Conditional time-dependent nonparametric estimators with an application to healthcare production function

Stavros Kourtzidis, Panayiotis Tzeremes, Nickolaos Tzeremes

    Research output: Contribution to journalArticle

    Abstract

    By using the probabilistic framework of production efficiency, the paper develops timedependent conditional efficiency estimators performing a non-parametric frontier analysis. Specifically, by applying both full and quantile (robust) time-dependent conditional estimators, it models the dynamic effect of health expenditure on countries’ technological change and technological catch-up levels. The results from the application reveal that the effect of per capita health expenditure on countries’ technological change and technological catch-up is nonlinear and is subject to countries’ specific income levels.
    Original languageEnglish
    Pages (from-to)2481-2490
    Number of pages10
    JournalJournal of Applied Statistics
    Volume46
    Issue number13
    Early online date8 Mar 2019
    DOIs
    Publication statusPublished - 3 Oct 2019

    Fingerprint

    Technological Change
    Production Function
    Nonparametric Estimator
    Healthcare
    Health
    Estimator
    Quantile
    Health expenditures
    Production function
    Technological catch-up
    Technological change
    Model
    Framework
    Income level
    Nonparametric frontier
    Frontier analysis
    Production efficiency
    Dynamic effects

    Keywords

    • Conditional efficiency measures
    • health expenditure
    • non-parametric analysis
    • probabilistic approach

    Cite this

    @article{8442e0c4e6674b1cb6f996636bac1187,
    title = "Conditional time-dependent nonparametric estimators with an application to healthcare production function",
    abstract = "By using the probabilistic framework of production efficiency, the paper develops timedependent conditional efficiency estimators performing a non-parametric frontier analysis. Specifically, by applying both full and quantile (robust) time-dependent conditional estimators, it models the dynamic effect of health expenditure on countries’ technological change and technological catch-up levels. The results from the application reveal that the effect of per capita health expenditure on countries’ technological change and technological catch-up is nonlinear and is subject to countries’ specific income levels.",
    keywords = "Conditional efficiency measures, health expenditure, non-parametric analysis, probabilistic approach",
    author = "Stavros Kourtzidis and Panayiotis Tzeremes and Nickolaos Tzeremes",
    year = "2019",
    month = "10",
    day = "3",
    doi = "10.1080/02664763.2019.1588234",
    language = "English",
    volume = "46",
    pages = "2481--2490",
    journal = "Journal of Applied Statistics",
    issn = "0266-4763",
    publisher = "Routledge",
    number = "13",

    }

    Conditional time-dependent nonparametric estimators with an application to healthcare production function. / Kourtzidis, Stavros; Tzeremes, Panayiotis; Tzeremes, Nickolaos.

    In: Journal of Applied Statistics, Vol. 46, No. 13, 03.10.2019, p. 2481-2490.

    Research output: Contribution to journalArticle

    TY - JOUR

    T1 - Conditional time-dependent nonparametric estimators with an application to healthcare production function

    AU - Kourtzidis, Stavros

    AU - Tzeremes, Panayiotis

    AU - Tzeremes, Nickolaos

    PY - 2019/10/3

    Y1 - 2019/10/3

    N2 - By using the probabilistic framework of production efficiency, the paper develops timedependent conditional efficiency estimators performing a non-parametric frontier analysis. Specifically, by applying both full and quantile (robust) time-dependent conditional estimators, it models the dynamic effect of health expenditure on countries’ technological change and technological catch-up levels. The results from the application reveal that the effect of per capita health expenditure on countries’ technological change and technological catch-up is nonlinear and is subject to countries’ specific income levels.

    AB - By using the probabilistic framework of production efficiency, the paper develops timedependent conditional efficiency estimators performing a non-parametric frontier analysis. Specifically, by applying both full and quantile (robust) time-dependent conditional estimators, it models the dynamic effect of health expenditure on countries’ technological change and technological catch-up levels. The results from the application reveal that the effect of per capita health expenditure on countries’ technological change and technological catch-up is nonlinear and is subject to countries’ specific income levels.

    KW - Conditional efficiency measures

    KW - health expenditure

    KW - non-parametric analysis

    KW - probabilistic approach

    UR - http://www.scopus.com/inward/record.url?scp=85062796831&partnerID=8YFLogxK

    U2 - 10.1080/02664763.2019.1588234

    DO - 10.1080/02664763.2019.1588234

    M3 - Article

    VL - 46

    SP - 2481

    EP - 2490

    JO - Journal of Applied Statistics

    JF - Journal of Applied Statistics

    SN - 0266-4763

    IS - 13

    ER -