Reexamining the Effect of Democratic Institutions on Inflows of Foreign Direct Investment in Developing Countries
Bibliographic record
Abstract
The effect of regime type on inflows of foreign direct investment (FDI) remains a matter of controversy. While some studies report a positive influence of democracy on FDI, others show a negative influence. This study reexamines this discrepancy using pooled panel data during the past 20 years and contributes to the existing literature in three ways. First, it refines the causal mechanisms underlying the democracy-related arguments of veto players, audience costs, and democratic hindrance with respect to foreign investment. Second, it introduces three accurate measures to capture each of those three causal arguments. Third, it briefly demonstrates how different measurements of the dependent variable can produce statistically spurious results. The empirical results reveal that democratic institutions are, at best, weakly associated with increases in FDI inflows (measured by FDI/GDP ratios). While multiple veto players (and, counterintuitively, democratic hindrance) may be positively associated with increases in FDI, audience costs are not linked to FDI activities. These findings have important policy implications given that developing democratic countries are trying to attract more FDI in order to achieve their economic growth and development targets.
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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 | 0.008 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".