A Re-Appraisal of the Role of Monetary Policy: The Quantity Theory of Money through a Structural Vector Autoregressive Approach
Bibliographic record
Abstract
The COVID-19 pandemic, the Russia–Ukraine and the Israel–Hamas conflicts, and the resulting global economic shocks will affect the world economy for several years. This paper analyzes and discusses monetary finance (MF) using the Quantity Theory of Money (QTM) to understand economic dynamics. To achieve this goal, we utilize a Structural Vector Autoregressive (SVAR) identification scheme with sign restrictions on datasets from advanced economies. The findings indicate that monetary growth plays a role in short-term inflationary dynamics, while its effects are less significant in the medium to long term. The aim of the paper is to contribute to ongoing debate surrounding the potential strategies for addressing the economic downturn through the reintroduction of monetary finance (MF).
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".