Relationship between FDI and Economic Growth in Selected Asian Countries: A Panel Data Analysis
Bibliographic record
Abstract
This study examines empirically the relationship between FDI and economic growth using heterogeneous panel for the period 1983-2008. The empirical findings of Larsson panel co-integration show that FDI and economic growth are cointegrated. FMOLS results reveal that FDI and economic growth are positively related to each other. The results of panel homogeneous causality hypothesis show the existence of bi-directional causality between FDI and economic growth while the results of panel homogeneous non-causality hypothesis confirm the existence of unidirectional causality running from FDI to economic growth in selected panel. The results of heterogeneous causality hypothesis show the existence of bi-directional causality between FDI and economic growth only in case of Malaysia. The existence of uni-directional causality running from FDI to economic growth is observed in cases of Nepal, Singapore, Japan and Thailand whereas the uni-directional causality is also found running from economic growth to FDI for Pakistan, Bangladesh and Sri Lanka. However, no causality in any direction is found in cases of India, Maldives, Indonesia, China, Philippines, Korea Dem and Singapore.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".