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Record W2950590825 · doi:10.11575/prism/36640

Essays in International Trade and Environmental Policy

2019· dissertation· en· W2950590825 on OpenAlexaboutno aff
Alaz Safak Munzur

Bibliographic record

VenueOpen MIND · 2019
Typedissertation
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental policyInternational tradeEconomicsCommercial policyInternational economicsNatural resource economics

Abstract

fetched live from OpenAlex

This thesis comprises a collection of three essays on international trade and environmental policy. In Chapter 1, I examine Britain’s trade policy in the 19th-century. Britain, the dominant trading nation of the time, abolished protectionist import tariffs in the middle of the century. To quantify the effect of this shift in trade policy on Britain’s welfare, I employ a general equilibrium trade model with multiple industries and input-output linkages. Relying on a novel dataset of trade flows and import tariffs of Britain and its main trading partners, I show that trade liberalization improved Britain’s overall welfare. This result is driven by the increased volume of trade. Although its terms of trade deteriorated, Britain benefited as its tariff structure became less restrictive over the period. In Chapter 2, I present an analysis of Canada’s commitment under the Paris Agreement. I examine the effects of meeting the emission reduction target as described in Canada’s Nationally Determined Contribution on welfare, bilateral trade and carbon leakage at the provincial and national level. To do this, I incorporate pollution emissions as a by-product of production into a general equilibrium trade model. Provinces substantially vary in terms of their economic structures and emissions profiles, therefore the effects of a national environmental policy differ at the regional level. By considering interprovincial trade and linkages across industries, the results provide a comprehensive understanding of how the industry level effects of a national target are transmitted through the Canadian economy and inform the policy in terms of the “emission intensive and trade exposed” industries at the provincial level. Meeting the Paris Agreement target decreases aggregate Canadian output by 0.48% but the provincial effects vary primarily due to differences in emissions intensity of production. Finally, the policy leads to 10.8% of emissions to relocate out of Canada but the proposed Output-Based Pricing System partly alleviates the problem of carbon leakage. In Chapter 3, using a general equilibrium trade model with cross-border pollution externalities from production, I evaluate the potential for carbon tariffs as an instrument to enforce the commitments under the Paris Agreement. Employing a non-cooperative optimal policy framework, I investigate the strategic interactions across five regions, Canada, China, the European Union, the United States and the rest of the world. In light of the debates following the possible withdrawal of the United States from the Paris Agreement, the analysis specifically focuses on the effects of welfare-maximising carbon tariffs on imports from the United States. I find that optimal carbon tariffs at the industry level result in small reductions in the total emissions and real income of the United States but are not sufficient to enforce participation in emission mitigation efforts. Compared to meeting its emission reduction targets, the United States is better off by withdrawing from the Paris Agreement, bearing the cost of carbon tariffs and retaliating in response. The committing regions are worse off when the United States retaliates. The results show that the negative effects of a worldwide tariff war on real incomes are substantially larger than the compliance cost to the Paris Agreement for all regions.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0030.005
Scholarly communication0.0060.005
Open science0.0010.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0130.002

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 head0.044
GPT teacher head0.256
Teacher spread0.212 · 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 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

Citations0
Published2019
Admission routes1
Has abstractyes

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