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Dependence modeling in stochastic frontier analysis

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    SYSNO ASEP0559340
    Document TypeJ - Journal Article
    R&D Document TypeJournal Article
    Subsidiary JČlánek ve WOS
    TitleDependence modeling in stochastic frontier analysis
    Author(s) Mamonov, Mikhail (NHU-C)
    Parmeter, C. F. (US)
    Prokhorov, A. (RU)
    Source TitleDependence Modeling. - : Walter de Gruyter - ISSN 2300-2298
    Roč. 10, č. 1 (2022), s. 123-144
    Number of pages22 s.
    Languageeng - English
    CountryPL - Poland
    Keywordsefficiency ; productivity ; panel data
    Subject RIVAH - Economics
    OECD categoryApplied Economics, Econometrics
    Method of publishingOpen access
    Institutional supportNHU-C - Cooperatio-COOP
    UT WOS000799191000003
    EID SCOPUS85131005963
    DOI10.1515/demo-2022-0107
    AnnotationThis review covers several of the core methodological and empirical developments surrounding stochastic frontier models that incorporate various new forms of dependence. Such models apply naturally to panels where cross-sectional observations on firm productivity correlate over time, but also in situations where various components of the error structure correlate between each other and with input variables. Ignoring such dependence patterns is known to lead to severe biases in the estimates of production functions and to incorrect inference.
    WorkplaceEconomics Institute - CERGE
    ContactTomáš Pavela, pavela@cerge-ei.cz, Tel.: 224 005 122
    Year of Publishing2023
    Electronic addresshttps://doi.org/10.1515/demo-2022-0107
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