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Record W3121617851

Sectoral Interdependence and Business Cycle Synchronization in Small Open Economies

2014· preprint· en· W3121617851 on OpenAlexaboutno aff
Drago Bergholt, Tommy Sveen

Bibliographic record

VenueBIBSYS Brage (BIBSYS (Norway)) · 2014
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsnot available
FundersNorges Forskningsråd
KeywordsBusiness cycleSmall open economyEconomicsDynamic stochastic general equilibriumOpen economyVolatility (finance)Tertiary sector of the economyProductivityInternational businessMonetary economicsInternational economicsEconomyInternational tradeMacroeconomicsEconometricsMonetary policy
DOInot available

Abstract

fetched live from OpenAlex

Existing DSGE models are not able to reproduce the observed influence of international business cycles on small open economies. We construct a two-sector New Keynesian model to address this puzzle. The set-up takes into account intermediate trade and producer heterogeneity, where goods and service industries differ in terms of i) price flexibility, ii) trade intensity, iii) technology, iv) I-O structure, and v) the volatility of productivity innovations. The combination of intermediate markets and heterogeneous producers makes international business cycles highly important for the small economy, even if it has a large service sector. Exploiting I-O matrices of Canadian and US industries, the model is able to reproduce the role of international disturbances typically found in empirical studies. Model simulations deliver cross-country correlations in macroeconomic variables of about 0:7, with half of the variation in domestic variables attributed to foreign shocks.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, 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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.069
GPT teacher head0.242
Teacher spread0.173 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

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