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Record W3122221701

Central bank communications: a case study

2016· preprint· en· W3122221701 on OpenAlexaboutno aff
Jonathan Davis, Mark A. Wynne

Bibliographic record

VenueRePEc: Research Papers in Economics · 2016
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicComplex Systems and Time Series Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsMonetary policyStatement (logic)Open market operationShock (circulatory)Central bankQuarter (Canadian coin)Inflation (cosmology)Forward guidanceFinancial marketMonetary economicsEconomicsBusinessInflation targetingPolitical scienceFinanceHistoryCredit channelLaw
DOInot available

Abstract

fetched live from OpenAlex

Over the past twenty five years, central bank communications have undergone a major revolution. Central banks that previously shrouded themselves in mystery now embrace social media to get their message out to the widest audience. The Federal Reserve System has not always been at the forefront of these changes, but the volume of information about monetary policy that the Federal Open Market Committee (FOMC) now releases dwarfs what it was releasing a quarter century ago. In this paper we focus on just one channel of FOMC communications, the post-meeting statement. We document how it has evolved over time, and in particular the extent to which it has become more detailed, but also more difficult to understand. We then use a VAR with daily financial market data to estimate a daily time series of U.S. monetary policy shocks. We show how these shocks on Fed statement release days have gotten larger as the statement has gotten longer and more detailed, and we show that the length and complexity of the statement has a direct effect on the size of the monetary policy shock following a Fed decision.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.682
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.003
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 head0.092
GPT teacher head0.327
Teacher spread0.236 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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