Intra-Industry Trade between the United States and Canada
Notice bibliographique
Résumé
In this thesis, US - Canada trade patterns were analyzed and the determinants of US - Canada Intra - Industry Trade (IIT) were empirically tested. IIT is explained using the new trade theories, including the Neo-factor Proportions Model and Monopolistic Competition Model under General Trade Equilibrium (instead of the Functional Hypotheses). The following three hypotheses that are empirically tested in this paper. The level of IIT is expected to be relatively high in industries: 1) with high levels of product differentiation, which is tested by the following proxies such as advertising expenses, value added and capital intensity, 2) typified by having economies of scale, which is tested by variable such as the average production cost; and 3) in which intense oligopolistic rivalry is common, where the oligopolistic rivalry is tested by proxy such as the world market share of US exports. Data were collected from the Organization of Economic Cooperation and Development (OECD) and the US Economic Census and proxies were developed to test each hypothesis. Three regression procedures were run. Results of the final model specification yielded statistically significant results and provided empirical evidence in support of the above three hypotheses. The findings resulting from this research include: First, the significant result of product differentiation variable - advertisement expenses, in manufacturing industries showed that advertisement expenses only significantly influenced the level of US - Canada IIT in manufacturing sector. This result is consistent with the observation that higher degrees of advertisement spending is associated with manufacturing industries because the existence of higher degrees of horizontal product differentiation in this sector as compared to other industry sectors. Large investment in advertisement is the direct result of high degree of horizontal product differentiation. Second, the regression results suggest that in the agricultural sector economies of scale is more likely to lead to comparative advantage in production. The greater economies of scale in agriculture sector result in a higher level of one-way trade, thus a lower level of IIT component of total trade. Third, industries with low capital intensity are more likely t? be linked with early stages of the product cycle and a low level of product differentiation. Therefore, a low degree of IIT should be observed in these industries. Fourth, the larger the international market share of US industries, the more international oligopolistic market power US companies have over foreign companies, the more difficult it is for Canadian products to enter US market. This leads to a low level of IIT in these industries. Finally, this research indicates that by mixing three and four digit SITC industries in one empirical study can cause misleading result, so it is critical to keep the same industry aggregation level for future empirical IIT study.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,006 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,002 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».