Causality between Macroeconomic Indicators and Stock Market: An Econometric Analysis
Bibliographic record
Abstract
We attempt to examine the causality between economic growth and stock market performance of Pakistan for the years 1992M01-2012M12. For this purpose, the test devised by Granger (1988) has been employed. The results reveal a bi-directional causality between economic growth and stock market performance of Pakistan proxied by Karachi Stock Exchange capitalization (KSECAP). Once this bidirectional causality is established, a system of simultaneous equations has been specified and estimated by 2SLS to find the impact of economic growth and selected macroeconomic indicators on the stock market of Pakistan. The estimated results lead to the conclusion that economic growth affects the stock market of Pakistan and vice versa. The implications of the study are of paramount importance, especially for the emerging economies. Hence, bearing in mind the role of macroeconomic indicators in the performance of stock market a better policy can be formulated to enhance the growth of capital markets that in turn will increase the economic growth of emerging economies such as Pakistan and vice versa.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".