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Record W2269311455 · doi:10.24148/wp2007-27

The International Dimension of U.S. Expansions: A Structural VAR Analysis

2008· article· en· W2269311455 on OpenAlexaff
Giancarlo Corsetti, Luca Dedola, Sylvain Leduc

Bibliographic record

VenueFederal Reserve Bank of San Francisco, Working Paper Series · 2008
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsBank of Canada
FundersEuropean University Institute
KeywordsEconomicsNet foreign assetsMonetary economicsLiberian dollarConsumption (sociology)Stock (firearms)ProductivityDemand shockAggregate demandExchange rateEconometricsInternational economicsMacroeconomicsCurrent accountMonetary policy

Abstract

fetched live from OpenAlex

This paper investigates the international dimension of productivity and demand shocks in the U.S. using sign restrictions based on standard theory predictions. Identifying shocks to U.S. manufacturing--our measure of tradables--we find that productivity gains have substantial aggregate demand effects, boosting U.S. consumption and investment, relative to the rest of the world, thus raising real imports; net exports and U.S. net foreign assets correspondingly decrease. At the same time, however, these shocks appreciate the U.S. real exchange rate, improve the terms of trade and raise stock prices. Shocks to the demand for U.S. manufacturing appear to have less pronounced aggregate effects, with little impact on trade and capital accounts; they lead to a (delayed) dollar appreciation, however. Our findings provide novel evidence on key channels of the international transmission of shocks, pointing to a low degree of consumption risk sharing as an essential feature of the transmission mechanism, and suggesting that strong wealth effects play an important role in generating aggregate demand fluctuations across countries.

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)0.000
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 score0.025
Threshold uncertainty score0.912

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.054
GPT teacher head0.236
Teacher spread0.183 · 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.

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

Citations2
Published2008
Admission routes1
Has abstractyes

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