Event-specific Data Envelopment Models and Efficiency Analysis

Robert G. Chambers, Atakelty Hailu and John Quiggin

No 151185, Risk and Sustainable Management Group Working Papers from University of Queensland, School of Economics

Abstract: Most, if not all, production technologies are stochastic. This article demonstrates how data envelopment analysis (DEA) methods can be adapted to accommodate stochastic elements in a state-contingent setting. Specifically, we show how observations on a random input, not under the control of the producer and not known at the time that variable input decisions are made, can be used to partition the state space in a fashion that permits DEA models to approximate an event-specific production technology. The approach proposed in this article uses observed data on random inputs and is easy to implement. After developing the event-specific DEA representation, we apply it to a data set for Western Australian wheat farmers. Our results highlight the need for acknowledging stochastic elements in efficiency analysis.

Keywords: Production Economics; Research and Development/Tech Change/Emerging Technologies (search for similar items in EconPapers)
Pages: 21
Date: 2005
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https://ageconsearch.umn.edu/record/151185/files/WPR07_08.pdf (application/pdf)

Related works:
Journal Article: Event-specific data envelopment models and efficiency analysis (2011)
Journal Article: Event‐specific data envelopment models and efficiency analysis (2011)
Working Paper: Event-specific Data Envelopment Models and Efficiency Analysis (2007)
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Persistent link: https://EconPapers.repec.org/RePEc:ags:uqsers:151185

DOI: 10.22004/ag.econ.151185

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