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Record W1501689787 · doi:10.34989/sdp-2010-15

Has the Inclusion of Forward-Looking Statements in Monetary Policy Communications Made the Bank of Canada More Transparent?

2021· preprint· en· W1501689787 on OpenAlexaffabout
Christine Fay, Toni Gravelle

Bibliographic record

VenueEconstor (Econstor) · 2021
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsBank of Canada
Fundersnot available
KeywordsTransparency (behavior)Monetary policyFinancial inclusionForward guidanceBusinessInclusion (mineral)Financial systemEconomicsBank rateAccountingInflation targetingCentral bankMonetary economicsFinanceCredit channelFinancial servicesPolitical science

Abstract

fetched live from OpenAlex

To investigate the extent to which the transparency of the Bank of Canada's monetary policy has improved, the authors examine empirically – over the period 30 October 2000 to 31 May 2007 – the reaction of Canadian financial markets to official Bank communications, and in particular their reaction to the recent inclusion of forward-looking policy-rate guidance in these communications. The authors find evidence that fixed announcement date (FAD) press releases, and, to a lesser extent, speeches by Governing Council members, significantly affect near-term interest rate expectations, indicating that central bank communication conveys important information to market participants. However, the authors' results also show that FAD press releases and speeches do not significantly impact market rates over the more recent period, when forward-looking statements have been used on a regular basis. The authors investigate two explanations for this change in response: (i) market participants better understand the Bank's monetary policy reaction function as they become accustomed to the FAD regime; or, (ii) market participants focus more on the forward-looking statements and less on the Bank's discussion of the economic outlook, and therefore respond less than before to new macroeconomic data releases. The authors find evidence to support the second explanation: forward-looking statements – even though they have been designed to be conditional – have made the Bank's decisions on the policy rate more predictable, but not necessarily more transparent.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.242
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.002
Research integrity0.0000.001
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 head0.073
GPT teacher head0.277
Teacher spread0.204 · 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.

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

Citations9
Published2021
Admission routes2
Has abstractyes

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