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Record W2227287924 · doi:10.1093/cesifo/ifaa012

The 2008 Financial Crisis and the Lack of Retaliatory Trade Intervention

2016· article· en· W2227287924 on OpenAlexaff
Chunding Li, John Whalley

Bibliographic record

VenueCESifo Economic Studies · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsWestern University
Fundersnot available
KeywordsTariffEconomicsGreat DepressionIncentiveFinancial crisisIntervention (counseling)General equilibrium theoryInternational economicsGlobalizationDownloadDepression (economics)Developing countrySimple (philosophy)MacroeconomicsMicroeconomicsEconomic growthComputer scienceMarket economyPolitical science

Abstract

fetched live from OpenAlex

Abstract The 2008 financial crisis did not precipitate global retaliatory trade intervention, in seeming contrast to the Great Depression in 1930s. This article discusses the influence of model structure in optimal tariff (OT) calculations in explaining this puzzle. We emphasize how earlier literature reports high OTs in numerical calculation (of a hundred percent) but only uses simple trade models. We use numerical general equilibrium (GE) calibration and simulation methodology to calculate OTs both with and without retaliation in a series of observationally equivalent models and explore the influence of model structures on OT levels. We gradually add more realistic features into the basic GE model, and show sharply declined OTs, which suggests that trade retaliation incentives effectively disappear with the deepening of globalization in 2008 compared to 1930. (JEL codes: F11, C63, F13).

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)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.104
GPT teacher head0.263
Teacher spread0.159 · 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 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

Citations0
Published2016
Admission routes1
Has abstractyes

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