Bibliographic record
Abstract
The study tries to recognize the macroeconomic variables responsible for inflation in Bahrain during the period 1980-2010. For this purpose, co-integration test were used in the empirical analysis. Using Augmented Dickey-Fuller (ADF) Phillips Perron (PP) tests, the variables of the study revealed to be integrated of the order one 1(1) at first difference. Cointegration test was used to state the existence or otherwise of a cointegrating vector in the variables. Trace and Maximum Eigen test value point out co-integration at 5% level of significance pointing to the fact that the variables have a long-run relationship. The paper found that inflation in the short-run is effected by M2, GEXP, and WACPI supporting the long run analysis. The signs of NEER and IR are not as expected. The error correction term is negative and significant at 1%, so the model is stable and supporting the Co-integration results. The variance decompositions (VDs) approach is used to capture the relative importance of various shocks and their influences on our variable of inflation. The relative variance of inflation is due the exchange rate and interest rate. The results show that shocks to the CPI itself, Nominal Effective Exchange Rate NEER, Nominal Interest Rate NIR, M2, Government Expenditure GEXP, and Consumer Price Index of Main Partners WACPI over all horizons.
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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 | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".