Inequality, inflation, and central bank independence
Bibliographic record
Abstract
What can account for the different contemporaneous inflation experiences of various countries, and of the same country over time? We present an analysis of the determination of inflation from a political economy perspective. We document a positive correlation between income inequality and inflation and then present a theory of the determination of inflation outcomes in democratic societies that illustrates how greater inequality leads to greater inflation, owing to a desire by voters for wealth redistribution. We conclude by showing that democracies with more independent central banks tend to have better inflation outcomes for a given degree of inequality. JEL Classification E5, H0 Inégalité, inflation et l'indépendance de la banque centrale. Quels sont les facteurs qui pourraient expliquer les expériences inflationnistes tellement différentes des divers pays dans le passé récent, et l'expérience tellement différente d'un pays donné dans le temps? Les auteurs analysent ce problème de la détermination du taux d'inflation dans une perspective d'économie politique. Ils déterminent qu'il y a une corrélation positive entre l'inégalité et l'inflation, et présentent une théorie de la détermination de l'inflation dans les sociétés démocratiques qui montre comment une inégalité plus grande entraîne une inflation plus grande à cause du désir des électeurs de demander une redistribution de la richesse. Le mémoire montre en terminant que les démocraties e´quipées de banques centrales plus indépendantes tendent à avoir de meilleurs résultats en terme d'inflation pour un degré d'inégalité donné.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".