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Enregistrement W3123411670

Projections of Washington-British Columbia Trade and Traffic by Commodity, Route and Border Crossings

2007· preprint· en· W3123411670 sur OpenAlex

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Notice bibliographique

RevueRePEc: Research Papers in Economics · 2007
Typepreprint
Langueen
DomaineBusiness, Management and Accounting
ThématiqueTransportation Systems and Infrastructure
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésCommodityOrder (exchange)TruckBusinessFrontierInternational tradeTransport engineeringEconomyFinanceGeographyEngineeringEconomics
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Continuing adaptation to the changing transportation needs of the U.S. and Canada is critical in maintaining efficiency and reducing costs of raw and manufactured goods. As NAFTA moves into its twelfth year of existence, there is a growing need to continue adapting to the changing transportation environment. With bilateral trade in excess of $1.2 billion per day between the U.S. and Canada and over 200 million annual crossings (passenger vehicles and freight trucks), knowledge of the composition of commodities crossing the border allow for easier adjustment to and support for the changing needs of industries and transportation providers. Since Washington borders Canada and acts as an international trade hub for the state as well as industries throughout the United States, there is a specific need to evaluate the composition of commodities at its key border ports in order to project future traffic. This project identifies key commodity groups in order to create a profile of major and minor Washington border ports in order to develop traffic projections. The central resource used to create the profile is the Strategic Freight Transportation Analysis (SFTA) database, a compilation of freight origin-destination survey results. The survey, not known to be duplicated by any other state, allows for the decomposition of freight flows by commodity, both northbound and southbound, thus allowing profiles to be created for seven major and minor border ports in Washington. The border ports analyzed are: Blaine/Pacific Highway, Lynden/Aldergrove, Sumas/Huntington, Oroville/Osoyoos, Danville/Carson, Laurier/Cascade, and Frontier/Patterson. Furthermore, SFTA allows for the decomposition of routes, which are used to estimate the flow of freight traffic on major Washington arterials, providing a profile of arterial highway usage by each border port. Once the profile was created, projections of northbound and southbound crossings from 2006 to the year 2015 were estimated for each border port. Linear regression trend line analysis was used to determine the potential growth of crossings based on the growth of trade between the U.S. and Canada. After projected crossings were initially estimated, projections of future northbound and southbound trade by Harmonized System of Commodity Classification Codes (HS) at the 2-digit commodity level, as well as projections of U.S. and Canadian industries, were combined with SFTA to determine the future composition of commodities crossing through the various border ports. These projections of traffic based on trade were then compared with the initial border crossing projections. The process used to determine the projections is shown in Figure 1. The top seven 3-digit NAICS commodity categories crossing the various Washington border ports are: food products, chemical products, plastic & rubber products, wood products, paper products, metallic products (fabricated and primary), and non-metallic mineral products. The NAICS categories were then translated into HS categories for 2 projections. The findings are in part corroborated with the Harmonized System trading commodities between British Columbia and Washington, as well as between Washington and Canada. The truck crossing findings show that the percentage growth in the number of northbound and southbound crossings by border port, based on 10-year average annual percent changes, range from -6.1% to 3.82%. The 10-year average annual increases for bidirectional trade range from 0.81% to 4.7%. As trade growth averages change over time, so will the commodity profiles of the specific border ports. When truck crossings are incorporated with trade growth we see a difference of 0.62% and 15.46% between the original “naïve” truck crossing projections and the new trade adjusted truck crossing projections. These projections on the future traffic volume and composition of commodities crossing between Washington and British Columbia serve as a guideline for future transportation of traded goods and the infrastructure investments necessary to support those flows.

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.

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 candidatesMéta-épidémiologie (sens strict), Communication savante
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,451
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0020,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
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 Opus0,016
Tête enseignante GPT0,277
Écart entre enseignants0,261 · 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