IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v93y2015ip2p1353-1360.html
   My bibliography  Save this article

Oil price crisis response: Capability assessment and key indicator identification

Author

Listed:
  • Ju, Keyi
  • Su, Bin
  • Zhou, Dequn
  • Zhou, P.
  • Zhang, Yuqiang

Abstract

China has become the second largest oil consumer and oil importer since 2008. In the context of sustained highly frequent fluctuating oil price, China's oil price crisis response system has been seriously threatened. Twelve indicators of four domains called economic stability, political stability, oil import dependence, as well as oil consumption dependence are used to construct “OPCVI (Oil Price Crisis Vulnerability Index)” system, to estimate China's response capability of oil price crisis. MDEA (Multiplicative Data Envelopment Analysis) is used to identify the weights of each indicator and appraise the OPCVI values between 1993 and 2013. Results show that, oil consumption intensity, GDP(Gross Domestic Product) per capita and the ratio of oil import expenditure to GDP are the three key indicators for China's oil price crisis response capability. China's OPCVI became weak since 2000. This is mainly because that the contribution of positive indicators to OPCVI gradually reduced while the contributions of negative indicators increased. Additionally, the contributions of the key indicators of OPCVI are so concentrated and lack of flexibility that it can easily make China's oil price crisis response capability fall into a dangerous situation. Finally, policy recommendations for enhancing the oil price crisis response capability of China are given.

Suggested Citation

  • Ju, Keyi & Su, Bin & Zhou, Dequn & Zhou, P. & Zhang, Yuqiang, 2015. "Oil price crisis response: Capability assessment and key indicator identification," Energy, Elsevier, vol. 93(P2), pages 1353-1360.
  • Handle: RePEc:eee:energy:v:93:y:2015:i:p2:p:1353-1360
    DOI: 10.1016/j.energy.2015.09.124
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S036054421501347X
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ebert, Udo & Welsch, Heinz, 2004. "Meaningful environmental indices: a social choice approach," Journal of Environmental Economics and Management, Elsevier, vol. 47(2), pages 270-283, March.
    2. Diaz-Balteiro, Luis & Romero, Carlos, 2004. "In search of a natural systems sustainability index," Ecological Economics, Elsevier, vol. 49(3), pages 401-405, July.
    3. Hatefi, S.M. & Torabi, S.A., 2010. "A common weight MCDA-DEA approach to construct composite indicators," Ecological Economics, Elsevier, vol. 70(1), pages 114-120, November.
    4. Michela Nardo & Michaela Saisana & Andrea Saltelli & Stefano Tarantola & Anders Hoffman & Enrico Giovannini, 2005. "Handbook on Constructing Composite Indicators: Methodology and User Guide," OECD Statistics Working Papers 2005/3, OECD Publishing.
    5. Yu, Lean & Wang, Zishu & Tang, Ling, 2015. "A decomposition–ensemble model with data-characteristic-driven reconstruction for crude oil price forecasting," Applied Energy, Elsevier, vol. 156(C), pages 251-267.
    6. Giuseppe Munda, 2005. "“Measuring Sustainability”: A Multi-Criterion Framework," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 7(1), pages 117-134, January.
    7. P. Zhou & B. Ang & D. Zhou, 2010. "Weighting and Aggregation in Composite Indicator Construction: a Multiplicative Optimization Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 96(1), pages 169-181, March.
    8. Ju, Keyi & Zhou, Dequn & Zhou, P. & Wu, Junmin, 2014. "Macroeconomic effects of oil price shocks in China: An empirical study based on Hilbert–Huang transform and event study," Applied Energy, Elsevier, vol. 136(C), pages 1053-1066.
    9. Brown, Stephen P.A. & Huntington, Hillard G., 2015. "Evaluating U.S. oil security and import reliance," Energy Policy, Elsevier, vol. 79(C), pages 9-22.
    10. Kruyt, Bert & van Vuuren, D.P. & de Vries, H.J.M. & Groenenberg, H., 2009. "Indicators for energy security," Energy Policy, Elsevier, vol. 37(6), pages 2166-2181, June.
    11. Cherchye, Laurens & Knox Lovell, C.A. & Moesen, Wim & Van Puyenbroeck, Tom, 2007. "One market, one number? A composite indicator assessment of EU internal market dynamics," European Economic Review, Elsevier, vol. 51(3), pages 749-779, April.
    12. Gnansounou, Edgard, 2008. "Assessing the energy vulnerability: Case of industrialised countries," Energy Policy, Elsevier, vol. 36(10), pages 3734-3744, October.
    13. Hope, Chris & Parker, Jonathan & Peake, Stephen, 1992. "A pilot environmental index for the UK in the 1980s," Energy Policy, Elsevier, vol. 20(4), pages 335-343, April.
    14. Zhou, P. & Ang, B.W. & Poh, K.L., 2006. "Comparing aggregating methods for constructing the composite environmental index: An objective measure," Ecological Economics, Elsevier, vol. 59(3), pages 305-311, September.
    15. Wang, H., 2015. "A generalized MCDA–DEA (multi-criterion decision analysis–data envelopment analysis) approach to construct slacks-based composite indicator," Energy, Elsevier, vol. 80(C), pages 114-122.
    16. Kang, Sang Mok, 2002. "A sensitivity analysis of the Korean composite environmental index," Ecological Economics, Elsevier, vol. 43(2-3), pages 159-174, December.
    17. Laurens Cherchye & Willem Moesen & Nicky Rogge & Tom Puyenbroeck, 2007. "An Introduction to ‘Benefit of the Doubt’ Composite Indicators," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 82(1), pages 111-145, May.
    18. Zhou, P. & Ang, B.W. & Poh, K.L., 2007. "A mathematical programming approach to constructing composite indicators," Ecological Economics, Elsevier, vol. 62(2), pages 291-297, April.
    19. Krajnc, Damjan & Glavic, Peter, 2005. "How to compare companies on relevant dimensions of sustainability," Ecological Economics, Elsevier, vol. 55(4), pages 551-563, December.
    20. Gnansounou, Edgard & Dong, Jun, 2010. "Vulnerability of the economy to the potential disturbances of energy supply: A logic-based model with application to the case of China," Energy Policy, Elsevier, vol. 38(6), pages 2846-2857, June.
    21. Charnes, A. & Cooper, W. W. & Seiford, L. & Stutz, J., 1982. "A multiplicative model for efficiency analysis," Socio-Economic Planning Sciences, Elsevier, vol. 16(5), pages 223-224.
    22. P. Zhou & B. Ang, 2009. "Comparing MCDA Aggregation Methods in Constructing Composite Indicators Using the Shannon-Spearman Measure," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 94(1), pages 83-96, October.
    23. Ozdemir, Zeynel Abidin & Gokmenoglu, Korhan & Ekinci, Cagdas, 2013. "Persistence in crude oil spot and futures prices," Energy, Elsevier, vol. 59(C), pages 29-37.
    24. Ang, B.W. & Choong, W.L. & Ng, T.S., 2015. "Energy security: Definitions, dimensions and indexes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 1077-1093.
    25. Hajkowicz, Stefan, 2006. "Multi-attributed environmental index construction," Ecological Economics, Elsevier, vol. 57(1), pages 122-139, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    2. repec:gok:ijdcv1:v:7:y:2017:i:2:p:97-118 is not listed on IDEAS
    3. Ju, Keyi & Su, Bin & Zhou, Dequn & Wu, Junmin & Liu, Lifan, 2016. "Macroeconomic performance of oil price shocks: Outlier evidence from nineteen major oil-related countries/regions," Energy Economics, Elsevier, vol. 60(C), pages 325-332.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:93:y:2015:i:p2:p:1353-1360. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.journals.elsevier.com/energy .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.