Systematic bias in EIA oil price forecasts: Concerns and consequences ///

Over the past decade, EIA projections differ substantially from actual oil prices. Further, Gately (2001; 2007)1 has suggested that the EIA National Energy Modeling System (NEMS) is “internally inconsistent” and routinely forecasts oil prices which are “far too low.” A review of the data provides strong support for Gately’s criticism. Since 1998, of 45 annual forecasts from the EIA, 42 (93%) have under-predicted the price of oil. To statistically assess the situation, we conducted an error decomposition analysis of EIA projections of oil prices from 1998-2006. Error decomposition is commonly used to evaluate economic forecasting models by identifying three sources of error: random chance, linear bias and model bias. The statistical analysis revealed: 1. The root mean squared error of the one-to-four-year EIA forecast of oil prices averages over 30% and ranges as high as 46%. 2. These forecast errors are not reflective of random chance...

Log in to view this article.

Not yet a subscriber?  Get started now for access to this content and more*.



Already a subscriber but don’t have an online account? Contact our customer service.



*Access will be granted the next business day.