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    An Information Theoretic Approach to Flexible Stochastic Frontier Models

    Miller, Douglas J.
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    [PDF] InformationTheoreticApproach.pdf (188.1Kb)
    Date
    2007
    Format
    Working Paper
    Metadata
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    Abstract
    Parametric stochastic frontier models have a long history in applied production economics, but the class of tractible parametric models is relatively small. Consequently, researchers have recently considered non-parametric alternatives such as kernel den- sity estimators, functional approximations, and data envelopment analysis (DEA). The purpose of this paper is to present an information theoretic approach to constructing more flexible classes of parametric stochastic frontier models. Further, the proposed class of models nests all of the commonly used parametric methods as special cases, and the proposed modeling framework provides a comprehensive means to conduct model specification tests. The modeling framework is also extended to develop information theoretic measures of mean technical efficiency and to construct a profile likelihood estimator of the stochastic frontier model.
    URI
    http://hdl.handle.net/10355/2559
    Part of
    Working papers (Department of Economics);WP 07-17
    Part of
    Economics publications
    Citation
    Department of Economics, 2007
    Rights
    OpenAccess.
    This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License.
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    • Economics publications (MU)

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