Multi-Product Marginal Productivity of Efficient Frontiers in Data Envelopment Analysis

37 Pages Posted: 4 Mar 2013

See all articles by Chia-Yen Lee

Chia-Yen Lee

National Cheng Kung University

Date Written: March 3, 2013

Abstract

Differential characteristics of the production function represent elasticity measures and marginal rates of production technologies. We extend the study by Podinovski and Førsund (2010) and develop multi-product marginal productivity (MP) by showing a consistent estimation of MP generated by data envelopment analysis (DEA), convex nonparametric least squares (CNLS), and directional distance function (DDF). Based on multi-product MP, a meta-DEA approach is developed to address finding the improving direction of the efficient firm on the frontier towards the allocatively efficient benchmarks for marginal profit maximization. This approach, which emphasizes “planning” over “evaluation” and focus on “margin” than “level”, forms the basis for transforming a typical “ex-post” DEA into a novel “ex-ante” DEA study. Two case studies show that the proposed model provides an explicit span of multi-product MP for productivity improvement via a tradeoff between distinct directions.

Keywords: data envelopment analysis, directional distance function, marginal productivity, nondifferentiable characteristics, marginal profit maximization

Suggested Citation

Lee, Chia-Yen, Multi-Product Marginal Productivity of Efficient Frontiers in Data Envelopment Analysis (March 3, 2013). Available at SSRN: https://ssrn.com/abstract=2227565 or http://dx.doi.org/10.2139/ssrn.2227565

Chia-Yen Lee (Contact Author)

National Cheng Kung University ( email )

No.1, University Road
Tainan
Taiwan

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