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 | |
| Publication status | Published - 3 Oct 2019 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Conditional efficiency measures
- health expenditure
- non-parametric analysis
- probabilistic approach
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty
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