International Productivity Differences and the Roles of Domestic Investment, FDI and Trade
Bibliographic record
Abstract
This paper calculates Theil's entropy index to measure the extent of productivity differences across 92 countries for the period from 1970 to 2003. While there is evidence of increasing differences in productivity across these countries, we observe different patterns when we group the countries by income levels. These differences seem to be decreasing among middle income developing and developed countries, whereas they seem to be widening among low and high income developing countries. The results of our multivariate time series analysis also suggest that FDI increases productivity differences among low and high income developing countries, whereas GDI reduces these differences among low income countries in the long-run. Granger causality test results indicate that while an increase in GDI leads to a decline in growth of trade, a higher growth of trade appears to be important for attracting FDI to middle income countries. Furthermore, a reduction in productivity differences and a higher FDI growth lead to higher growth of trade in developed countries.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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 source (direct Gemma or distilled Codex), 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".