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Record W1531219838 · doi:10.1111/caje.12354

On the effects of unilateral environmental policy on offshoring in multi‐stage production processes

2018· article· en· W1531219838 on OpenAlexvenueno aff
Oliver Schenker, Simon Koesler, Andreas Löschel

Bibliographic record

VenueCanadian Journal of Economics/Revue canadienne d économique · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsOffshoringUpstream (networking)Supply chainComputable general equilibriumDownstream (manufacturing)Production (economics)Industrial organizationEuropean unionRepresentation (politics)EconomicsGeneral equilibrium theoryInternational tradeMicroeconomicsBusinessInternational economicsOperations managementComputer scienceOutsourcing

Abstract

fetched live from OpenAlex

Abstract We extend the literature on global supply chains by analyzing if and how unilateral environmental regulation induces offshoring. We develop an analytical model of two‐stage production processes that can be distributed between two countries and investigate unilateral emission pricing and its supplementation with border carbon taxes. In contrast to existing final good models, we are able to show how impacts of regulation differ across the different stages of the supply chain, depending on the interplay of comparative advantages and general equilibrium effects. To get a more comprehensive picture, we subsequently apply a computable general equilibrium model that includes a representation of international supply chains. We find heterogeneous but mostly positive effects of a unilateral carbon emission reduction by the European Union on the degree of vertical specialization of European industries. Border taxes are successful in protecting upstream industries, but with negative side effects for downstream industries.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.748
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.210
GPT teacher head0.210
Teacher spread0.000 · 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 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

Citations21
Published2018
Admission routes1
Has abstractyes

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