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Enregistrement W6963436269 · doi:10.21256/zhaw-26512

Switzerland’s opportunity costs for not joining the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP)

2022· article· en· W6963436269 sur OpenAlexaboutno aff

Notice bibliographique

RevueZürcher Hochschule für Angewandte Wissenschaften digital collection (Zurich University of Applied Sciences) · 2022
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueInternational Relations in Latin America
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésGeneral partnershipOpportunity costWork (physics)

Résumé

récupéré en direct d'OpenAlex

Switzerland has faced growing troubles concerning negotiating new and renegotiating existing free trade agreements (FTAs). These agreements are a critical part of the country’s ability to provide its companies with competitive parity compared to businesses from other countries. Therefore, new options have to be assessed to even the playing field in terms of trade for Swiss companies. One such option is the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP), which to date includes 11 nations. So far, the discussion regarding a Swiss membership in this agreement has been held on a qualitative basis. Therefore, it is unknown what membership in this agreement would mean for Switzerland in numeric terms. This Bachelor’s thesis provides a first approach to calculating the opportunity costs (OC) for Switzerland in the form of lost trade. In addition, it gives an overview of all current and potential CPTPP countries, their current relationship with Switzerland, and their demographic situation. Moreover, it estimates the FTAs' impact on different Swiss industries and lists the most important countries among current CPTPP members. These countries are then compared with the current priority list of the State Secretariat for Economic Affairs (SECO). To make these forecasts, Swiss trade data from 2012 to 2020 is used to predict how trade might behave in the future. The forecasts estimate how trade between Switzerland and CPTPP members might behave between 2020 and 2030. All detailed calculations can be found in the appendix and an additional Excel file attached to this thesis. The calculations conducted in this thesis have forecasted that the OC for Switzerland is equal to approximately CHF 989.6 million. Of these costs, CHF 283.9 million are expected to be carried by exporters and CHF 705.7 million by importers of goods. Therefore, imports are expected to rise more than exports if Switzerland enters this FTA. Sectors that will benefit from this treaty were found to be the pharmaceutical, chemical, and metal industries. The industries of precision instruments, watches, jewelry, textiles, precious metals, machinery, agriculture, forestry, and fishing will be at a disadvantage. Another version of this analysis was conducted without Vietnam and found that precision instruments, watches, jewelry, and machines would also benefit from a Swiss CPTPP membership. The most crucial CPTPP members for Switzerland were found to be Vietnam, Japan, Australia, Singapore, Malaysia, and Canada. Of these nations, Australia is the only one that Switzerland does not view as one of its priorities or has started the process of negotiating an FTA. This thesis recommends that Switzerland becomes a member of the CPTPP as the potential costs resulting from lost trade are significant. It would be beneficial to enter into this FTA from a monetary perspective as the costs of the currently higher tariffs are carried by domestic consumers, reducing their welfare. However, an entry into this agreement is estimated to reduce Swiss net exports, which could put additional stress on domestic producers.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesÉtudes des sciences et des technologies
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,680
Score d'incertitude au seuil0,997

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0050,001
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,055
Tête enseignante GPT0,311
Écart entre enseignants0,256 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2022
Routes d'admission1
Résumé présentoui

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