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Record W3005521681

Water in the Wine? Monetary Policy and the Impact of Non-bank Financial Intermediaries

2020· article· en· W3005521681 on OpenAlex
Wendy Wu, Jeremy Kronick

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueC.D. Howe Institute Commentary · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBanking stability, regulation, efficiency
Canadian institutionsnot available
Fundersnot available
KeywordsFinancial intermediaryFinancial systemBusinessFinancial crisisIntermediationLoanMonetary policyBank runMonetary economicsDeposit insuranceFinancial sectorFinanceEconomicsMarket liquidityMacroeconomics
DOInot available

Abstract

fetched live from OpenAlex

Canada was lauded for surviving the 2007-08 global financial crisis relatively unscathed. In part, this was due to the success of our financial services sector. This resilience, especially in contrast to the US banking sector, is partly explained by the smaller size of the non-bank financial intermediation (NBFI) sector in Canada – more popularly known as “shadow banking.” But signs of robust growth in Canada’s NBFI sector after the crisis suggest this resilience might be under threat. The assets of those institutions engaged in non-bank financial intermediation have continued to grow in Canada since the global financial crisis, and now account for a larger share of total financial assets than prior to the crisis. A more important NBFI sector has multiple effects on the financial system and on the economy. On the one hand, intermediaries in the sector, or NBFIs, provide alternatives for both depositors and borrowers that improve the functioning of the economy by increasing competition. On the other hand, they also might increase vulnerabilities, since they are often not as closely regulated, and deposit insurance does not cover their liabilities. We find that, as NBFI deposit growth increases in importance, it can dilute the effectiveness of monetary policy. This drag might be the result of depositors shifting between NBFIs and traditional banks, an effect that is exacerbated as the NBFI sector grows. We also find that contractionary monetary policy causes an increase in business credit growth for NBFIs and a fall in chartered bank business loan growth. Although the overall effect on business credit growth is the desired decrease, the increase in NBFI business loans both decreases monetary policy effectiveness and results in a riskier composition. Lastly, we find the insignificant effect on overall mortgage credit growth following a contractionary monetary policy shock appears to be driven by a shift of credit from traditional banks to NBFIs, and could be a concern from a financial stability perspective. Overall, these results highlight the importance of a growing NBFI sector for monetary policy and financial stability. Our findings suggest that both the traditional monetary policy tool of the overnight rate and tightening mortgage underwriting standards through macroprudential policy might have the unintended side effect of increasing financial instability. One way to reduce this potential side effect is to limit the migration of loans between traditional banks and NBFIs by tightening regulation of NBFIs to level the playing field between the two types of financial institutions. At a minimum, the systemically important NBFIs should face capital requirements and underwriting standards similar to those imposed on traditional banks. We hope these results help the Bank of Canada as it continues to evaluate and model the evolution of monetary policy transmission in the Canadian economy. To that end, NBFIs should be front and centre when the four coordinating bodies that provide systemic financial services oversight next meet.

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.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.180
Threshold uncertainty score0.540

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.244
Teacher spread0.224 · 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