Long-Run Relationship between Exports and Imports of Pakistan
Bibliographic record
Abstract
The present study investigates dynamic relationship between exports and imports of Pakistan by using fiscal year data from1948-49 to 2012-13. ARDL co-integration technique has been employed to estimate the relationship and from empirical results, it is concluded that exports and imports are indeed co-integrated or in other words, long run equilibrium relationship does exist between exports and imports of Pakistan. It is further concluded that Pakistan is not violating its international budget constraints. VECM estimation also confirms that exports and imports are co-integrated and coefficient of error correction term indicates that in case of any departure from equilibrium exports adjust back at the speed of 17.147 percent of its last year disequilibrium value and it takes 5.832 years to fade away any impact caused by short term trade imbalances. Results obtained by Toda and Yamamoto (1995) test indicate that bi-directional causal relationship also exists between exports and imports of Pakistan. Findings of the current study has very important implications for policy makers to design such macroeconomic policies that can lead to establish long run equilibrium relationship between exports and imports adjusting short term trade deficit shocks to avoid violation of international budget constraints.
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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 | 0.001 |
| 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 | 0.000 |
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".