Comparative Analysis of Causality and Cointegration Relations Between Stock Market and Economic Growth in G7 and BRICS Countries and Turkey
Bibliographic record
Abstract
The economic growth in a country isgenerally measured by a change in the Gross Domestic Product (GDP). Theincrease in GDP will also increase per capita national income and personalsavings. The increase in the national income will also increase individuals'available income, their savings and the share of their savings on investments.Hence, GDP is one of the most important indicators considered by investors. Inthis study, it was attempted to test the relationship between these twovariables and the findings of previous studies. For this purpose, therelationships between GDPs and stock markets of the BRICS and G7 countries fromthe 1st quarter of 1998 to 4th quarter of 2016 were examined. The Johansencointegration test and the Granger Causality test were used to determine theexistence of a relationship. As a result of the analyzes made, one-wayrelations from stock indices to GDP were found. At the same time, the seriesare moving together in the long run. Therefore, the increase in stock prices isaccompanied by 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 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 | 0.001 |
| 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".