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Record W2014170497 · doi:10.1080/09638199.2011.647049

Green productivity and bilateral trade flows in an augmented gravity model – A panel data analysis

2012· article· en· W2014170497 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.

Bibliographic record

VenueJournal of International Trade & Economic Development · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsDawson College
Fundersnot available
KeywordsPanel dataGravity model of tradeProductivityBilateral tradeEconomicsPer capitaEconometricsInternational tradeMacroeconomicsChinaSociologyGeography

Abstract

fetched live from OpenAlex

Motivated by the debate in the trade liberalization and the environment literature, this article examines the effect of enhancing green productivity (GP) on bilateral trade flows. The uptake of per capita ISO14001 certification counts is used to measure GP. The existing literature provides other key determinants of bilateral trade flows. This article employs an augmented gravity model and presents panel data analysis on 26 countries from 1995-2004. Since GP is closely related to quality management, this article also examines the joint effect of the measure of quality management systems (QMS) and the measure of GP. Several fixed effects regression equations are estimated. The results support the hypothesis that enhancing green productivity is a positive and statistically significant determinant of real bilateral exports. The joint significance of the measures of GP and QMS is also supported. This article lends empirical support for the new trade theory and Linder's hypothesis and is consistent with those obtained in the existing literature.

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)0.002
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 score0.090
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.136
GPT teacher head0.271
Teacher spread0.135 · 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