Inflation, taxes, and the coordination of monetary and fiscal policy by use of a game of chicken
Bibliographic record
Abstract
In this study some of the consequences of an uncertain policy struggle (‘game of chicken’) between independent taxing agencies (a monetary and a fiscal authority) are examined. We show that policy uncertainty may improve upon regimes where there is no uncertainty and one agency succeeds in implementing a low‐tax policy at the expense of the other agency. An uncertain tax policy never dominates a fully coordinated tax policy, but it can move average tax rates in the right direction. In this sense, the game of chicken between agencies can be beneficial and can compensate for the lack of a specific coordinating administration. (JEL Classification: E61) Inflation, fiscalité et la coordination des politiques fiscale et monétaire par l'utilisation du ‘jeu du premier qui se dégonfle.’ Cette étude examine certaines conséquences d'un combat politique incertain (jeu du premier qui se dégonfle) entre des agences indépendantes de taxation (une autorité monétaire et une autorité fiscale). On montre que l'incertitude politique peut constituer un régime qui fait mieux que des régimes où il n\'y a pas d'incertitude et où une agence réussit à mettre en place une politique de faible imposition au dépens de l'autre agence. Une politique de taxation incertaine ne domine jamais une politique de taxation pleinement coordonnée, mais elle peut déplacer les taux moyen d'imposition dans la bonne direction. En ce sens, le \′jeu du premier qui se dégonfle\' entre agences peut être bénéfique et peut compenser pour le manque de coordination spécifiquement gérée.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".