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    Understanding prediction intervals for firm specific inefficiency scores from parametric stochastic frontier models

    Access Status
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    Authors
    Wheat, P.
    Greene, William
    Smith, A.
    Date
    2014
    Type
    Journal Article
    
    Metadata
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    Citation
    Wheat, P. and Greene, W. and Smith, A. 2014. Understanding prediction intervals for firm specific inefficiency scores from parametric stochastic frontier models. Journal of Productivity Analysis. 42 (1): pp. 55-65.
    Source Title
    Journal of Productivity Analysis
    DOI
    10.1007/s11123-013-0346-y
    ISSN
    0895-562X
    School
    School of Economics and Finance
    URI
    http://hdl.handle.net/20.500.11937/53874
    Collection
    • Curtin Research Publications
    Abstract

    This paper makes two important contributions to the literature on prediction intervals for firm specific inefficiency estimates in cross sectional SFA models. Firstly, the existing intervals in the literature do not correspond to the minimum width intervals and in this paper we discuss how to compute such intervals and how they either include or exclude zero as a lower bound depending on where the probability mass of the distribution of $$ u_{i} |\varepsilon_{i} $$ui|ei resides. This has useful implications for practitioners and policy makers, with greatest reductions in interval width for the most efficient firms. Secondly, we propose an ‘asymptotic’ approach to incorporating parameter uncertainty into prediction intervals for firm specific inefficiency (given that in practice model parameters have to be estimated) as an alternative to the ‘bagging’ procedure suggested in Simar and Wilson (Econom Rev 29(1):62–98, 2010). The approach is computationally much simpler than the bagging approach.

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