Convergence of Health Expenditure in OECD Countries: Evidence from a Nonlinear Asymmetric Heterogeneous Panel Unit Root Test
Bibliographic record
Abstract
This paper examines the convergence in health expenditure across 22 OECD countries between 1980 and 2012 by implementing panel unit root tests. Contribution of application of the nonlinear asymmetric heterogeneous panel unit root test is twofold. Firstly, it relaxes the assumption of cross-sectional dependency in panel data. Secondly, it incorporates the asymmetric nonlinear mean reversion in a panel setting. Results show that while the conventional panel unit root test cannot reject the null hypothesis of a unit root in relative per capita health expenditures for the whole set of countries, both the symmetric and the asymmetric nonlinear panel unit root tests indicate the stationarity of the panel. Specifically, almost 23 percent of the countries are found to be converging by employing the nonlinear asymmetric panel unit root test. In addition, introducing asymmetric structure helps to uncover additional converging countries which cannot be detected using linear and nonlinear symmetric panel unit root tests.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".