The ACEGES laboratory for energy policy: Exploring the production of crude oil

An agent-based computational laboratory for exploratory energy policy by means of controlled computational experiments is proposed. It is termed the ACEGES (agent-based computational economics of the global energy system). In particular, it is shown how agent-based modelling and simulation can be applied to understand better the challenging outlook for oil production by accounting for uncertainties in resource estimates, demand growth, production growth and peak/decline point. The approach emphasises the idea that the oil system is better modelled not as black-box abode of ‘the invisible hand’ but as a complex system whose macroscopic explananda emerges from the interactions of its constituent components. Given the estimated volumes of oil originally present before any extraction, simulations show that on average the world peak of crude oil production may happen in the broad vicinity of the time region between 2008 and 2027. Using the proposed petroleum market diversity, the market diversity weakness rapidly towards the peak year.     

Can reserve additions in mature crude oil provinces attenuate peak oil?

Following the peak in US crude oil production 30 years ago, more and more non-OPEC producers have seen their production decline as a result of resource depletion. OPEC, on the other hand has extracted a comparatively smaller proportion of its reserve base. Given that new non-OPEC discoveries are growing ever limited, we explore the role of reserve additions and OPEC in determining future crude oil supply: we formulate a model that embodies a weak and strong OPEC for various rates of reserve additions in mature crude oil provinces. Using this geo-economic partial equilibrium model that generates a peak in crude oil production, we show that although potential conventional crude oil resources may seem abundant, OPEC strategy could cause substantial crude oil reserve depletion in non-OPEC countries by 2050 (or even earlier) given likely depletion rates. In addition, we find that reducing reserve decline rates in mature crude oil provinces not only extends the time to exhaustion substantially, but also discourages OPEC from engaging in an overly strategic extraction behavior.     

Peak oil: The four stages of a new idea

The present paper reviews the reactions and the path of acceptance of the theory known as “peak oil”. The theory was proposed for the first time by M.K. Hubbert in the 1950s as a way to describe the production pattern of crude oil. According to Hubbert, the production curve is “bell shaped” and approximately symmetric. Hubbert's theory was verified with good approximation for the case of oil production in the United States that peaked in 1971, and is now being applied to the worldwide oil production. It is generally believed that the global peak of oil production (“peak oil”) will take place during the first decade of the 21st century, and some analysts believe that it has already occurred in 2005 or 2006. The theory and its consequences have unpleasant social and economical implications. The present paper is not aimed at assessing the peak date but offers a discussion on the factors that affect the acceptance and the diffusion of the concept of “peak oil” with experts and with the general public. The discussion is based on a subdivision of “four stages of acceptance”, loosely patterned after a sentence by Thomas Huxley.     

Rational destabilizing speculation,positive feedback trading,and the oil bubble of 2008

This article examines how the interaction of different participants in the crude oil futures markets affects the crude oil price efficiency. Normally, the commercial market participants, such as oil producers and oil consumers, act as arbitrageurs and ensure that the price of crude oil remains within the fundamental value range. However, institutional investors that invest in crude oil to diversify their portfolios and/or hedge inflation can destabilize the interaction among commercial participants and liquidity-providing speculators. We argue that institutional investors can impose limits to arbitrage, particularly during the financial crisis when the investment demand for commodities is particularly strong. In support, we show that commercials hedgers had significantly reduced their short positions leading to the 2008 oil bubble—they were potentially aggressively offsetting their short hedges. As a result, by essentially engaging in a positive feedback trading, commercial hedgers at least contributed to ‘the 2008 oil bubble'. These findings have been mainly overlooked by the existing research.     

Non-linear unit root properties of crude oil production

While there is good reason to expect crude oil production to be non-linear, previous studies that have examined the stochastic properties of crude oil production have assumed that crude oil production follows a linear process. If crude oil production is a non-linear process, conventional unit root tests, which assume linear and systematic adjustment, could interpret departure from linearity as permanent stochastic disturbances. The objective of this paper is to test for non-linearities and unit roots in crude oil production. To realize our objective, this study applies a threshold autoregressive model with an autoregressive unit root to monthly crude oil production for 17 OPEC and non-OPEC countries over the period January 1973 to December 2007. Specifically, first we test for the presence of non-linearities (threshold effects) in the production of crude oil in two regimes. Second, we test for a unit root against a non-linear stationary process in two regimes and a partial unit root process when the unit root is present in one regime only. We find that crude oil production is characterized by threshold effects. We find that for eleven of the countries a unit root was present in both regimes, while for the others a partial unit root was found to be present in either the first regime or second regime.     

Forecasting oil price movements with crack spread futures

In oil markets, the crack spread refers to the crude–product price relationship. Refiners are major participants in oil markets and they are primarily exposed to the crack spread. In other words, refiner activity is substantially driven by the objective of protecting the crack spread. Moreover, oil consumers are active participants in the oil hedging market and they are frequently exposed to the crack spread. From another perspective, hedge funds are heavily using crack spread to speculate in oil markets. Based on the high volume of crack spread futures trading in oil markets, the question we want to raise is whether the crack spread futures can be a good predictor of oil price movements. We investigated first whether there is a causal relationship between the crack spread futures and the spot oil markets in a vector error correction framework. We found the causal impact of crack spread futures on spot oil market both in the long- and the short-run after April 2003 where we detected a structural break in the model. To examine the forecasting performance, we use the random walk model (RWM) as a benchmark, and we also evaluate the forecasting power of crack spread futures against the crude oil futures. The results showed that (a) both the crack spread futures and the crude oil futures outperformed the RWM; and (b) the crack spread futures are almost as good as the crude oil futures in predicting the movements in spot oil markets.     

A variant of the Hubbert curve for world oil production forecasts

In recent years, the economic and political aspects of energy problems have prompted many researchers and analysts to focus their attention on the Hubbert Peak Theory with the aim of forecasting future trends in world oil production.In this paper, a model that attempts to contribute in this regard is presented; it is based on a variant of the well-known Hubbert curve. In addition, the sum of multiple-Hubbert curves (two cycles) is used to provide a better fit for the historical data on oil production (crude and natural gas liquid (NGL)).Taking into consideration three possible scenarios for oil reserves, this approach allowed us to forecast when peak oil production, referring to crude oil and NGL, should occur.In particular, by assuming a range of 2250–3000 gigabarrels (Gb) for ultimately recoverable conventional oil, our predictions foresee a peak between 2009 and 2021 at 29.3–32.1 Gb/year.     

The end of cheap oil: Current status and prospects

This paper, analyses the factors impacting the price of crude oil in order to examine the likely evolution of the oil market and attempts to answer the question, whether cheap oil is already a thing of the past. Based on data made publicly available mostly by the major oil companies, it examines the effects of demand and supply, the evolution of world oil reserves, the trends in new discoveries of new oilfields, the evolution of world Gross Domestic Product (GDP), and the depletion of oil resources. The analysis concludes that the world peak in conventional oil production—the point beyond which oil production will irreversibly start declining—is approaching and will be reached, even according to the most optimistic scenarios, before 2040 and quite possibly much sooner. If the appropriate solutions for substituting crude oil and for conserving the use of energy are not implemented in time, then the current upward trend in oil prices is bound to continue.     

Multiscale entropy analysis of crude oil price dynamics

Price formation in crude oil markets is the result of the action of many participants (e.g., producers, governments, speculators, etc.) whose effects are perceived at different time scales, from days to years. The diversity of participants as well as the occurrence of extreme socio-political events yields a market with complex price evolution. This paper uses entropy methods to monitor the evolution of crude oil price movements. As the complexity of the price can depend of the time horizon, entropy computations are performed for different time scales via low-pass filtering of the price difference dynamics. The results are interpreted in term of relative market efficiency concepts in the sense that high entropy values should be related to a more complex and, hence, less predictable market evolution. It is shown that the highest market efficiency is found for small time scales up to one or two weeks. The multiscale entropy pattern for high time scales, longer than one quarter, is interesting as it shows alternating periods of high and low entropy levels. Interestingly, this alternating pattern has a dominant spectral component of about 4.3 years, which could be related to macroeconomic (Kitchin) business cycles. It is shown that U.S. recessions in the recent 25 years are coincident with periods of reduced entropy levels, meaning that during economic downturn the long-run market complexity is drastically reduced. The possible effects of extreme events (e.g., Iraq War) are analyzed in terms of the relative market efficiency, suggesting that some events have affected the short-term but not the long-term market complexity. Overall, these results show that methods based on entropy concepts can shed light on the structure of crude oil markets as well as on its link to macroeconomic conditions and socio-political extreme events.     

OPEC vs US shale: Analyzing the shift to a market-share strategy

In November 2014, OPEC announced a new strategy geared towards improving its market share. Oil-market analysts interpreted this as an attempt to squeeze higher-cost producers, notably US shale oil, out of the market. Over the next year, crude oil prices crashed, with large repercussions for the global economy. We present a simple equilibrium model that explains the fundamental market factors that can rationalize such a “regime switch” by OPEC: (i) the growth of US shale oil production; (ii) the slowdown of global oil demand; (iii) reduced cohesiveness of the OPEC cartel; and (iv) production ramp-ups in other non-OPEC countries; while (v) reductions in US shale costs act against these factors. We show that these qualitative predictions are broadly consistent with oil market developments during 2014–2015. The model is calibrated to oil market data; it predicts accommodation up to 2014 and a market-share strategy thereafter, and explains large oil-price swings as well as realistically high levels of OPEC output.     

Retail fuel price adjustment in Germany: A threshold cointegration approach

Consumers in Germany often complain that retail fuel prices usually adjust quickly to crude oil price increases than decreases and characterize this pricing pattern as market power exploitation. In this paper, we use both weekly national and daily city-specific (Berlin, Hamburg, Munich and Cologne) data to investigate the extent to which retail fuel prices in Germany adjust to changes in the international crude oil price. At the national level with weekly prices, we find positive asymmetries for both gasoline and diesel within the period 2003–2007, reflecting that retail prices react more swiftly to crude oil price increases than decreases. In contrast, for 2009–2013, we observe symmetric adjustment and negative asymmetry for retail diesel and gasoline prices, respectively. The city level analysis supports our findings in the latter time period. Thus, regulatory measures aimed at the retail fuel market over recent years seem to have been effective, and, contrary to consumers' perception, we find no evidence for excessive market power or collusion.     

Market integration among electricity markets and their major fuel source markets

Dynamic price information flows among U.S. electricity wholesale spot prices and the prices of the major electricity generation fuel sources, natural gas, uranium, coal, and crude oil, are studied. Multivariate time series methods applied to weekly price data show that in contemporaneous time peak electricity prices move natural gas prices, which in turn influence crude oil. In the long run, price is discovered in the fuel sources market (except uranium), as these prices are weakly exogenous in a reduced rank regression representation of these energy prices.     

Crude oil price analysis and forecasting: A perspective of “new triangle”

In this paper, the new structural characteristics and core influencing factors of the crude oil prices are summarized based on previous representative research results. Firstly, a newly dynamic Bayesian structural time series model (DBSTS) is developed to investigate the oil prices. In particular, Google trend is introduced as an indicator to reflect the impact of search data on the oil price. Secondly, the spike and slab method is employed to select core influence factors. Finally, the Bayesian model average (BMA) is utilized to predict the oil price. Experimental results confirm that the supply and demand of global crude oil and the financial market are still the main factors affecting the oil price. Furthermore, Google trend can reflect the changes in the crude oil price to a certain extent. Moreover, the impact of shale oil production on the oil price is gradually increasing, yet remains relatively small. In addition, the DBSTS model can identify turning points in historical data (such as the 2008 financial crisis). Finally, the findings suggest the DBSTS model has good predictive capabilities in short-term prediction, making it suitable for analyzing the crude oil prices.     

Worldwide cheap and heavy oil productions: A long-term energy model

Crude oil, natural gas liquids, heavy oils, deepwater oils, and polar oils are non-renewable energy resources with increasing extraction costs. Two major definitions emerge: regular or ‘cheap’ oil and non-conventional or ‘heavy’ oil. Peaking time in conventional oil production has been a recent focus of debate. For two decades, non-conventional oils have been mixed with regular crude oil. Peaking time estimation and the rate at which production may be expected to decline, following the peak, are more difficult to determine. We propose a two-wave model for world oil production pattern and forecasting, based on the diffusion of innovation theories: a sequential multi-Bass model. Historical well-known shocks are confirmed, and new peaking times for crude oil and mixed oil are determined with corresponding depletion rates. In the final section, possible ties between the dynamics of oil extraction and refining capacities are discussed as a predictive symptom of an imminent mixed oil peak in 2016.     

OPEC and demand response to crude oil prices

This paper investigates demand response to crude oil price movements before and after the recent global financial and economic crisis. It employs several market power indices to structurally estimate price elasticities. A newly developed market power index for crude oil markets is implemented. In this approach OPEC is the central player and acts as a dominant producer in the global oil market. We quantify how a change in market structure (such as changes in marginal cost of production) would contribute to market power exercise of OPEC and have an ultimate impact on price elasticity of demand for oil. Our price elasticity predictions fall in a range reported in the literature, however estimates for pre-crisis deviate from the post-crisis ones. In fact, demand response to crude oil prices has almost doubled during the crisis. This severe change in price response can be associated with record price levels caused by supply shortages and surge in alternative renewable energy resources. The key advantages of this methodology over the existing literature are that it is simple to use and estimates price elasticity using a competition framework without specifying demand/supply function(s), and utilizes commonly observable market variables that can be applied to any admissible data frequency.     

通过匹配原油计价量与加工量规避原油计价风险的探讨

进口原油具有的贸易特点及计价方法,与炼油企业当期销售成品油的计价方法不同,造成原油与成品油计价期不同,在国际油价剧烈波动,特别是油价快速下跌时,使炼油企业严重亏损。当企业均衡生产时,这种时间差带来的市场风险会通过装置长周期运行而减小,但当企业的加工和采购进度因装置检修、非计划停工以及市场供需调整等原因进行大幅调整时,成本和产品价格之间的时间差可能会给企业带来巨大风险。分别介绍了进口原油、成品油的贸易特点及计价方法,提出了如何研究国际油价走势。分析了国际油价上涨时,如何选择原油计价期,实现低价采购原油、高价销售成品油的目标;国际油价下跌时,如何实现同期原油计价量与原油加工量匹配,实现均衡计价,规避因国际油价波动造成的企业亏损,进一步剖析了如何运用套期保值方法,锁定当期炼油企业原油加工效益。同时,列举了操作中的注意事项,提出套期保值应善于选择时机操作,加强计划管理的重要性,以及控制合理库存的必要性。     

Crude oil price uncertainty and corporate investment: New global evidence

Using a comprehensive dataset of more than 33,000 firms from 54 countries in the period 1984–2015, we show that crude oil price uncertainty negatively influences corporate investment. More importantly, the effect is dependent on the market and stock characteristics of the firms. In addition, we discover that the effect is stronger in the crude oil producers group than for crude consumers. Our analysis reveals that the global financial crisis and market volatility phases significantly affect this relationship. Our results survive a range of robustness tests.     

System dynamics model of Hubbert Peak for China's oil

 American geophysicist M. King Hubbert in 1956 first introduced a logistic equation to estimate the peak and lifetime production for oil of USA. Since then, a fierce debate ensued on the so-called Hubbert Peak, including also its methodology. This paper proposes to use the generic STELLA model to simulate Hubbert Peak, particularly for the Chinese oil production. This model is demonstrated as being robust. We used three scenarios to estimate the Chinese oil peak: according to scenario 1 of this model, the Hubbert Peak for China's crude oil production appears to be in 2019 with a value of 199.5 million tonnes, which is about 1.1 times the 2005 output. Before the peak comes, Chinese oil output will grow by about 1–2% annually, after the peak, however, the output will fall. By 2040, the annual production of Chinese crude oil would be equivalent to the level of 1990. During the coming 20 years, the crude oil demand of China will probably grow at the rate of 2–3% annually, and the gap between domestic supply and total demand may be more than half of this demand.     

The price of oil: Lower and upper bounds

The magnitude of the recent dramatic fall in oil prices has once again (like the rises of 1973 and 1979) taken most energy analysts and oil industry participants by suprise, creating even greater uncertainty about future developments in the oil market. In this paper, we suggest that a return to first principles is appropriate at this time in order to help clarify the outlook. Two simple Hotelling-type models of the oil market are described - one of the perfectly competitive market, the other of a purely monopolistic market. These two models are used to derive lower and upper bounds on oil prices. A reinterpretation of the history of the oil market over the last 25 years is suggested, with some implications for the future course of oil prices.     

The role of transnational companies as oil suppliers to the United States

This paper analyzes the extent to which the international oil production of transnational companies meets the oil requirements of the United States. Disaggregated data from each company have been used to determine which companies (refineries) are importing crude oil, how much oil each transnational company is produced abroad, and where this production goes to. The analysis show that American international oil production represents a small part of U.S. oil imports. Two conclusions are reached. The first is that U.S. refineries buy the majority of the crude oil they process on the international market and, as a result, are dependent on the unstable conditions of this market. The second is that the economic interests the large American oil companies have abroad are far greater than those they have within the United States and, as a result, these companies do not play a decisive role in a national strategy to guarantee foreign supply.