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Food versus crude oil: what do prices tell us? Evidence from China

Author

Listed:
  • Yumeng Wang
  • Shuoli Zhao
  • Zhihai Yang
  • Donald J. Liu

Abstract

Purpose - – The purpose of this paper is to investigate the causal relationship between the prices of rice, crude oil, wheat, corn and soybean in China and estimate the long-run and short-run price relationships. Design/methodology/approach - – Using monthly price date over the period of January 1998-December 2013 in China, this paper employs an autoregressive distributed lag (ARDL) bounds test to explore the cointegration relationship among the price variables and estimate the ARDL long-run price relationship and the short-run error correction process (ARDL-EC). Findings - – The empirical results indicate that crude oil, as one of the forcing variables along with wheat, corn, and soybean prices, is effecting rice price in China. Both the long-run and short-run price transmission elasticity estimates suggest the importance of crude oil price on the formation of rice prices. Furthermore, the adjustment speed coefficient is found to be statistically significant, supporting the notion that there is an error correction mechanism for maintaining the long-run price relationship facing short-run shocks. Originality/value - – This paper adopts four types of commodity food prices to explore the relationships with crude oil price. The evidence of market integration, including the degree of price transmission and the speed of adjustment, remains a crucial step to proceed with the government intervention.

Suggested Citation

  • Yumeng Wang & Shuoli Zhao & Zhihai Yang & Donald J. Liu, 2015. "Food versus crude oil: what do prices tell us? Evidence from China," China Agricultural Economic Review, Emerald Group Publishing Limited, vol. 7(3), pages 435-447, September.
    • Handle: RePEc:eme:caerpp:v:7:y:2015:i:3:p:435-447
    DOI: 10.1108/CAER-09-2014-0091
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    Cited by:

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    3. You, Siming & Neoh, Koon Gee & Tong, Yen Wah & Dai, Yanjun & Wang, Chi-Hwa, 2017. "Variation of household electricity consumption and potential impact of outdoor PM2.5 concentration: A comparison between Singapore and Shanghai," Applied Energy, Elsevier, vol. 188(C), pages 475-484.

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