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Record W1583249874 · doi:10.34989/swp-2009-29

Exchange Rate Pass-through and Monetary Policy: How Strong is the Link?

2021· preprint· en· W1583249874 on OpenAlexaffabout
Stephen Murchison

Bibliographic record

VenueEconstor (Econstor) · 2021
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsBank of Canada
Fundersnot available
KeywordsEconomicsHumanitiesMonetary policyExchange ratePolitical scienceKeynesian economicsMonetary economicsPhilosophy

Abstract

fetched live from OpenAlex

Several authors have presented reduced-form evidence suggesting that the degree of exchange rate pass-through to the consumer price index has declined in Canada since the early 1980s and is currently close to zero. Taylor (2000) suggests that this phenomenon, which has been observed for several other countries, may be due to a change in the behaviour of inflation. Specifically, moving from a high to a low-inflation environment has reduced the expected persistence of cost changes and, by consequence, the degree of pass-through to prices. This paper extends his argument, suggesting that this change in persistence is due to a change in the parameters of the central bank's policy rule. Evidence is presented for Canada indicating that policy has responded more aggressively to inflation deviations over the low pass-through period relative to the high pass-through period. We test the quantitative importance of this change in policy for exchange rate pass-through by varying the parameters of a simple monetary policy rule embedded in an open economy, dynamic stochastic general equilibrium model. Results suggest that increases in the aggressiveness of policy consistent with that observed for Canada are sufficient to effectively eliminate measured pass-through. However, this conclusion depends critically on the inclusion of price-mark-up shocks in the model. When these are excluded, a more modest decline to pass-through is predicted.

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), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.458
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.062
GPT teacher head0.241
Teacher spread0.179 · 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; both teacher heads agree on what is shown here.

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

Citations17
Published2021
Admission routes2
Has abstractyes

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