Does Foreign Direct Investment Lead to Economic Growth? Evidences from Asian Developing Countries
Bibliographic record
Abstract
The study about the interrelationship between FDI and economic growth in the host country is one of the hottest discussions. Some of the studies have evidence and consider FDI as the growth driver and some others don’t. This study attempted to scrutinize the causal association of FDI with GDP in Indonesia, India, Malaysia and Bangladesh for the years of 1990 to 2014. Cointegration test has been applied in this study which shows that there is a long-term interrelationship within FDI and economic growth and then applied the Granger causality (GC) test which is based on the VECM. The short run results show that there are no evidence of causality direction from FDI to GDP and vice versa, whereas the long run results show that there is a positive impact of FDI and other variables to the GDP but not significant, and from GDP and other variables to FDI there is a negative interrelationship but significant. The results show the ambiguous interrelationship between FDI and economic growth.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".