Properties of inefficiency indexes on 〈input, output〉 space

Russell, R. Robert; Schworm, William

doi:10.1007/s11123-011-0209-3

Cited by 42 publications

(20 citation statements)

References 29 publications

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“…It is worth noticing that there are no clear indications in the literature which values of directional vector should be applied, and the choice of directional vector is usually considered a matter of convenience. Our choice of directional vector obeys Russell and Schworm's () recommendation to choose a directional vector that is positive and has the same units as those of a production vector . We further compute the difference between static and dynamic measures, which could be relevant to evaluate the importance of adjustment costs on different inefficiency components in the Polish meat‐processing industry.…”

Section: Resultsmentioning

confidence: 99%

Dynamic versus static inefficiency assessment of the Polish meat‐processing industry in the aftermath of the European Union integration and financial crisis

Kapelko

2017

Agribusiness

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This paper assesses the dynamic inefficiency of the Polish meatprocessing industry during the period between 2004 and 2012. This study employs also a comparison of dynamic with static inefficiency measures to address the importance of accounting for adjustment costs when measuring a firm's inefficiency. Dynamic and static cost inefficiencies and their decomposition into technical, allocative, and scale inefficiency are derived using Data Envelopment Analysis (DEA). Results show that firms' low levels of dynamic cost inefficiency are mainly due to dynamic allocative inefficiency rather than technical and scale inefficiency. The 2008 financial crisis appears to hamper firms' dynamic technical performance, but has also a positive influence on the dynamic allocative and scale inefficiencies. We further show that the average static measures tend to underestimate all inefficiency components compared to dynamic counterparts. [EconLit citations: C61, D61, L66].

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Section: Resultsmentioning

confidence: 99%

Dynamic versus static inefficiency assessment of the Polish meat‐processing industry in the aftermath of the European Union integration and financial crisis

Kapelko

2017

Agribusiness

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“…33 Many (in)efficiency indexes have been proposed in the literature. 34 In empirical work on pollution-generating technologies, however, HYP and DDF are among the more widely used of these conventional indexes. Given the above problems with these two indexes under the BP approach, we propose, in the next subsection, a modification of another conventional efficiency index that is better behaved for use in measuring efficiency on BP production technologies.…”

Section: Inadequacies Of Conventional Efficiency Indexes For the By-pmentioning

confidence: 99%

“…33 See Appendix posted on the Journal's online repository of supplementary material, accessible at http://www.aere.org/journals/, for a further discussion of this problem in the context of Example 1. 34 See Russell and Schworm [34] for an analysis of these indexes and their properties. 35 This feature is attributable to the fact that the Färe-Grosskopf-Lovell index involves a maximal contraction/expansion of all inputs/outputs in coordinate-wise directions (rather than in a maximal radial or hyperbolic direction).…”

Section: A Proposed Efficiency Index For By-production Technologies: mentioning

confidence: 99%

On modeling pollution-generating technologies

Murty

Russell

Levkoff

2012

Journal of Environmental Economics and Management

405

343

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a b s t r a c tWe argue analytically that many commonly used models of pollution-generating technologies, which treat pollution as a freely disposable input or as a weakly disposable and nulljoint output, may generate unacceptable implications for the trade-offs among inputs, outputs, and pollution. We show that the correct trade-offs in production are best captured if a pollution-generating technology is modeled as an intersection of an intendedproduction technology of the firm and nature's residual-generation set. The former satisfies standard disposability properties, while the latter violates free (strong) disposability of pollution and pollution-causing inputs. As a result, the intersection-which we call a byproduction technology-violates standard free disposability of pollution and pollutioncausing inputs. Employing data envelopment analysis on an electric-power-plant database, we illustrate shortcomings, under by-production, of two popular efficiency indexes: the hyperbolic and directional-distance-function indexes. We propose and implement an alternative index with superior properties. Under by-production, most efficiency indexes decompose very naturally into intended-production and environmental efficiency indexes. This decomposition is difficult to find under alternative specifications of pollutiongenerating technologies.

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“…However, the shortage function measures potential efficiency improvements in all dimensions. Russell and Schworm (2011) recently took a look at similar efficiency measures in production theory and prudently conclude that the shortage function with a proportional interpretation satisfies a stronger unit invariance property compared to the case of a fixed direction. Furthermore, as may be clear from the above description so far, the traditional distance functions analysed in this axiomatic literature do not normally adhere to the mathematical notion of a norm.…”

Section: Introductionmentioning

confidence: 99%

Benchmarking mean-variance portfolios using a shortage function: the choice of direction vector affects rankings!

Kerstens

Mounir

Woestyne³

2012

Journal of the Operational Research Society

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In addition to its use in data envelopment analysis models, the shortage function has been proposed as a tool to gauge performance in multi-moment portfolio models. An open issue is how the choice of direction vector affects the efficiency measurement, especially when some of the data can be negative and, from a practical point of view, whether and how the resulting league tables are affected. This paper illustrates empirically how the choice of direction vector affects the relative ranking of mean-variance portfolios. This result is relevant to all frontier-based applications, especially those where some of the data can be naturally negative.

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Properties of inefficiency indexes on 〈input, output〉 space

Abstract: Technical efficiency indexes, Technical efficiency axioms, C43, C61, D24,

Cited by 42 publications

References 29 publications

Dynamic versus static inefficiency assessment of the Polish meat‐processing industry in the aftermath of the European Union integration and financial crisis

Dynamic versus static inefficiency assessment of the Polish meat‐processing industry in the aftermath of the European Union integration and financial crisis

On modeling pollution-generating technologies

Benchmarking mean-variance portfolios using a shortage function: the choice of direction vector affects rankings!

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