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Record W2120183203 · doi:10.22004/ag.econ.25297

The Effects of Trade Liberalization of the Environment: An Empirical Study

2006· preprint· en· W2120183203 on OpenAlexaff
Geoffrey R. McCarney, Wiktor Adamowicz

Bibliographic record

VenueAgEcon Search (University of Minnesota, USA) · 2006
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicEnergy, Environment, Economic Growth
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPollution haven hypothesisOpenness to experiencePanel dataEconomicsPollutantInternational economicsEnvironmental degradationEnvironmental qualityNatural resource economicsForeign direct investmentMacroeconomicsEconometricsEcology

Abstract

fetched live from OpenAlex

We seek to contribute to the emerging economic theory on trade, the environment and development. Using panel data across countries, econometric models are estimated to predict the effects of openness on organic water pollutant (BOD) and carbon dioxide (CO2) emissions. Results indicate that freer trade significantly increases emissions of both pollutants, thus reducing environmental quality. Moreover, the panel nature of the data allows heterogeneity across countries to be controlled, so that comparisons can be made of how different national characteristics influence the environmental impact of freer trade. By testing the effects of democratic versus autocratic governance, it is found that while greater democracy can induce significant reductions in BOD emissions as openness increases, it may also lead to increased CO2 levels. Meanwhile, by testing for and failing to reject the pollution haven hypothesis, it is suggested that environmental gains from openness in relatively rich countries may be coming at the expense of environmental degradation in poorer 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.027
GPT teacher head0.215
Teacher spread0.188 · 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.

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

Citations19
Published2006
Admission routes1
Has abstractyes

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