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Home/Global Energy Markets Forecasts – Q4 2016

Global Energy Markets Forecasts – Q4 2016

This report – read by many of the world’s major energy companies – compiles Aurora’s long-term forecasts for oil, gas, and coal markets. Deploying our state-of-the-art in-house global general equilibrium model AER-GLO, the full Q1 report:

  • Presents an internally consistent, long-term view on fuel prices, production, and consumption by region
  • Identifies key areas of long-term uncertainty in global energy market fundamentals
  • Provides central, high, low, and P10/P90 price sensitivity analyses based on historical variation in key sources of uncertainty

Near-term price updates in Q2-Q4 reconcile the latest market outlook, encapsulated in futures prices, with Aurora’s annual Q1 equilibrium forecast. In our most recent central scenario, we forecast a moderate price recovery for all fuels in the medium term, reflecting a view that the recent market correction has overshot the fundamental extraction costs of supply necessary to meet growing demand from emerging economies. However, Aurora’s central scenario fundamentals imply that crude oil is set to remain below $75 per barrel (real 2014 US dollars) for the next two decades, and could potentially see a long term price of $40 per barrel in a low price scenario, where recent productivity improvements in North America are achieved globally.

To provide a transparent basis for judging the foundations of Aurora’s forecasts, our full Q1 report lays out the structure of the AER-GLO model and input assumptions in detail. AER-GLO is a global energy-economy model with a hybrid structure, consisting of a top-down global general equilibrium model and a detailed bottom-up dynamic resource extraction module. The key components of AER-GLO, and their main features, are:

Global General Equilibrium Model

  • General equilibrium structure enforces market clearance across all markets, ensuring internal consistency of results
  • Covers all economic activity in the world economy, aggregated to 12 collectively exhaustive categories of goods, and 23 regions
  • Takes into account interactions between different markets, and substitution mechanisms between coal, oil, gas, and all other goods

Dynamic Resource Extraction Module

  • Provides realistic fuel extraction modelling through dynamic forward-looking profit maximization
  • Accounts for all existing and estimated oil, gas, and coal resources in the world, split into 11 different subcategories of fuels – five for oil, four for gas, and two for coal
  • Differentiates between extraction with existing capacity and exploiting additional resources. The former depends on current fuel price and marginal extraction cost, while the latter involves investment in extraction capacity if the project is found viable given levelised cost of extraction and expected future fuel prices
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