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Comparison of international transport corridors in the Arctic based on the autoregressive distributed lag model
Author(s) -
D. F. Skripnuk,
K. N. Kikkas,
A. S. Safonova,
Elena Volodarskaya
Publication year - 2019
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/302/1/012096
Subject(s) - distributed lag , context (archaeology) , arctic , environmental science , sea transport , geography , transport engineering , econometrics , engineering , oceanography , economics , geology , archaeology
This article examines the modeling of international transport corridors using the autoregressive distributed lag (ARDL) model. The modeling of international transport corridors makes allowance for the potential capacity to develop the Arctic transport environment in the context of polar ice melting and increasing time of navigation on the seas of the Arctic Ocean. The authors build models for the Northern Sea Route, the Trans-Siberian Railway (TSR), the Southern Sea Route (transport corridor of the Suez Canal), the Northwest Passage, and analyze the natural, organizational, technological, and economic factors that affect the endogenous variable of the international transport corridor model. When building the transport corridor models, the authors take the volume of transit traffic via the international corridor in time t as the endogenous variable for all corridors. Exogenous variables are selected according to the variables that have the highest impact on the volume of traffic via each transport corridor and feature most prominently in the literature reviewed in this article. For the Northern Sea Route, these variables include Russia’s GDP, the number of ships passing through the route, the number of nuclear icebreakers, the average tariff, and the minimum ice coverage in the Arctic. For the Southern Sea Route (transport corridor of the Suez Canal) – EU’s GDP, the number of ships passing through the route, the average tariff, and the volume of commercial transit cargo. The methodology for determining the parameters of the model includes the following procedures: flux balance analysis, analysis of the autocorrelation between endogenous and exogenous variables, multicollinearity analysis.

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