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Record W635994182

Exchange Rate Impacts on West Coast Container Port Traffic

2013· article· en· W635994182 on OpenAlexaboutno aff
Philip R. Davies

Bibliographic record

VenueTransportation Research Board 92nd Annual MeetingTransportation Research Board · 2013
Typearticle
Languageen
FieldEngineering
TopicMaritime Ports and Logistics
Canadian institutionsnot available
Fundersnot available
KeywordsPort (circuit theory)Liberian dollarMainland ChinaMarket shareBusinessExchange rateRenminbiContainer (type theory)EconomicsAgricultural economicsMonetary economicsGeographyChinaFinanceEngineering
DOInot available

Abstract

fetched live from OpenAlex

Previous studies of the elasticity of West Coast container port traffic to increases in gateway costs have concluded that traffic is highly sensitive to cost increases. However, the major change in West Coast container port market shares has been the upward trend in the market share of the BC Lower Mainland ports (now combined as Port Metro Vancouver) from 9% in 2002 to 11% in 2011. This is difficult to reconcile with a high elasticity since the Canadian dollar increased by 36% against the U.S. dollar over this period, which led to higher port and inland transportation costs relative to US ports for Pacific Rim import traffic. The impact of exchange rate changes is explored through a regression analysis of Canadian Pacific Rim imports and port market shares. The results indicate that while the appreciation of the Canadian dollar had a negative impact on Lower Mainland container traffic, the effect was outweighed by increases in import volumes due to the reduction in the prices of imported goods. Estimates of Canadian Pacific Rim imports transhipped through US ports suggest that the share of US ports in Canadian traffic increased substantially over this period as a result of higher relative inland transportation costs. The paper highlights the influence of the differential impacts of changes in macroeconomic variables on port competitiveness.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.815
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.046
GPT teacher head0.328
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2013
Admission routes1
Has abstractyes

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