On Price Efficiency

Färe, Rolf; Grosskopf, Shawna; Nelson, Julianne

doi:10.2307/2527170

Cited by 37 publications

(19 citation statements)

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“…In that case a shadow price approach can be followed, i.e. basically those prices are selected that are 'most favorable' to the observation under evaluation (see, e.g., Färe, Grosskopf and Nelson (1990)). …”

Section: Measuring Shadow Cost and Profit Inefficiencymentioning

confidence: 99%

“…This benefit of the doubt idea also gives the economic intuition behind (24) and (26). First, for any price vector under which actual (and maximum) profit is positive, the maximum netput scale expansion (within CM (S)) gives the minimum proportional profit expansion (compare with (24)).…”

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confidence: 96%

“…First, for any price vector under which actual (and maximum) profit is positive, the maximum netput scale expansion (within CM (S)) gives the minimum proportional profit expansion (compare with (24)). Similarly, if actual (and maximum) profit is negative, then reducing netput scale to a certain degree (within CM (S)) always reduces the profit loss to the same degree (compare with (26)). 14 Since we do not know the actual prices, we need to consider both scenarios, and the benefit-of-the-doubt idea suggests selecting the most favorable scenario (see (21) 14 Observe that the benefit of the doubt principle calls for selecting prices that yield actual and maximal profit with the same sign, as this guarantees the profit efficiency measure to be non-negative.…”

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confidence: 99%

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The economic meaning of Data Envelopment Analysis: A ‘behavioral’ perspective

Cherchye

Rock

Hennebel

2014

Socio-Economic Planning Sciences

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We reconsider the motivation of Data Envelopment Analysis (DEA), the non-parametric technique that is widely employed for analyzing productive efficiency in academia, the private sector and the public sector. We first argue that the conventional engineering motivation of DEA can be problematic since it often builds on unverifiable production axioms. We then provide a dual viewpoint and highlight the 'behavioral' interpretation of DEA models.We start from a specification of the production objectives while imposing minimal structure on the production possibilities, and construct tools to meaningfully quantify deviations of observed producer behavior from optimizing behavior. This brings to light the economic meaning of DEA, provides guidelines for selecting the appropriate model in practical research settings, and prepares the ground for instituting new DEA models. We hope that our insights will contribute to the further dissemination of DEA, and stimulate public sector applications of DEA that build on its behavioral interpretation.JEL Classification: C14, C61, D21, D24.

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Section: Measuring Shadow Cost and Profit Inefficiencymentioning

confidence: 99%

mentioning

confidence: 96%

mentioning

confidence: 99%

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The economic meaning of Data Envelopment Analysis: A ‘behavioral’ perspective

Cherchye

Rock

Hennebel

2014

Socio-Economic Planning Sciences

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“…In addition to its original use in efficiency measurement, DEA is also employed for approximating production possibility sets or input/output correspondences (see Färe and Grosskopf (1995)), recovering shadow prices (see Färe, Grosskopf and Nelson (1990)), providing best-practice benchmarks (e.g. Bogetoft and Hougaard (1999)), as monitoring tool in agency problems (Bogetoft (1994)), and as a "lazy man's decision support tool" (Doyle (1995)).…”

Section: Introductionmentioning

confidence: 99%

DEA with efficiency classification preserving conditional convexity

Kuosmanen¹

2001

European Journal of Operational Research

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“…Färe et al (1990) presented the idea of absolute shadow price in the context of price efficiency, but did not utilize it for efficiency measurement.…”

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confidence: 99%