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Stockpile strategy for China׳s emergency oil reserve: A dynamic programming approach

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  • Bai, Y.
  • Dahl, C.A.
  • Zhou, D.Q.
  • Zhou, P.

Abstract

China is currently accelerating construction of its strategic petroleum reserves. How should China fill the SPR in a cost-effective manner in the short-run? How might this affect world oil prices? Using a dynamic programming model to answer these questions, the objective of this paper is to minimize the stockpiling costs, including consumer surplus as well as crude acquisition and holding costs. The crude oil acquisition price in the model is determined by global equilibrium between supply and demand. Demand, in turn, depends on world market conditions including China׳s stockpile filling rate. Our empirical study under different market conditions shows that China׳s optimal stockpile acquisition rate varies from 9 to 19 million barrels per month, and the optimal stockpiling drives up the world oil price by 3–7%. The endogenous price increase accounts for 52% of total stockpiling costs in the base case. When the market is tighter or the demand function is more inelastic, the stockpiling affects the market more significantly and pushes prices even higher. Alternatively, in a disruption, drawdown from the stockpile can effectively dampen soaring prices, though the shortage is likely to leave the price higher than before the disruption.

Suggested Citation

  • Bai, Y. & Dahl, C.A. & Zhou, D.Q. & Zhou, P., 2014. "Stockpile strategy for China׳s emergency oil reserve: A dynamic programming approach," Energy Policy, Elsevier, vol. 73(C), pages 12-20.
  • Handle: RePEc:eee:enepol:v:73:y:2014:i:c:p:12-20
    DOI: 10.1016/j.enpol.2014.05.042
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    Cited by:

    1. Yu, Shiwei & Gao, Siwei & sun, Han, 2016. "A dynamic programming model for environmental investment decision-making in coal mining," Applied Energy, Elsevier, vol. 166(C), pages 273-281.
    2. Xie, Nan & Yan, Zhijun & Zhou, Yi & Huang, Wenjun, 2017. "China's optimal stockpiling policies in the context of new oil price trend," Energy Policy, Elsevier, vol. 105(C), pages 332-340.
    3. Sun, Xiaolei & Liu, Chang & Chen, Xiuwen & Li, Jianping, 2017. "Modeling systemic risk of crude oil imports: Case of China’s global oil supply chain," Energy, Elsevier, vol. 121(C), pages 449-465.
    4. repec:eee:enepol:v:117:y:2018:i:c:p:25-38 is not listed on IDEAS

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