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Record W3122097285 · doi:10.22004/ag.econ.273660

Monetary Transmission Mechanism in a Small Open Economy: A Bayesian Structural VAR Approach

2008· preprint· en· W3122097285 on OpenAlexaboutno aff
Rokon Bhuiyan

Bibliographic record

VenueAgEcon Search (University of Minnesota, USA) · 2008
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsnot available
Fundersnot available
KeywordsMonetary policyImpulse responseEconomicsBayesian vector autoregressionShock (circulatory)Exchange rateSmall open economyInterest rateMonetary economicsFederal fundsVector autoregressionEconometricsBayesian probabilityOpen economyInterest rate parityMacroeconomicsStatisticsMathematics

Abstract

fetched live from OpenAlex

This paper develops an open-economy Bayesian structural VAR model for Canada in order to estimate the effects of monetary policy shocks, using the overnight target rate as the policy instrument. I allow the policy variable and the financial variables of the model to interact simultaneously with each other and with a number of other home and foreign variables. When I estimate this over-identified VAR model, I find that the policy shock transmits to real output through both the interest rate and exchange rate channels, and the shock does not induce a departure from uncovered interest rate parity. I also find that the impulse response of the monetary aggregate, M1, does not exactly follow the impulse response of the target rate. Finally, I find that Canadian variables significantly responds to the US federal funds rate shock, and external shocks are an important source of Canadian output fluctuations.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.543
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.001
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 head0.104
GPT teacher head0.230
Teacher spread0.127 · 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 designSimulation or modeling
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

Citations6
Published2008
Admission routes1
Has abstractyes

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