Maintaining the Regular Ultra Passum Law in data envelopment analysis

The variable returns to scale data envelopment analysis (DEA) model is developed with a maintained hypothesis of convexity in input-output space. This hypothesis is not consistent with standard microeconomic production theory that posits an S-shape for the production frontier, i.e. for production technologies that obey the Regular Ultra Passum Law. Consequently, measures of technical efficiency assuming convexity are biased downward. In this paper, we provide a more general DEA model that allows the S-shape.Data envelopment analysis; homothetic production; S-shaped production function; non-convex production set

Scale properties in data envelopment analysis

Recently there has been some discussion in the literature concerning the nature of scale properties in the Data Envelopment Model (DEA). It has been argued that DEA may not be able to provide reliable estimates of the optimal scale size. We argue in this paper that DEA is well suited to estimate optimal scale size, if DEA is augmented with two additional maintained hypotheses which imply that the DEA-frontier is consistent with smooth curves along rays in input and in output space that obey the Regular Ultra Passum (RUP) law (Frisch 1965). A necessary condition for a smooth curve passing through all vertices to obey the RUP-law is presented. If this condition is satisfied then upper and lower bounds for the marginal product at each vertex are presented. It is shown that any set of feasible marginal products will correspond to a smooth curve passing through all points with a monotonic decreasing scale elasticity. The proof is constructive in the sense that an estimator of the curve is provided with the desired properties. A typical DEA based return to scale analysis simply reports whether or not a DMU is at the optimal scale based on point estimates of scale efficiency. A contribution of this paper is that we provide a method which allows us to determine in what interval optimal scale is located.DEA; efficiency

Testing over-representation of observations in subsets of a DEA technology

This paper proposes a test for whether data are over-represented in a given production zone, i.e. a subset of a production possibility set which has been estimated using the non-parametric Data Envelopment Analysis (DEA) approach. A binomial test is used that relates the number of observations inside such a zone to a discrete probability weighted relative volume of that zone. A Monte Carlo simulation illustrates the performance of the proposed test statistic and suggests good estimation of both facet probabilities and the assumed common inefficiency distribution in a three dimensional input space.Data Envelopment Analysis (DEA); Over-representation; Data density; Binomial test; Convex hull

Anmeldelse af "Krigeren, borgeren og taberen"

"Krigeren, borgeren og taberen" / af Ole Thyssen, Henrik Dahl. - 2. oplag. [Kbh.] : Gyldendal, 2006. 243 sider

Identification of nuclear factors which interact with the 5′ flanking region of the EF-1αO gene in Xenopus laevis

AbstractThe EF-1αO gene of Xenopus laevis is a stage-specific gene, being transcribed in oogonia and oocytes, but not in postmeiotic germ cells and terminally differentiated cells. We found that two trans-acting factors from oocyte nuclear extract are able to interact with a DNA sequence in the 5′-upstream region of the EF-1αO gene. Methylation interference experiments suggested that the two factors recognised the same DNA element. Gel retardation assays indicated that part of the protein binding site could be confined to a 21 bp sequence, located between −51 and −72, relative to the cap site. Interestingly, this region shares great homology to a negative regulatory segment in the promoter of the TFIIIA gene, another developmentally regulated gene