Progressing from Uncertainty to Risk for DEA-Based Decisions
We demonstrate a methodology for estimating, with a specified probability, the interval within which the true DEA efficiency of an individual Decision Making Unit occurs. With this procedure, decisions based on DEA scores are made under conditions of risk, as opposed to the current practice in which...
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2012
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Online Access: | http://hdl.handle.net/10986/5180 |
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okr-10986-51802021-04-23T14:02:21Z Progressing from Uncertainty to Risk for DEA-Based Decisions Barnum, D. T. Gleason, J. M. Hemily, B. Lin, Justin Yifu Wang, P. We demonstrate a methodology for estimating, with a specified probability, the interval within which the true DEA efficiency of an individual Decision Making Unit occurs. With this procedure, decisions based on DEA scores are made under conditions of risk, as opposed to the current practice in which decisions are made under uncertainty. The method applies statistical Panel Data Analysis (PDA), which provides proven and powerful methodologies for diagnostic testing of residuals and estimation of confidence intervals. Using PDA, we demonstrate, with a sample of real-world data, that DEA score residuals sometimes are independent and Normally distributed, and estimate confidence intervals based on these validated assumptions. Then, using another sample of real-world data in which violations of these assumptions do occur, we demonstrate well-known PDA Generalized Least Squares statistical models that account for the violations in the estimation of confidence intervals. Journal of the Operational Research Society (2010) 61, 1548-1555. doi:10.1057/jors.2009.120 Published online 28 October 2009 2012-03-30T07:31:41Z 2012-03-30T07:31:41Z 2010 Journal Article Journal of the Operational Research Society 0160-5682 http://hdl.handle.net/10986/5180 EN http://creativecommons.org/licenses/by-nc-nd/3.0/igo World Bank Journal Article |
repository_type |
Digital Repository |
institution_category |
Foreign Institution |
institution |
Digital Repositories |
building |
World Bank Open Knowledge Repository |
collection |
World Bank |
language |
EN |
relation |
http://creativecommons.org/licenses/by-nc-nd/3.0/igo |
description |
We demonstrate a methodology for estimating, with a specified probability, the interval within which the true DEA efficiency of an individual Decision Making Unit occurs. With this procedure, decisions based on DEA scores are made under conditions of risk, as opposed to the current practice in which decisions are made under uncertainty. The method applies statistical Panel Data Analysis (PDA), which provides proven and powerful methodologies for diagnostic testing of residuals and estimation of confidence intervals. Using PDA, we demonstrate, with a sample of real-world data, that DEA score residuals sometimes are independent and Normally distributed, and estimate confidence intervals based on these validated assumptions. Then, using another sample of real-world data in which violations of these assumptions do occur, we demonstrate well-known PDA Generalized Least Squares statistical models that account for the violations in the estimation of confidence intervals. Journal of the Operational Research Society (2010) 61, 1548-1555. doi:10.1057/jors.2009.120 Published online 28 October 2009 |
format |
Journal Article |
author |
Barnum, D. T. Gleason, J. M. Hemily, B. Lin, Justin Yifu Wang, P. |
spellingShingle |
Barnum, D. T. Gleason, J. M. Hemily, B. Lin, Justin Yifu Wang, P. Progressing from Uncertainty to Risk for DEA-Based Decisions |
author_facet |
Barnum, D. T. Gleason, J. M. Hemily, B. Lin, Justin Yifu Wang, P. |
author_sort |
Barnum, D. T. |
title |
Progressing from Uncertainty to Risk for DEA-Based Decisions |
title_short |
Progressing from Uncertainty to Risk for DEA-Based Decisions |
title_full |
Progressing from Uncertainty to Risk for DEA-Based Decisions |
title_fullStr |
Progressing from Uncertainty to Risk for DEA-Based Decisions |
title_full_unstemmed |
Progressing from Uncertainty to Risk for DEA-Based Decisions |
title_sort |
progressing from uncertainty to risk for dea-based decisions |
publishDate |
2012 |
url |
http://hdl.handle.net/10986/5180 |
_version_ |
1764394231494868992 |