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Record W3112716718 · doi:10.5430/ijba.v12n1p9

Does Unconventional Monetary Policy Affect Bank Profitability in the Euro Area?

2020· article· en· W3112716718 on OpenAlexvenueno aff
Paolo Agnese, Paolo Capuano

Bibliographic record

VenueInternational Journal of Business Administration · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEuropean Monetary and Fiscal Policies
Canadian institutionsnot available
Fundersnot available
KeywordsProfitability indexNet interest marginReturn on assetsEconomicsMonetary policyMonetary economicsReturn on equityInterest rateEquity (law)Forward guidanceMargin (machine learning)FinanceCredit channelInflation targetingComputer science

Abstract

fetched live from OpenAlex

This paper investigates the impact of unconventional monetary policy (UMP) on bank profitability in the euro area, over the period 2007-2019.In particular, through multiple regression models, we analyze the relationship between the UMP variables (Longer-term refinancing operations and Securities held for monetary policy purposes) and the main bank profitability variables used in the literature (Return on average equity, Return on average assets and Net interest margin).This work is original compared to recent studies on the subject as it considers the impact of UMP expressed in terms of volumes rather than in terms of interest rates on bank profitability variables.Our results suggest that the UMP adopted by the Eurosystem over the period considered is negatively associated with bank profitability expressed by the Return on average equity and the Return on average asset. By contrast, monetary policy measures do not seem to have had any effect on the Net interest margin.

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)0.001
metaresearch head score (Gemma)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
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 science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.046
GPT teacher head0.258
Teacher spread0.213 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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