Published by Canadian Center of Science and Education 119 What Drives Inflation in MENA Countries?
Bibliographic record
Abstract
This paper assesses the impact of both monetary and non-monetary determinants of inflation for a sample of 8 MENA countries over the period 1980-2009. We carried out different model estimations to examine the impact of five mainstream variable groups on inflation namely structural, business-cycle-related, openness-related and external and monetary variables. To control for robustness of our results, we used alternative estimation techniques, mainly system GMM. Estimation results report strong evidence on the existence of persistent inflation dynamics in these countries. With regards to the world inflation and nominal effective exchange rate, they produce significant and positive effects on inflation. Our empirical findings also report a negative effect of the output gap on inflation. The effect produced by government spending is however surprisingly negative. A last set of regressions suggests a potential explanation for this result: the effect produced by the output gap reflects the effects of both fiscal and monetary policy on inflation. That is a decrease in government spending over a long period enhances growth, reduces the output gap and generates inflation, whereas an increase in money supply produces inflation by enhancing growth and reducing the output gap.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.411 | 0.113 |
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".