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Record W3121240670 · doi:10.1016/j.rfe.2004.08.004

Interest rate smoothing and financial stability

2004· article· en· W3121240670 on OpenAlexaff
R. Todd Smith, Henry van Egteren

Bibliographic record

VenueReview of Financial Economics · 2004
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBanking stability, regulation, efficiency
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsInterest rateEconomicsInsolvencyMonetary economicsMoral hazardMonetary policyNet interest marginFinanceCapital adequacy ratioIncentiveMicroeconomics

Abstract

fetched live from OpenAlex

Abstract Central banks smooth fluctuations in interest rates based on a belief that this policy promotes financial stability. This belief is based on a presumption that the direct effect of less interest rate volatility on a bank's likelihood of insolvency is the predominant effect of this policy. The main point of this paper is that these policies also give rise to indirect effects that lower financial stability. These indirect effects occur because the policy itself alters bank behavior. In effect, if the central bank provides (liquidity) insurance (at zero premia), it may introduce a classic moral hazard problem that encourages risk taking by banks. As a result, to maintain a given degree of financial stability, a bank regulator may, in fact, need to impose a higher prudential capital requirement when an interest rate smoothing policy is in place. The paper concludes that the link between interest rate smoothing policy and financial stability may be more complicated than is generally recognized.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.034
GPT teacher head0.239
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations15
Published2004
Admission routes1
Has abstractyes

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