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Record W4391928331 · doi:10.1111/roie.12740

Spatial spillovers in trade agreement memberships: Does institutional proximity matter?

2024· article· en· W4391928331 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueReview of International Economics · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsUniversity of Guelph
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of WaterlooUniversity of Patras
KeywordsEconomicsRobustness (evolution)Variable (mathematics)Spatial econometricsSpatial dependenceEconometricsInternational economicsStatisticsMathematics

Abstract

fetched live from OpenAlex

Abstract This paper examines spatial spillovers in the formation of preferential trade agreements (PTAs) through a new channel of institutional proximity. Our dependent variable is the status of PTAs between country attributes within a country‐pair. The explanatory variable of interest is the status of PTAs in neighbouring country‐pairs that share proximity in institutional development. We consider democracy and economic freedom as the main aspects of institutions, and use both as the fundamental components of institutional distance between country‐pairs. Employing a spatial econometric method, we find strong evidence of the institutional interdependence of PTAs: country‐pairs tend to influence each other's decision on the formation and the chosen type of PTAs (i.e., deep or shallow), such a neighbourhood effect increases with institutional proximity and is more prominent for the decisions on the type of PTAs. The institutional spatial channel is robust to various robustness checks.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.896
Threshold uncertainty score1.000

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.042
GPT teacher head0.245
Teacher spread0.203 · 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