Abstract
In an earlier report, changes in bitumen prices at Hardesty, Alberta, Canada, were modeled as the responses to changes in monthly prices of Hardesty light/medium crude oil for the period 2000–2006 with a simple error correction econometric model. This note re-examines that price relationship for the period 2009–2014. Over the period 2006–2014, there was also rapid growth in North American light oil production from low-permeability carbonate, sandstone, and shale reservoirs. During that period, Canadian raw bitumen production grew by more than 12% per year and there was significant geographical diversification in its markets. Results of the statistical analysis showed that the change in the dynamic relationships between bitumen prices and Hardesty light oil prices probably reflected, in part, the maturation of bitumen markets and closer integration with North American light oil markets. The analysis also examines the dynamic relationships between bitumen prices and West Texas Intermediate and Brent international benchmark crude oil prices. Ideally, if bitumen prices are found to be closely related to a widely traded benchmark crude oil, the benchmark crude oil price forecasts could be used as a basis for predicting bitumen prices. However, neither of international benchmark crude oils tested had high explanatory power.
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Notes
1 barrel = 0.1590 cubic meters.
The group of producers includes Cenovus, Canadian Natural Resources Limited, Suncor, and Talisman Energy Inc.
The standard blend for pipeline transportation is 30% condensates and 70% bitumen. With heated tanker cars for unloading bitumen, diluents can be reduced to zero. Without diluents, however, unloading can be a long process lengthening transport cycle times. A suggested alternative to the full 30% diluent requirement is ‘railbit’, which is composed of 17% diluents and which will facilitate the unloading and subsequent transport of the bitumen (Fielden 2013).
The Alberta government agency series represented actual transactions prices. The government stopped publishing those data to protect the identity of the firms participating in the market. Flint Hill refinery monthly posted prices are indicative of transactions prices but the actual transaction prices may differ. Flint Hill no longer posts prices on its website.
Granger causality is not a proof of true causality but simply provides a means of assessing whether current values of an economic variable are useful in predicting the future values of another economic variable.
There was no evidence of co-integration between the bitumen price series and the WCS crude blend price series according to the Phillips–Ouliaris test at the 5% confidence level. There was also no evidence that the WCS prices are useful in predicting bitumen prices, that is, those WCS prices cause bitumen prices in the Granger sense.
Bewley (1979) provides a method to directly compute the long-term multiplier and its standard deviation, thus permitting the calculation of the Student’s t statistic (ratio of multiplier to its standard deviation) and the p value. For the model using the Hardesty light oil as the benchmark for the period 2000–2006, the calculated value of long-run multiplier is 0.45 and the Student’s t statistic is 14 ( p value <0.0001) . Using the same price series but for the period 2009–2014, the long-run multiplier is 0.98 and the Student’s t statistic is 15.3 (p values <0.0001).
Co-integration is not a necessary condition for valid error correction models (De Boef and Keele 2008).
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Attanasi, E.D. Bitumen Prices and Structural Changes in North American Crude Oil Markets. Nat Resour Res 25, 487–496 (2016). https://doi.org/10.1007/s11053-016-9298-z
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DOI: https://doi.org/10.1007/s11053-016-9298-z