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Record W6909116163 · doi:10.34989/swp-1996-8

Interpreting Money-Supply and Interest-Rate Shocks as Monetary-Policy Shocks

2021· article· en· W6909116163 on OpenAlexaffabout

Bibliographic record

VenueBank of Canada Research · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsBank of Canada
Fundersnot available
KeywordsShock (circulatory)Depreciation (economics)Monetary policyMarket liquidityInterest rateStock (firearms)Vector autoregressionMoneyness

Abstract

fetched live from OpenAlex

In this paper two shocks are analysed using Canadian data: a money-supply shock ("M-shock") and an interest-rate shock ("R-shock"). Money-supply shocks are derived using long-run restrictions based on long-run propositions of monetary theory. Thus, an M-shock is represented by an orthogonalized innovation in the trend shared by money and prices. An R-shock is represented by the orthogonalized innovation in the overnight interest rate. Either type of shock might be interpreted as a monetary-policy shock. A permanent increase in the nominal stock of M1 generates: a temporary fall in the interest rate, consistent with the liquidity effect; a temporary rise in real output; a permanent increase in the price level; and a permanent depreciation of the nominal exchange rate. Although the behaviour of M1 is not directly controlled by the central bank, the identifying assumption that the central bank controls the long-run trend in money and prices and has no long-run effect on real output appears to be quite reasonable. A temporary positive real-interest-rate shock generates a temporary fall in money and output, but prices rise initially (a "price puzzle") before eventually declining. Both the M-shock and R-shock models are consistent with an active role for money in the transmission of monetary policy.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.377
Threshold uncertainty score0.999

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.088
GPT teacher head0.296
Teacher spread0.207 · 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 designNot applicable
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

Citations0
Published2021
Admission routes2
Has abstractyes

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