Pooled Mean Group Approach to Test the Determinants of Financial Integration: Evidence From OECD and G20 Countries
Bibliographic record
Abstract
This study investigates the role of financial liberalization, trade integration, economic growth and global financial crisis on financial integration level of selected OECD and G20 countries during the period of 2000-2016. PMG technique has been implemented to estimate the ARDL model. Regression results suggest a statistically significant long run co-integration relationship between financial integration and independent variables. Analysis also concludes that there are both long run and short run positive impact of trade integration level on financial integration level. The study also concludes that the global financial crisis has had a negative influence on global financial integration both in the short run and long run. But according to the regression results the impact of financial liberalization on the actual financial integration level of the countries only appears in the long run. Results also indicate that positive impact of economic growth on financial globalization level appears only in the long run.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".