Multilateral tariff cooperation under fairness and reciprocity
Bibliographic record
Abstract
This paper explores the impact of fairness and reciprocity on multilateral tariff cooperation. Reciprocal countries reward kind behaviour (positive reciprocity), but retaliate against countries behaving unkindly (negative reciprocity). We demonstrate that reciprocal countries that are moderately demanding from their trading partners regarding their commercial policy can support a greater degree of cooperation than self-interested ones. However, when only very liberal import policies are considered fair, then reciprocity could have a detrimental effect on multilateral tariff cooperation.Thus, our model provides a novel perspective on the role of expectations in trade negotiations. JEL classification: F13, D63 Cooperation tarifaire multilaterale en presence d’egards (fairness) et de reciprocite.Ce texte explore l’impact des egards et de la reciprocite sur la cooperation tarifaire multilaterale, Les pays en relation de reciprocite recompensent un comportement avec egards (reciprocite positive) mais se vengent des pays des pays qui se comportent sans egards (reciprocite negative). On montre que les pays en relation de reciprocite qui sont moderement exigeants de leurs partenaires commerciaux quand a leur politique commerciale peuvent supporter un plus fort degre de cooperation que ceux strictement interesses a leurs interets propres. Cependant, quand seulement des politiques d’importation tres liberales sont considerees comme montrant des egards (fair), alors la reciprocite peut avoir un effet negatif sur la cooperation tarifaire multilaterale. Le modele developpe une perspective nouvelle sur le role des anticipations dans les negociations commerciales. We would like to thank Luis Santos-Pinto, anonymous referees, and participants at CRETE 2009, ETSG 2009, ASSET 2009, Spring 2011 Midwest International Trade Meeting, UECE Lisbon Meetings 2011 in Game Theory and Applications, and a seminar at Istanbul Bilgi University for very helpful comments and suggestions. A previous version of the paper was written while . Iris was visiting UC San Diego and Tabakis was an International Faculty Fellow at the MIT Sloan School of Management. Tabakis gratefully acknowledges financial support from the Fundacao para a Ciencia e a Tecnologia in Portugal. Any errors are ours. Email: costash@ucy.ac.cy Canadian Journal of Economics / Revue canadienne d’Economique, Vol. 45, No. 3 August / aout 2012. Printed in Canada / Imprime au Canada 0008-4085 / 12 / 925–941 / C © Canadian Economics Association 926 C. Hadjiyiannis, D. Iris, and C. Tabakis
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| 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 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".