CENTRAL BANK AUTONOMY, LEGAL INSTITUTIONS AND BANKING CRISIS INCIDENCE
Bibliographic record
Abstract
ABSTRACT We examine whether the autonomy of a country's central bank (CB) reduces the probability of a banking crisis. We take a fine‐grained approach to CB autonomy by disentangling its various components as well. In addition, we look at the joint effects of CB autonomy and the legal tradition on the probability of a banking crisis in a country. Using the cross‐country data for CB independence for the period of 1980–1989, and both binary and ordered logit estimation models, this study finds that a country's CB with more autonomy in aggregate can lessen the probability of a banking crisis. When the CB's autonomy is disentangled with respect to its responsibilities, this study finds that the longer the tenure of the CB's chief executive officer, the lower the probability of a banking crisis. We also find that the probability of a banking crisis in the country is reduced even more if the relatively more autonomous CB can perform its duties in line with the country's stronger law‐and‐order tradition. We also carry out some counterfactual thought experiments along these lines. Copyright © 2011 John Wiley & Sons, Ltd.
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 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.006 | 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".