Foreign Direct Investment, Financial Development and Economic Growth Evidence from Saudi Arabia
Bibliographic record
Abstract
This study is an effort to explain and establish a relationship among foreign direct investment, financial development and economic growth in Saudi Arabian context for the period of 1970 to 2015 by employing Vector Auto Regression (VAR) and modified Granger Casualty Models. The result of Johansen co-integration test illustrates that no long run co-integration can be established among the variables. VAR has established a link between economic growth, financial development and foreign direct investment. The Granger causality test also confirms that economic growth causes foreign direct investment and financial development which is a unidirectional causality running from economic growth towards foreign direct investment and financial development. No significant causality can be observed empirically between foreign direct investment and financial development. This feature can be attributed to the fact that Saudi Arabian economy is still heavily dependent on its oil resources which is the driving force behind growth. Impulse Response Function has been utilized in order to observe the response to the shocks among the variables.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".