The Future of Oil: Geology versus Technology
The Future of Oil: Geology versus Technology
Future oil prices have been notoriously difficult to predict. In a recent paper, Alquist, Kilian, and Vigfusson (2011) conclude that forecasts based on monthly futures prices, monthly surveys of forecasts, simple econometric models, or other commonly employed forecasting techniques cannot consistently beat a random-walk forecast out of sample. This result is well known within the oil industry.
The simple econometric models used by Alquist, Kilian, and Vigfusson (2011) emphasize macroeconomic indicators as predictors of future oil prices. These indicators are highly correlated with fluctuations in aggregate demand, and will therefore mainly capture changes in the price of oil caused by variations in demand. But they are unlikely to be effective in capturing temporary oil supply disruptions. Moreover, since aggregate demand tends to revert to a trend, these variables are not likely to be successful in predicting a long-lasting increase in the price of oil such as the one we have recently observed.
However, there is an alternative explanation for the recent persistent price movements that, despite considerable evidence in its support, has received very little attention in the economics literature. This is that one key driver of recent events may have been a highly persistent or even permanent shock to oil supply that is due to geological limits on the oil industry’s ability to maintain the historical growth rate of production. The extent to which the literature discounts or embraces this possibility is critical for its interpretation of recent events in the oil markets.
Kilian (2009), in analyzing the U.S. economy, distinguishes between three drivers of oil prices, aggregate demand for goods, precautionary demand for oil, and supply of oil, where the latter captures only the possibility of temporary supply disruptions due to political events in oil producers, the dominant supply shock in historical data. He finds that the two demand shocks have been far more important as drivers of oil prices, while supply shocks have had a negligible effect. Kilian’s (2009) analysis does not allow for the possibility of highly persistent shocks to the supply of oil that are driven by terminal geological limits.
Hamilton (2009), on the other hand, finds that temporary disruptions in physical oil supply have already had a major role in explaining historical dynamics of oil price movements. And furthermore, he argues that stagnating world oil production, meaning a very persistent reduction in oil supply growth, may have been one of the reasons for the run-up in oil prices in 2007-08. The main reasons why oil supply shocks affect output
according to Hamilton is their disruptive effect on key industries such as automotive manufacturing, and their effect on consumers’ disposable incomes. In other words, the main effect is on aggregate demand. As for aggregate supply effects, his view is that there may be short-run impacts due to very low short-run elasticities of substitution between oil and other factors of production. But he assumes that such elasticities get larger over longer horizons, as agents find possibilities to substitute away from oil. This is because high prices start to stimulate technological change that can both increase the recovery of oil, and the availability of substitutes for oil. Therefore, even though Hamilton is closest among mainstream economists to seeing real problems emanating from the physical, geological availability of oil, he nevertheless subscribes to the economic or technological view whereby prices must eventually have a decisive impact on production levels.
This is where he parts company with proponents of the geological view of future oil production, who suggest that oil reserves are ultimately finite, easy-to-access oil is produced first, and therefore oil must become harder and more expensive to produce as the cumulated amount of oil already produced grows. According to many scientists in this group, the recently observed stagnant oil production in the face of persistent and large oil price increases is a sign that physical scarcity of oil is already here, or at least imminent, and that it must eventually overwhelm the stimulative effects of higher prices.
Furthermore they state, on the basis of extensive studies of alternative technologies and resources, that suitable substitutes for oil simply do not exist on the required scale, and that technologies to improve oil recovery must eventually run into limits dictated by the laws of thermodynamics, specifically entropy. This view of oil supply traces its origins back to the work of M. King Hubbert (1956), a geoscientist who in 1956 correctly predicted that U.S. oil output would peak in 1970. It is discussed in a study for the U.S. Department of Energy1, Hirsch et al. (2005), and in a subsequent book, Hirsch et al. (2010). The most thorough research available on this topic is UK Energy Research Centre (2009), which is succinctly summarized in Sorrell et al. (2010). Based on a wealth of geological and engineering evidence, these authors conclude that there is a significant risk of a peak in conventional oil production before 2020, with an inexorable decline thereafter.
In this paper we find that our ability to forecast future developments in the oil market, and by implication in aggregate activity, can be dramatically improved by combining the geological and economic/technological views of oil supply, and by estimating their respective contributions. We develop a simple macroeconomic model that combines a conventional linear demand specification with a nonlinear supply equation, the latter combining a mathematical formalization of the geological view with a conventional price sensitive oil production. We find that this model can predict oil prices far better out of sample than a random walk, and that it can predict oil production far better than the historical track record of official energy agencies on the one hand, and of advocates of pure versions of the geological view on the other hand. We also use the model to identify which driving force has been most responsible for the recent run-up in oil prices. We find that the geological, price-insensitive component of supply is the key reason for the recent accuracy of the model’s predictions because it captures the underlying trend in prices.
But we also find that shocks to excess demand for goods and to demand for oil, the latter probably due to phenomenal recent growth in China and India, have been key to explaining persistent and sizeable deviations from that trend. These deviations work through the price channel. Looking into the future, both of these factors continue to be important, and point to a near doubling of real oil prices over the coming decade. But there is substantial uncertainty about these future trends that are rooted in our fundamental lack of knowledge, based on current data, about ultimately recoverable oil reserves, and about long-run price elasticities of oil demand and supply. The rest of the paper is organized as follows. Section II presents data on historical oil supply forecasts by proponents of the technological and geological views. Section III presents and discusses the model specification and parameter estimates. Section IV presents a detailed analysis of the estimation results. Section V concludes.
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