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Record W2790544120 · doi:10.5539/ibr.v11n5p18

Determinants of Bank Profitability in the Euro Area: What Has Changed During the Recent Financial Crisis?

2018· article· en· W2790544120 on OpenAlexvenueno aff
Simone Rossi, Mariarosa Borroni, Andrea Lippi, Mariacristina Piva

Bibliographic record

VenueInternational Business Research · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBanking stability, regulation, efficiency
Canadian institutionsnot available
Fundersnot available
KeywordsProfitability indexCapitalizationPanel dataFinancial crisisLeverage (statistics)EconomicsFinancial systemMonetary economicsBusinessFinancePortfolioMacroeconomicsEconometrics

Abstract

fetched live from OpenAlex

During the recent financial crisis, bank profitability has become an element of strong concern for regulators and policymakers; in fact both self-financing strategies and capital increases – necessary to provide higher level of capitalization – rely on the ability of a bank to generate profits. However, the determinants of bank profitability, that seemed to be unequivocally identified by previous literature, appear to have changed under the effect of regulatory and competitive dynamics. We test this hypothesis on commercial, cooperative and saving banks, employing a random effect panel regression on a dataset comprising bank-level data and macroeconomic information (covering the period 2006-2013) for 9 countries of the Euro area. Our findings suggest that, after a period of “irrational exuberance” in which credit growth and high leverage were seen as proper and fast ways to boost profitability, a sound financial structure and a wiser and objective credit portfolio management have become the main drivers to ensure higher returns.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.017
Threshold uncertainty score0.552

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.126
GPT teacher head0.344
Teacher spread0.218 · 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 teacher head, 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
Published2018
Admission routes1
Has abstractyes

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