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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/119862


    Title: A hierarchical panel data stochastic frontier model for the estimation of stochastic metafrontiers
    Authors: Christine Amsler;Yi Yi Chen;Peter Schimdt;Hung Jen Wang
    Keywords: Stochastic frontier;Panel data;Hierarchical model;Metafrontier;Inefficiency
    Date: 2020-08-19
    Issue Date: 2021-01-21 12:10:15 (UTC+8)
    Publisher: Springer-Verlag GmbH Germany, part of Springer Nature 2020
    Abstract: This paper proposes a stochastic frontiermodel with three composed errors, and therefore
    six error components. As in the metafrontier literature, firms belong to groups
    with a group-specific frontier. A firm has a level of short-run and long-run inefficiency
    relative to its group-specific frontier, as in existing models with two composed errors
    and four error components. But now there is also a group-specific inefficiency, that
    is, a shortfall of the group-specific frontier from the best practice metafrontier. The
    paper shows how to estimate this model and how to extract predictions of the various
    inefficiencies.
    Relation: Empirical Economics 60, p.53–363
    DOI: 10.1007/s00181-020-01929-w
    Appears in Collections:[Graduate Institute & Department of Economics] Journal Article

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