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Record W4387740092 · doi:10.1080/10242694.2023.2269520

International Transmission of Fiscal News Shock: Evidence from Defense Spending

2023· article· en· W4387740092 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueDefence and Peace Economics · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDefense, Military, and Policy Studies
Canadian institutionsEmployment and Social Development Canada
Fundersnot available
KeywordsEconomicsShock (circulatory)Fiscal policyGranger causalityGovernment spendingMonetary economicsMacroeconomicsEconometrics

Abstract

fetched live from OpenAlex

This paper proposes a novel fiscal news shock transmission channel from the US to Canada. The US and Canada have a long history of strong political and economic ties. This high degree of economic and political interdependence between Canada and the US makes the Canadian economy sensitive to policy changes in the US. We demonstrate that a fiscal news shock originating from a significant increase in US defense spending can directly transmit to Canada through enhanced defense spending in Canada. We construct a transmission model containing the defense spending news variable to assess the transmission of a fiscal news shock through this novel channel. Our findings suggest that news about increased US defense spending induces Canadian defense spending to rise. Consequently, this increased defense spending has a positive impact on the Canadian GDP. The estimated international fiscal multiplier for Canada is 0.11. We coin a novel fiscal multiplier labeled as the international defense multiplier, which quantifies the response of defense spending of a country due to a change in defense spending in another country.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.459
Threshold uncertainty score0.809

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.079
GPT teacher head0.272
Teacher spread0.193 · 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