Economic, social and institutional determinants of FDI inflows: A comparative analysis of developed and developing economies
Bibliographic record
Abstract
This paper investigates the determinants of Foreign Direct Investment (FDI) inflows by classifying determinants into economic, social, and institutional categories, and examines its linkage between FDI in developed and developing economies at an aggregate level. Countries are distinguished in accordance with country income level, and each category is constructed as a composite index by utilizing the Principal Component Analysis (PCA) method. Using annual data from 1996 to 2019 and panel data approaches, the determinants of FDI are investigated for 178 countries. Main findings are, first, developing economies are largely dependent on economic indicators to attract FDI. Second, in the case of developed economies, the role of social indicators on FDI inflows is shown relatively more significant than economic indicators. Finally, the linkage between institutional indicators and FDI inflows is weak and statistically insignificant in both developed and developing economies.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".