In search of spatial interdependence of <scp>US</scp> outbound <scp>FDI</scp> in the <scp>MENA</scp> region
Why this work is in the frame
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Bibliographic record
Abstract
Abstract The paper investigates the spatial interdependence of US MNE investments in the MENA region. Given the variations in resource endowments, governance structures and degree of infrastructure availability in MENA countries, one would expect these variables to affect an MNE 's choice of FDI location. We do find that domestic non‐spatial factors such as own country inflation and governance measured by bureaucratic quality as well as infrastructure affect a host country's inward FDI . We also found that only one measure of natural resource endowment; that is, oil and gas exports were instrumental in attracting FDI . This non‐spatial result is generally robust and invariant to the two methodologies employed in this study, that is the spatially autoregressive ( SAR ) model and the spatial Durbin model ( SDM ). We found that neighbouring countries’ infrastructure availability measured either by “electricity used” or “energy used” affected FDI inflows in a host country. However, this spatial impact was found only in the SDM model. The spatial effects of neighbouring countries’ economic and political conditions and resource endowments were, however, not observed on a host country's inward FDI . The insignificance of both the surrounding market potential and the spatially weighted FDI suggests a purely horizontal motive of MNE investments in the MENA region.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it