Culture and Monetary Policy Effectiveness
Bibliographic record
Abstract
Monetary policy, typically set by a nation’s central bank, mainly focuses on managing \nprice stability and encouraging economic growth. Arguably, this means that in shaping its \nmonetary policy, a central bank also influences the behavior of its country’s residents. In this \ncontext, we investigate if differing cultural and societal behaviors could make a central bank’s job \neasier or more challenging. Specifically, we use five of the six dimensions of national culture from \nGeert Hofstede and information on a country’s political, legal, and institutional framework to \nexamine whether a country’s cultural and/or institutional environment affects the efficiency of its \nmonetary policy, as reflected in both price stability and economic growth. Our findings suggest \nthat culture and societal behavior indeed play a role in how effective a country’s monetary policy \ncan be. For instance, we find that countries with high Power Distance and Individualism tend to \nbe less efficient, whereas societies with more Indulgence tend to be more efficient. Additionally, \nour research supports previous findings regarding the positive effect of inflation-targeting on \nmonetary policy efficiency.
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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 | 0.003 | 0.021 |
| 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 | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".