Optimal tariffs of preferential trade agreements and the tariff complementarity effect
Bibliographic record
Abstract
Purpose The purpose of this paper is to evaluate and contrast the welfare effects of free trade agreements (FTAs) and customs unions (CUs) on member and non‐member countries when tariffs of both members and non‐members are endogenously determined. It also aims to provide sufficient conditions under which both types of preferential trade agreement (PTA) are likely to lower tariffs on non‐members relative to that under most favored nation (MFN). Design/methodology/approach The paper employs a three country Cournot oligopoly model of trade with segmented markets. Findings It is shown that under symmetry CU members enjoy higher welfare relative to that under an FTA or MFN. Furthermore, the non‐member country gains from the formation of a PTA so long as the PTA's external tariff falls below a certain threshold. However, for FTA members to necessarily gain, their external tariff needs to be greater than this threshold but smaller than twice their MFN tariffs. Outside this tariff range, welfare effects of FTAs are ambiguous in the absence of further assumptions. The paper also isolates sufficient conditions under which a PTA member is less likely to impose a positive tariff on the non‐member relative to that under MFN. Originality/value Unlike existing literature, we do no assume demand linearity to obtain our main welfare results and use this assumption only for illustrative purposes. Another contribution of the paper is to provide sufficient conditions under which a PTA member is less likely to impose a positive tariff on the non‐member relative to that under MFN.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".