Institutional Dimension of Investment Profile, Natural Resources & Foreign Direct Investments: A Case of MENA Oil Producing Countries
Bibliographic record
Abstract
The economic development of countries depends on the flow of foreign direct investment. The natural resources are responsible for maximum attraction of FDI in MENA countries. The study has aimed to examine the impact of institutional dimension of investment profile and natural resources on the flow of foreign direct investment in MENA countries. The study has included 17 MENA countries for the generation of incomplete and unbalanced panel data for the years 1960-2012. The study has considered FDI as dependent variable; while, the independent variables include location dimension, institutional dimension, new theory trade, and other economic determinants. The basic dunning OLI paradigm is combined with different variables; and the results were compared with previous studies. The flow of FDI in MENA countries is affected by different natural resources. The application of resource curse to FDI flow in MENA countries represents the negative correlation between energy endowment and FDI flow. The results showed that oils rents are not statistically significant. Moreover, investment profile and oil relative production were negatively correlated. The importance of natural resources and FDI determinants in MENA countries has been determined in the present study.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".