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Record W1540651576

The Economic Impact of a U.S. Slowdown on the Americas

2008· article· en· W1540651576 on OpenAlexaboutno aff
Mark Weisbrot, John Schmitt, Luis Sandoval

Bibliographic record

VenueCEPR Reports and Issue Briefs · 2008
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsRecessionEconomicsInternational economicsReal gross domestic productFree trade agreementBalance of tradeInternational tradeSlowdownFree tradeDevelopment economicsEconomic growthMonetary economicsMacroeconomics
DOInot available

Abstract

fetched live from OpenAlex

This paper shows that the U.S.'s biggest trading partners in the Americas will likely see a significant loss in exports and GDP as the U.S. economy slows. Countries less reliant on the U.S. market will not be as negatively impacted. The paper makes two sets of projections for the decline in exports countries in the Americas may experience. The low-adjustment scenario assumes that the U.S. trade deficit falls from 5.2 percent of GDP in 2007 to 3.0 percent of GDP in 2010. The high adjustment scenario assumes that the U.S. trade deficit falls back to 1.0 percent of GDP by 2010. The paper finds that the countries that will likely suffer most as the result of a reduction in U.S. imports are the same countries with which the United States has implemented “free trade” agreements in recent decades, including the North American Free Trade Agreement (NAFTA) between the United States, Canada, and Mexico, and the Dominican Republic-Central America Free Trade Agreement (DR-CAFTA), which includes the United States along with Guatemala, El Salvador, Costa Rica, Nicaragua, Honduras, and the Dominican Republic. Meanwhile, countries that are less dependent on the United States, or more reliant on domestic demand, will see smaller impacts of the U.S. recession on their exports and national GDP.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.758
Threshold uncertainty score0.973

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.027
GPT teacher head0.251
Teacher spread0.225 · 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 designTheoretical or conceptual
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

Citations6
Published2008
Admission routes1
Has abstractyes

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