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dc.contributor.advisor10.1080/09638199.2019.1629616en
dc.contributor.authorFahmy, Hany
dc.date.accessioned2019-07-27T21:49:39Z
dc.date.available2019-07-27T21:49:39Z
dc.date.issued2019
dc.identifier.citationFahmy, H. (2019). Classifying and modeling nonlinearity in commodity prices using Incoterms. The Journal of International Trade & Economic Development, 1-28.en_US
dc.identifier.issn1469-9559
dc.identifier.urihttps://viurrspace.ca/handle/10613/13983
dc.descriptionThe file associated with this record is the original manuscript version of the article, previously titled "Understanding the Behavior and Co-Movement in Commodity Prices using Incoterms". The final authenticated version is available at: https://doi.org/10.1080/09638199.2019.1629616.en_US
dc.description.abstractThis paper proposes a novel approach of classifying and modeling the nonlinear behavior of commodity prices using regime-switching models with exogenous transition variables. The approach rests on using the International Commercial Terms (Incoterms), also known as border prices, to classify commodities in groups that tend to display similar dynamics. The suggested border price classification is useful in identifying the key exogenous driving variables in each group. In particular, the classification suggests that inflation and oil price are the best transition candidates that are capable of capturing the nonlinear dynamics of free on board (FOB) and cost insurance and freight (CIF) prices respectively. Our statistical linearity tests and estimation results confirm this prediction and highlight the importance of the suggested border price classification in improving our understanding of the behavior of commodity prices. KEYWORDS: Incoterms, border prices, commodity prices, regime switching, smooth transition regression JEL CLASSIFICATIONS: C10, C22, E30, F00, F10en_US
dc.language.isoenen_US
dc.publisherThe Journal of International Trade & Economic Developmenten_US
dc.subjectPricesen_US
dc.subjectIncotermsen_US
dc.titleClassifying and modeling nonlinearity in commodity prices using Incotermsen_US
dc.typeArticleen_US


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