Investigate the Long-Run Trade-Off between Inflation and Unemployment in Egypt
Bibliographic record
Abstract
The main objective of this study is to investigate the long run trade-off between unemployment and inflation in Egypt through the period (1974-2011) using Johansen-Juselius (1990) cointegration test and Vector Error Correction Model (VECM). Results of ADF test indicate that both series are cointegrated of order one I(1). Add to that, the outcomes of cointegration analysis confirm a positive relationship between changes in inflation rate and unemployment gap in the long run, which is consistent with “Locus Critique” where a policy of inflation would fail to reduce the unemployment rate in the long run, because workers would eventually adjust their expectations of inflation. Results of the ECM have illustrated that the error-correction term is negative and significant with an adjustment coefficient of - 0.280, pointing out that changes in inflation rate adjust to its equilibrium level in the long run with 28% of the adjustment taking place within the first year.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".