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Sino-Venezuelan oil-for-loan deal – the Chinese strategic gamble?#

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  • Wang, Qiang
  • Li, Rongrong

Abstract

In a bid to secure oil resources for its expanding economy, China has developed a new model of bilateral oil finance, called “oil-for-loan.” Venezuela is a test case for the ability of China to pursue its oil-for-loan strategy. Venezuela has the largest proven oil reserves in the world, and China has loaned over US $50 billion to Venezuela. A case study of Sino-Venezuelan oil-for-loan deals not only can provide policy implications for the Sino-Venezuelan oil-for-loan project, but it can also provide a policy discussion about China's oil-for-loan strategy. To this end, we first give an outline of the evolution of the Sino-Venezuelan oil-for-loan deal. And then, we explain why there was such an interest and how both parties theoretically benefited from oil-for-loan deal. Next, we analyze the risks of the Sino-Venezuela oil-for-loan deal before and after the sharp drop in oil prices of 2014. Before 2014, the Sino-Venezuelan deal had been China's high-stakes game. Venezuela has had difficulties in meeting both its repayment and oil obligations since the oil-for-loan deal was implemented, because Venezuela's oil output has steadily declined since Hugo Chávez became president in 1999. After 2014, the falling oil prices have made Sino-Venezuelan oil-for-loan deal become China's high-stakes gamble. The falling oil prices since June 2014 have heavily weakened the Venezuelan economy and it may trigger social and political unrest, which might lead Venezuela to default on its loan. Finally, we propose policy recommendations for China and Venezuela to reach win-win game.

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  • Wang, Qiang & Li, Rongrong, 2016. "Sino-Venezuelan oil-for-loan deal – the Chinese strategic gamble?#," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 817-822.
    • Handle: RePEc:eee:rensus:v:64:y:2016:i:c:p:817-822
    DOI: 10.1016/j.rser.2016.06.042
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    6. Jiefang Dong & Chun Deng & Rongrong Li & Jieyu Huang, 2016. "Moving Low-Carbon Transportation in Xinjiang: Evidence from STIRPAT and Rigid Regression Models," Sustainability, MDPI, vol. 9(1), pages 1-15, December.

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