Democracy in the neighborhood and foreign direct investment
Bibliographic record
Abstract
Abstract The determinants of foreign direct investment (FDI) have been extensively studied. Even though there is extensive research in the area, most of it is based on analyzing the effects of host country characteristics on FDI flows, and yet there is little research on how neighboring country characteristics play a role in facilitating FDI flows to host countries. This paper analyzes the association between the democracy level in neighboring countries and FDI flows to host countries. Using bilateral FDI flows from the OECD countries, with a large host country sample, we find that countries surrounded by democratic countries attract higher FDI flows. Furthermore, we find evidence that countries that are surrounded by neighboring countries with good institutions tend themselves to have better institutions, experience lower civil conflict, and have higher political stability and hence indirectly attract higher FDI flows. Our findings suggest that if neighboring countries act in such way as to become more democratic, FDI flows to these countries would be higher since not only does improving the quality of democracy attract more FDI inflows, but also being surrounded by neighboring advanced democratic countries will also lead to higher FDI flows to them.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".