Exploring the Linkages Among Economic Growth, Openness, Income Inequality, Education and Health in Pakistan
Bibliographic record
Abstract
The present study is an attempt to investigate empirical linkages among economic growth, openness, income inequality, education and health in Pakistan during 1974-2009 by using annual time series data. Phillips-Perron (PP) unit root test is utilized to check stationarity of the variables. Long-run relationship is confirmed through Johansen and Juselius cointegration test. VECM is proposed to check short-run and long-run dynamics. Toda-Yamamoto causality test is utilized for observing the causality. Diagnostic tests are utilized to confirm the validity of the model. The results support strong positive impact of openness of trade, education and health on economic growth in the long-run whereas income inequality is negatively associated with economic growth. The study finds significant five uni-directional causalities and two bi-directional causalities among variables. For achieving higher economic growth in Pakistan attention must be directed towards decisive economic policies related to liberalizing trade, provision of education and health facilities and to reduce income inequality. JEL Classification: F43, F13, I19, I29 Key words: Economic Growth; Openness; Income Inequality; Education; Health
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".