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

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  • Stavros Kourtzidis
  • Panayiotis Tzeremes
  • Nickolaos G. Tzeremes

Abstract

By using the probabilistic framework of production efficiency, the paper develops time-dependent 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.

Suggested Citation

  • Stavros Kourtzidis & Panayiotis Tzeremes & Nickolaos G. Tzeremes, 2019. "Conditional time-dependent nonparametric estimators with an application to healthcare production function," Journal of Applied Statistics, Taylor & Francis Journals, vol. 46(13), pages 2481-2490, October.
    • Handle: RePEc:taf:japsta:v:46:y:2019:i:13:p:2481-2490
    DOI: 10.1080/02664763.2019.1588234
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    Cited by:

    1. Cordero, Jose Manuel & Polo, Cristina & Simancas, Rosa, 2022. "Assessing the efficiency of secondary schools: Evidence from OECD countries participating in PISA 2015," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    2. Pablo Daniel Monterubbianesi & Mara Leticia Rojas & Carlos Darío Dabús, 2021. "Education and Health: Evidence of Threshold Effects on Economic Growth," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 94, pages 195-231, Enero-Jun.

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