate is one of the most widely used chemical products worldwide and its manufacturer has considered it the safest herbicide for human health around the world under the stated technical conditions: a direct fumigation on weed, concentration use of between 1 to 3%, and low dose and low exposure time on the part of the person who is handling the herbicide. Glyphosate has a short lifespan, about three months, but the analyses on the environmental destination of this herbicide get to detect it up to two years later, especially in soils rich in iron. Whatever the case may be, it is obvious tha