Data Envelopment Analysis in Environmental Valuation: Environmental Performance, Eco-efficiency and Cost-Benefit Analysis

Data Envelopment Analysis (DEA) is a linear programming based method for evaluating performance of comparable production units such as firms. Although the method is already extensively applied in many areas of economics, its use in environmental economics and related fields remains limited. The purpose of this paper is to present basic principles of DEA and evaluate its application possibilities for a range of environmental valuation problems. We show how DEA has to be adjusted to the context of environmental performance, eco-efficiency and Cost-Benefit analysis (CBA). By modifying the traditional DEA framework to the specific features and purposes of environmental application we show that the valuation principles to which DEA is based on can offer useful insights and complement the conventional toolbox of environmental economists in valuation of the environmental services in general.

[1]  R. Färe.  Derivation of Shadow Prices for Undesirable Outputs: A Distance Function Approach , 1993 .

[2]  Rolf Färe,et al.  Productivity of the U.S. Agricultural Sector: The Case of Undesirable Outputs , 2001 .

[3]  R. Dyson,et al.  Reducing Weight Flexibility in Data Envelopment Analysis , 1988 .

[4]  Atakelty Hailu,et al.  Pollution abatement and productivity performance of regional Canadian pulp and paper industries , 2003 .

[5]  Daniel Tyteca,et al.  Linear Programming Models for the Measurement of Environmental Performance of Firms—Concepts and Empirical Results , 1997 .

[6]  Daniel Tyteca,et al.  On the Measurement of the Environmental Performance of Firms— A Literature Review and a Productive Efficiency Perspective , 1996 .

[7]  R. Shepherd.  Theory of cost and production functions , 1970 .

[8]  Katrin Allen,et al.  DEA in the ecological context- An overview• , 1999 .

[9]  Emmanuel Thanassoulis,et al.  Weights restrictions and value judgements in Data Envelopment Analysis: Evolution, development and future directions , 1997, Ann. Oper. Res..

[10]  R. Shephard.  Cost and production functions , 1953 .

[11]  Harald Dyckhoff,et al.  Measuring ecological efficiency with data envelopment analysis (DEA) , 2001, Eur. J. Oper. Res..

[12]  O. H. Brownlee,et al.  ACTIVITY ANALYSIS OF PRODUCTION AND ALLOCATION , 1952 .

[13]  Kingsley E. Haynes,et al.  Toward a pollution abatement monitoring policy: Measurements, model mechanics, and data requirements , 1994 .

[14]  G. Dantzig.  Programming of Interdependent Activities: II Mathematical Model , 1949 .

[15]  Isabelle Piot-Lepetit,et al.  Agriculture's environmental externalities: DEA evidence for French agriculture , 1997 .

[16]  Timothy Coelli,et al.  An Introduction to Efficiency and Productivity Analysis , 1997 .

[17]  C.A.K. Lovell,et al.  Multilateral Productivity Comparisons When Some Outputs are Undesirable: A Nonparametric Approach , 1989 .

[18]  Agapi Somwaru,et al.  Incorporating undesirable outputs into models of production: an application to United States agriculture , 1994 .

[19]  Marie-Paule Kestemont,et al.  Assessing the economic and environmental performance of municipal solid waste collection and sorting programmes , 1998 .

[20]  Rolf Färe,et al.  Environmental regulation and profitability: An application to Swedish pulp and paper mills , 1995 .

[21]  Suthathip Yaisawarng,et al.  The Effects of Sulfur Dioxide Controls on Productivity Change in the U.S. Electric Power Industry , 1994 .

[22]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .

[23]  M. Farrell.  The Measurement of Productive Efficiency , 1957 .

[24]  R. Färe,et al.  An activity analysis model of the environmental performance of firms—application to fossil-fuel-fired electric utilities , 1996 .

[25]  A. Hailu,et al.  Non‐Parametric Productivity Analysis with Undesirable Outputs: An Application to the Canadian Pulp and Paper Industry , 2001 .

[26]  C. A. Knox Lovell,et al.  Environmental efficiency with multiple environmentally detrimental variables; estimated with SFA and DEA , 2000, Eur. J. Oper. Res..

[27]  John Maleyeff,et al.  Quantitative Models for Performance Evaluation and Benchmarking: DEA with Spreadsheets and DEA Excel Solver , 2005 .

[28]  Francisco Pedraja-Chaparro,et al.  On the Role of Weight Restrictions in Data Envelopment Analysis , 1997 .