On the optimal size of bilateral investment treaty network in foreign direct investment flows
Bibliographic record
Abstract
Purpose The aim of this paper first is to go beyond the static effects of bilateral investment treaties (BITs) and empirically estimate the marginal effects of the stock of BITs on foreign direct investment flows. Design/methodology/approach These statistical models use a gravity equation. Findings This paper finds that BITs is subject to diminishing returns measured in terms of FDI flows. Diminishing returns are more pronounced among country-pairs that have not signed BITs but have their own BIT network than among country-pairs with their own BITs. Research limitations/implications The subsidiary finding is that a measure of a country’s BIT network characteristic, capturing conditions favorable for a mix of horizontally and vertically integrated activities, may be the limiting force underlying the diminishing returns of the stock of BITs. Originality/value For a given country’s BIT network, a multinational enterprise finds more value in investing where a bilateral treaty is in place. This suggests either stronger property-rights protection or greater latitude to use the host country as an export platform.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".