Marginal values and returns to scale for nonparametric production frontiers

We present a unifying linear programming approach to the calculation of various directional derivatives for a very large class of production frontiers of data envelopment analysis (DEA). Special cases of this include different marginal rates, the scale elasticity and a spectrum of partial and mixed elasticity measures. Our development applies to any polyhedral production technology including, to name a few, the conventional variable and constant returns-to-scale DEA technologies, their extensions with weight restrictions, technolo gies with weakly disposable undesirable outputs and network DEA models. Furthermore, our development provides a general method for the characterization of returns to scale (RTS) in any polyhedral technology. The new approach effectively removes the need to develop bespoke models for the RTS characterization and calculation of marginal rates and elasticity measures for each particular technology

Technical efficiency in electricity generation - the impact of smallness and isolation of island economies

Technical efficiency in electricity generation - the impact of smallness and isolation of island economie

A linear programming approach to efficiency evaluation in nonconvex metatechnologies

The notions of metatechnology and metafrontier arise in applications of data envelopment analysis (DEA) in which decision making units (DMUs) are not sufficiently homogeneous to be considered as operating in the same technology. In this case, DMUs are partitioned into different groups, each operating in the same technology. In contrast, the metatechnology includes all DMUs and represents all production possibilities that can in principle be achieved in different production environments. Often, the metatechnology cannot be assumed to be a convex set. In such cases benchmarking a DMU against the common metafrontier requires implementing either an enumeration algorithm and solving a linear program at each of its steps, or solving an equivalent mixed integer linear program. In this paper we show that the same task can be accomplished by solving a single linear program. We also show that its dual can be used for the returns-to-scale characterization of efficient DMUs on the metafrontier

A linear programming approach to efficiency evaluation in nonconvex metatechnologies

The notions of metatechnology and metafrontier arise in applications of data envelopment analysis (DEA) in which decision making units (DMUs) are not sufficiently homogeneous to be considered as operating in the same technology. In this case, DMUs are partitioned into different groups, each operating in the same technology. In contrast, the metatechnology includes all DMUs and represents all production possibilities that can in principle be achieved in different production environments. Often, the metatechnology cannot be assumed to be a convex set. In such cases benchmarking a DMU against the common metafrontier requires implementing either an enumeration algorithm and solving a linear program at each of its steps, or solving an equivalent mixed integer linear program. In this paper we show that the same task can be accomplished by solving a single linear program. We also show that its dual can be used for the returns-to-scale characterization of efficient DMUs on the metafrontier

Firm and Industry Level Profit Efficiency Analysis Under Incomplete Price Data: A Nonparametric Approach based on Absolute and Uniform Shadow Prices

We discuss the nonparametric approach to profit efficiency analysis at the firm and industry levels in the absence of complete price information, and propose two new insights. First, choosing one commodity (whose price is known) as a numeraire good enables us to measure profit inefficiency in absolute monetary terms. Second, imposing a ‘Law of One Price’ (LoOP) constraint that all firms should be evaluated in terms of the same input-output prices allows us to aggregate firm-level profit inefficiencies to the overall industry inefficiency. Moreover, the LoOP restrictions increase the discriminatory power of the method by better capturing firm-level allocative inefficiencies. Besides the measurement of profit losses, the presented approach enables one to recover absolute price information from quantity data. We conduct a series of Monte Carlo simulations to study the performance of the proposed approach in controlled production environments.Profit Efficiency, Industry Inefficiency, Data Envelopment Analysis, Absolute Prices, Law of One Price, Weight Restrictions, Simulation

Returns to scale in convex production technologies

The notion of returns to scale (RTS) is well-established in data envelopment analysis (DEA). In the variable returns-to-scale production technology, the RTS characterization is closely related to other scale characteristics, such as the scale elasticity, most productive scale size (MPSS), and global RTS types indicative of the direction to MPSS. In recent years, a number of alternative production technologies have been developed in the DEA literature. Most of these technologies are polyhedral, and hence are closed and convex sets. Examples include technologies with weakly disposable undesirable outputs, models with weight restrictions and production trade-offs, technologies that include several component production processes, and network DEA models. For most of these technologies, the relationship between RTS and other scale characteristics has remained unexplored. The theoretical results obtained in this paper establish such relationships for a very large class of closed convex technologies, of which polyhedral technologies are an important example

The Tale of Two research Communities: The Diffusion of Research on Productive Efficiency

The field of theoretical and applied efficiency analysis is pursued both by economists and people from operational research and management science. Each group tends to cite a different paper as the seminal one. Recent availability of extensive electronically accessible databases of journal articles makes studies of the diffusion of papers through citations possible. Research strands inspired by the seminal paper within economics are identified and followed by citation analysis during the 20 year period before the operations research paper was published. The first decade of the operations research paper is studied in a similar way and emerging differences in diffusion patterns are pointed out. Main factors influencing citations apart from the quality of the research contribution are reputation of journal, reputation of author, number of close followers; colleagues, “cadres of protégés”, Ph.D. students, and extent of network (“invisible college”). Such factors are revealed by the citing papers. In spite of increasing cross contacts between economics and operations research the last decades co-citation analysis reveals a relative constant tendency to stick to “own camp” references.Farrell efficiency measures, data envelopment analysis, DEA, bibliometry

Using data envelopment analysis for the efficiency and elasticity evaluation of agricultural farms

Data Envelopment Analysis (DEA) is a well-established relative efficiency measurement technique, which has been widely applied to evaluate the technical efficiency of agricultural units in different countries by focusing on different aspects of agricultural production. This research deals with the evaluation of efficiency through DEA in non-homogeneous agricultural production, where units produce a wide range of different outputs. The objectives are threefold. Firstly, we propose a novel methodological approach of integrating the production trade-offs concept of DEA into non-homogeneous agricultural efficiency evaluation to prevent the overstatement of the efficiency of specialist farms and overcome the issue of insufficient discrimination due to large number of outputs in the models. Secondly, we aim to integrate this methodological perspective to the theory of elasticity measurement on DEA frontiers. The efficient frontiers of DEA are not defined in functional forms as in the classical economic theory, therefore obtaining elasticity measures on them require different considerations. We introduce the production trade-offs to the elasticity measurement and derive the necessary models to calculate the elasticities of response in the presence of production trade-offs. As a third objective, before moving to the introduction of the trade-offs in elasticity measurement, for theoretical completeness, we first consider the elasticity measurement on DEA frontiers of constant returns-to-scale (CRS) technologies. Our proposed methodology and all the developed elasticity theory are illustrated in a real world case of Turkish agricultural sectors. We provide extensive empirical applications covering all the proposed theory and methodology. Among the results of this research, we provide an elasticity measurement framework, which enables us to calculate elasticities of response measures in both VRS and CRS technologies, with or without production tradeoffs included. We observe that the integration of production trade-offs provide better discrimination of efficiency scores compared to the models without trade-offs included. We also investigate how changing production trade-offs affect the efficiency and elasticity measures of the evaluated units