MétaCan
Menu
Back to cohort
Record W1019872509 · doi:10.34989/swp-2015-10

Effects of Funding Portfolios on the Credit Supply of Canadian Banks

2021· preprint· en· W1019872509 on OpenAlexaffabout
H. Evren Damar, Césaire Meh, Yaz Terajima

Bibliographic record

VenueEconstor (Econstor) · 2021
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicBanking stability, regulation, efficiency
Canadian institutionsBank of Canada
Fundersnot available
KeywordsPolitical scienceEconomicsHumanitiesFinancial systemBusinessPhilosophy

Abstract

fetched live from OpenAlex

This paper studies how banks simultaneously manage the two sides of their balance sheet and its implications for bank risk taking and real economic activity. First, we analyze how changes in funding affect the supply of bank loans. We then examine how the supply of credit by banks that rely more on wholesale funding changed during periods of low-for-long interest rates and during the recent financial crisis. The findings suggest that contemporaneous changes in wholesale funding are positively associated with large business loans. In addition, we find that banks that rely on wholesale funding tend to increase mortgage loans in a prolonged low rate environment. This is suggestive evidence that these banks may be taking on more liquidity risk by supplying long-term loans with short-term funding. We also find that mortgage lending by banks relying more on wholesale funding increased, a likely result of government policies to increase liquidity in the market during the crisis.

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)0.014
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 score0.092
Threshold uncertainty score0.185

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.020
GPT teacher head0.214
Teacher spread0.194 · 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

Citations2
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueEconstor (Econstor)Same topicBanking stability, regulation, efficiencyFrench-language works237,207