Determinants of Exchange Rate: A Case Study of Pakistan
Bibliographic record
Abstract
The present research was conducted to study the impact of macro-economic variables on index value of currency. The main objective of this research was to investigate some major factors having their contribution towards influencing exchange rate of Pakistan. For this purpose, time series monthly data on five macro-economic variables, i.e. Inflation rate, KIBOR, Forex Reserves, Exports and Imports of Pakistan was collected for the period of 2001-2015. Correlation and Regression analysis techniques were used to analyze the relationship between criterion and predictor variables. Study divulged that Inflation rate; exports and imports remained significant and have their major contribution towards influencing currency rates in Pakistan. On the other hand, Forex reserves and KIBOR confirmed moderate relationship with exchange rate. Multiple regression analysis confirmed that inflation rate, KIBOR and exports have positive association while imports and Forex reserves demonstrated negative association with exchange rate.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".