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Record W3142195563 · doi:10.1093/rof/rfab009

The Strategic Response of Banks to Macroprudential Policies: Evidence from Mortgage Stress Tests in Canada*

2021· article· en· W3142195563 on OpenAlexaffabout
Robert Clark, Shaoteng Li

Bibliographic record

VenueEuropean Finance Review · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsQueen's University
Fundersnot available
KeywordsMortgage underwritingIntermediaryPaymentBusinessGovernment (linguistics)Monetary economicsInterest rateMortgage insuranceShared appreciation mortgageFinancial crisisFinancial systemSecondary mortgage marketEconomicsFinanceMacroeconomics

Abstract

fetched live from OpenAlex

Abstract Following the crisis, macroprudential regulations targeting mortgage-market vulnerabilities were widely adopted, their success often relying on the response of financial intermediaries. We provide evidence from Canada suggesting banks may have behaved strategically to limit the effectiveness of recently implemented mortgage stress tests. Before implementation, borrowers had to prove they could make mortgage payments based on the interest rate specified in the contract. The new tests require borrowers to show they can afford payments based on a typically higher qualifying rate, derived from the mode of 5-year rates posted by the six largest banks. The government’s objective was to cool credit markets, but, since many mortgages are government-insured, the big banks’ interests were not aligned. We find evidence of rate manipulation using a difference-in-differences approach comparing changes in spreads for 5-year mortgages with 3-year spreads, unaffected by the policy. The qualifying rates were lowered encouraging continued borrowing, muting the tests’ impact.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.342
Threshold uncertainty score0.833

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.056
GPT teacher head0.254
Teacher spread0.198 · 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

Citations11
Published2021
Admission routes2
Has abstractyes

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