Event-specific data envelopment models and efficiency analysis

Robert G. Chambers, Atakelty Hailu and John Quiggin

Australian Journal of Agricultural and Resource Economics, 2011, vol. 55, issue 01, 17

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 barley production data. Our results highlight the need for acknowledging stochastic elements in efficiency analysis.

Keywords: Research and Development/Tech Change/Emerging Technologies; Research Methods/ Statistical Methods; Risk and Uncertainty (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (12)

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Related works:
Journal Article: Event‐specific data envelopment models and efficiency analysis (2011)
Working Paper: Event-specific Data Envelopment Models and Efficiency Analysis (2007)
Working Paper: Event-specific Data Envelopment Models and Efficiency Analysis (2005)
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Persistent link: https://EconPapers.repec.org/RePEc:ags:aareaj:176734

DOI: 10.22004/ag.econ.176734

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