Does Stock Market Performance Affect Economic Growth? Empirical Evidence from Saudi Arabia
Bibliographic record
Abstract
This research paper investigates the impact of stock prices on real economic activity in the Saudi Arabian economy. We utilize various econometric techniques – Johansen and Juselius’s (1990) cointegration tests and Granger’s (1969) causality test – to assess such a relationship, based on quarterly observations spanning the period from the first quarter of 2010 to the fourth quarter of 2018. Our empirical evidence indicates the presence of a significant cointegrating relationship between the two variables being examined; in other words, stock prices have a significant impact on real economic growth. Specifically, the estimated long-run relationship reveals that a 1 percent increase in stock prices would boost economic growth by 0.32 percent. In addition, the error correction model suggests that when the economy deviates from its steady state condition, it needs about a year and a half to return to its equilibrium condition. Lastly, this paper applies the most common Granger causality test, which confirms the essential role of stock prices in predicting changes in economic growth.
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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 | 0.005 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".