An Analysis of the Relationship between Crude Oil Prices, Current Account Deficit and Exchange Rates: Turkish Experiment
Bibliographic record
Abstract
In this study, the effect of raw oil prices and exchange rates on current account deficit of the Turkish Economy has been examined by investigating the short and long run relationship between the current account deficit of the Turkish Economy, raw oil prices (Brent oil prices) and exchange rates (USD/TRY). The Monthly Data between December 1991 and January 2016 were used in the study. The relationships between the variables were tested with the VAR (Vector Auto Regressive) Model. None of the series was found stable after the unit root tests, but it was observed that all the variables became stable when their first differences were taken. Firstly, an unrestricted VAR model was built to determine the long term relationship between the variables. After the long term relationship was found between the variables, the VECM (Vector Error Correction) Model was estimated in order to determine the short term relationship. A mutual granger causality relationship is detected between crude oil prices and current account deficit variables. No causality relationship is found between the other variables.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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".