Value And Quantity Data In Economic And Technical Efficiency Measurement
This paper calls attention to the implications of using cost or revenue data in efficiency measurement through Data Envelopment Analysis (DEA). In many empirical settings this issue arises, since frequently input and/or output quantities or prices are not available, and only value measures are available. When value data are used in technical efficiency models it is clearly questionable what sort of efficiency measure is being computed, since it cannot be a productive efficiency measure (that takes into account only quantities of inputs and outputs), and it cannot be either a traditional cost or revenue efficiency measure (that considers prices of factors disagregated from quantities). In this paper we call the attention for this fact and address situations where only value data are available, and situations where for some inputs (outputs) there is quantity information and for others there is value information. The main contribution of this paper is a reconciliation of previous literature on analysing these issues and on providing some guidelines on what to do and not do, when these issues arise in a data set.
|Date of creation:||Sep 2013|
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- Subhash C. Ray & Lei Chen & Kankana Mukherjee, 2008.
"Input Price Variation Across Locations and a Generalized Measure of Cost Efficiency,"
2008-11, University of Connecticut, Department of Economics.
- Ray, Subhash C. & Chen, Lei & Mukherjee, Kankana, 2008. "Input price variation across locations and a generalized measure of cost efficiency," International Journal of Production Economics, Elsevier, vol. 116(2), pages 208-218, December.
- Portela, Maria Conceição A. Silva & Thanassoulis, Emmanuel, 2014. "Economic efficiency when prices are not fixed: disentangling quantity and price efficiency," Omega, Elsevier, vol. 47(C), pages 36-44.
- Rolf Fare & Valentin Zelenyuk, 2002. "Input aggregation and technical efficiency," Applied Economics Letters, Taylor & Francis Journals, vol. 9(10), pages 635-636.
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