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5 Results

The New Benchmark for Forecasts of the Real Price of Crude Oil

How can we assess the quality of a forecast? We propose a new benchmark to evaluate forecasts of temporally aggregated series and show that the real price of oil is more difficult to predict than we thought.

Outlook for Electric Vehicles and Implications for the Oil Market

Staff Analytical Note 2019-19 Étienne Latulippe, Kun Mo
The market for electric vehicles (EVs) is growing rapidly. Subsidies and technological improvements are expected to increase the market share of EVs over the coming decade. In its base-case scenario, the International Energy Agency (IEA) expects EV use to rise from 4 million vehicles in 2018 to 120 million by 2030, or from 0.3 per cent to over 7 per cent of the global car fleet.
Content Type(s): Staff research, Staff analytical notes Topic(s): International topics JEL Code(s): Q, Q4, Q47

Crude Oil Prices and Fixed-Asset Cash Spending in the Oil and Gas Industry: Findings from VAR Models

Staff Analytical Note 2016-8 Farrukh Suvankulov
This note investigates the relationship between crude oil prices and investment in the energy sector. We employ a set of vector autoregression (VAR) models (unconstrained VAR, vector error-correction and Bayesian VAR) to formalize the relationship between the West Texas Intermediate (WTI) benchmark and fixed-asset cash spending in the oil and gas extraction and support activities sector of the Canadian economy.

A Blessing in Disguise: The Implications of High Global Oil Prices for the North American Market

Staff Working Paper 2013-23 Ron Alquist, Justin-Damien Guénette
We examine the implications of increased unconventional crude oil production in North America. This production increase has been made possible by the existence of alternative oil-recovery technologies and persistently elevated oil prices that make these technologies commercially viable.

Forecasting the Price of Oil

Staff Working Paper 2011-15 Ron Alquist, Lutz Kilian, Robert Vigfusson
We address some of the key questions that arise in forecasting the price of crude oil. What do applied forecasters need to know about the choice of sample period and about the tradeoffs between alternative oil price series and model specifications?