Degree of Financial Development and Economic Growth in Qatar: Cointegration and Causality Analysis
Bibliographic record
Abstract
Utilizing the cointegration technique and Granger causality test based on the Error Correction Model (ECM), this study empirically investigates the long-run relationship and the direction of causality between the financial development and economic growth in Qatar over the period 1990–2012. The financial development is measured by three alternative indicators: a broad money supply (M2) to GDP ratio, bank credit to the private sector as ratio to GDP, and domestic credit provided by bank sector as ratio to GDP. The economic growth is measured by the growth rate of real GDP. The results suggest that a positive long-run equilibrium relationship exists between all three financial development indicators and the growth rate of real GDP. The causality test results indicate that in the long-run, there is a bidirectional causal relationship between the broad money supply to the GDP ratio and the growth rate of real GDP as well as a unidirectional causality, which runs from domestic credit provided by the bank sector as a percentage of GDP to the growth rate of real GDP. However, a causality relationship does not exist between bank credits to the private sector ratio to GDP and economic growth. In the short-run, the findings show a unidirectional causality running from the growth rate of real GDP to domestic credit provided by the banking sector. However, no causal relationship between the growth rate of real GDP and the other two financial development indicators has been found.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".