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Energy and Economy: Global Interdependences

William W. Hogan

Year: 1985
Volume: Volume 6
Number: Number 4
DOI: 10.5547/ISSN0195-6574-EJ-Vol6-No4-2
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Abstract:
This meeting, the Seventh International Conference of the International Association of Energy Economists (IAEE), finds us again in the midst of transitions in energy markets. Continued adjustments in oil demand, natural gas bubbles in Europe and North America, closures of refineries, and concerns about acid rain are just a few of the issues that reflect the turbulence and continued change in energy concerns and policy. This list of challenges suggests opportunities for energy economists to contribute their special perspectives to the clarification of issues and options. At an international conference, we can reinforce communications across national boundaries as we consider our related problems.



Futures Prices are Useful Predictors of the Spot Price of Crude Oil

Reinhard Ellwanger and Stephen Snudden

Year: 2023
Volume: Volume 44
Number: Number 4
DOI: 10.5547/01956574.44.4.rell
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Abstract:
How well do futures prices forecast the spot price of crude oil? Contrary to the established view, futures prices significantly improve upon the accuracy of monthly no-change forecasts. This results from two innovations. First, we document that independent of the construction of futures-based forecasts, longer-horizon futures prices have become better predictors of crude oil spot prices since the mid-2000s. Second, we show that futures curves constructed using end-of-month prices instead of average prices have consistently been able to generate large accuracy-improvements for short-horizon forecasts of average prices. These findings are remarkably robust and apply to all major crude oil benchmarks.



Evaluating Oil Price Forecasts: A Meta-analysis

Michail Filippidis, George Filis, and Georgios Magkonis

Year: 2024
Volume: Volume 45
Number: Number 2
DOI: 10.5547/01956574.45.2.mfil
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Abstract:
Oil price forecasts have traditionally attracted the interest of both the empirical literature and policy makers, although research efforts have been intensified in the last 15 years. The present study investigates the forecasting characteristics that have the greatest impact on the accuracy level of such forecasts. To achieve this, we employ a meta-analysis approach of more than 6,000 observations of relative root mean squared errors (RRMSEs) which are pooled within a Bayesian Model Averaging (BMA) method. The findings indicate that forecasting frameworks such as MIDAS and combined forecasts tend to report significantly lower forecast errors. In addition, the choice of the oil price benchmark is an important factor, with the Brent price to offer lower forecast errors. Furthermore, the short-run horizons tend to produce more accurate forecasts and the same holds for the real, instead of the nominal oil prices. A number of robustness tests confirms the validity of these results. Overall, the findings of this study serve as a guide for future oil price forecasting exercises.





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