Combining the Beveridge and the Phillips Curve into an Integrative Model: The Modified Output Gap
Bibliographic record
Abstract
We present a new theoretical concept: modified output gap (MOG), based on the Phillips and on the Beveridge curve. Both of these pillars are derived analytically and combined with each other, revealing the explicit positive relationship between the vacancy ratio and the inflation rate. It is shown how a deterioration in the matching process on the labor market leads to shifts in both curves, but also in the MOG. This indicates that a loss in the efficiency of matching in the labor market, when combined with an increase of the demand in the markets for goods will push up inflation. As a result, a sort of second ¡°policy ineffectiveness lemma¡± emerges: at high levels of mismatch, expansive measures of monetary and/or fiscal policies will lead to higher inflation in the first place with little (positive) repercussions on the real side of the economy.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".