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Abstract Details
Activity Number:
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618
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Type:
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Contributed
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Date/Time:
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Thursday, August 4, 2011 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Bayesian Statistical Science
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Abstract - #302154 |
Title:
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Bayesian Analysis of a Hierachical Stochastic Frontier Production Function
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Author(s):
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Seongho Song*+ and Younshik Chung and David Taesok Yi and Young-Suk Cho
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Companies:
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University of Cincinnati and Pusan National University and Xavier University and Pusan National University
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Address:
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Department of Mathematical Sciences , Cincinnati, OH, 45221-0025,
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Keywords:
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a hierarchical model ;
Stochastic Frontier Production Model ;
Technical Efficiency
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Abstract:
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A stochastic frontier production function has been considered in the case that there is the effects of non-negative technical inefficiency in the data. In the past decades, many studies have been discussed to determine the explanatory variables which affect the technical inefficiency effects in the stochastic frontier production function. We consider a hierarchical model of the stochastic frontier production function to investigate the data which has multiple hierarchical structures. It turns out that the proposed model naturally gives us the dependent covariance structure within a sub-group and the independent between sub-groups. We use Bayesian approach to estimate the model parameters in the model as well as the inefficiency model.
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Authors who are presenting talks have a * after their name.
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