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Record W3161828907 · doi:10.3386/w27652

Trade Flows and Fiscal Multipliers

2020· report· en· W3161828907 on OpenAlexaffabout
Matteo Cacciatore, Nora Traum

Bibliographic record

VenueNational Bureau of Economic Research · 2020
Typereport
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policy and Economic Growth
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsEconomicsInternational economicsInternational tradeMacroeconomicsMonetary economicsBusiness

Abstract

fetched live from OpenAlex

We present novel insights on the role of international trade following unanticipated government spending and income tax changes in a flexible exchange rate environment.In a simple twocountry, two-good model, we show analytically that fiscal multipliers can be larger in economies more open to trade, even when fiscal expansions imply a trade deficit.Cross-country comovement can be positive or negative.Three factors determine how trade linkages affect fiscal multipliers: the relative import share of public and private goods, how the government finances its budget, and the currency invoicing of exports.A Bayesian prior-predictive analysis shows a quantitative international business-cycle model bears the same predictions.Estimating the model on Canadian and U.S. data, we find support for larger multipliers relative to a counterfactually closed economy and positive cross-country spillovers.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.009
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.386
GPT teacher head0.443
Teacher spread0.056 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations8
Published2020
Admission routes2
Has abstractyes

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