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

Stavros Kourtzidis; Panayiotis Tzeremes; Nickolaos Tzeremes

doi:10.1080/02664763.2019.1588234

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

Stavros Kourtzidis, Panayiotis Tzeremes, Nickolaos Tzeremes

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

154 Downloads (Pure)

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 language	English
Pages (from-to)	2481-2490
Number of pages	10
Journal	Journal of Applied Statistics
Volume	46
Issue number	13
Early online date	8 Mar 2019
DOIs	https://doi.org/10.1080/02664763.2019.1588234
Publication status	Published - 3 Oct 2019

Keywords

Conditional efficiency measures
health expenditure
non-parametric analysis
probabilistic approach

ASJC Scopus subject areas

Statistics and Probability
Statistics, Probability and Uncertainty

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1080/02664763.2019.1588234

Author Accepted ManuscriptAccepted author manuscript, 702 KB

Cite this

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AU - Tzeremes, Nickolaos

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

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

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