Understanding the Crude Oil Price: How Important Is the China Factor?

Abstract

This paper employs monthly data on China’s net oil import from January 1997 to June 2010 to assess the role of China’s net import in the evolution of the crude oil price. Based on a vector autoregression (VAR) analysis, we find that the growth of China’s net oil import has no significant impact on monthly oil price changes and there is no Granger causality between the two variables. The historical decomposition indicates that shocks to China’s oil demand have only played a small role in the oil price run-up of 2002-2008. We also calculate the price changes implied by China’s net oil import growth from a longer-term supply and demand shift perspective. doi: 10.5547/ISSN0195-6574-EJ-Vol32-No4-4

“Surging Chinese demand is underpinning the recent spike in the price of oil, figures from the International Energy Agency (IEA) show. This ‘China factor’ has more bearing on oil prices than the ‘risk factor’ coming from global tensions, some experts say”

—CNN (2004)

“The price of crude oil could soar to $200 a barrel in as little as six months, as supply continues to struggle to meet demand . . . Soaring global demand for oil is being led by China’s

Keywords

China Oil Price VAR historical decomposition Granger causality

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References

Ashley

Richard

Haichun

(2010). “On the Granger causality between median inflation and price dispersion.” Working paper, Department of Economics at Virginia Tech University.

Bai

Perron

(1998). “Testing for and Estimation of Multiple Structural Changes”, Econo-metrica 66: 47-79.

BBC (2008). “Oil Price May Hit $200 a Barrel”, May 7, 2008, http://news.bbc.co.uk/1Zhi/business/7387203.stm (accessed Sep 10, 2010)

Clark

Todd

McCracken

Michael

(2001). “Test of Equal Forecast Accuracy and Encompassing for Nested Models.” Journal of Econometrics 105(1): 85-110.

Clark

Todd

West

Kenneth

(2006). “Using Out-of-Sample Mean Squared Prediction Errors to Test the Martingale Difference Hypothesis.” Journal of Econometrics 135(1-2): 155-186.

Clark

Todd

West

Kenneth

(2007). “Approximately Normal Tests for Equal Predictive Accuracy in Nested Models.” Journal of Econometrics 138(1): 291-311.

CNN (2004). “China factor driving oil prices”, May 24, 2004, http://edition.cnn.com/2004/BUSI-NESS/05/24/china.oil.demand/index.html (accessed Sep 15, 2010)

Gonclaves

Silvia

Killian

Lutz

(2004). “Bootstrapping Autoregressions with Conditional Het-eroskedasticity of Unknown Form.” Journal of Econometrics 123(1): 89-120.

Granger

Clive

Newbold

Paul

(1976). “Forecasting Transformed Series.” Journal of the Royal Statistical Society Series B 38(2): 189-203.

10.

Hamilton

James

(2009a). “Understanding Crude Oil Prices.” The Energy Journal 30(2): 179-206.

11.

Hamilton

James

(2009b) “Causes and Consequences of the Oil Shock of 2007-08” Brookings Papers on Economic Activity, Spring 2009, 215-261.

12.

Killian

Lutz

(2009). “Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market” American Economic Review 99(3): 1053-1069.

13.

Krichene

Noureddine

(2002) “World Crude Oil and Natural Gas: A Demand and Supply Model.” Energy Economics, 24(6): 557-576.

14.

McCracken

Michael W.

(2007). “Asymptotics for Out of Sample Tests of Granger Causality.” Journal of Econometrics 140(2): 719-752.

15.

Smith

James

(2009). “World Oil: Market or Mayhem?” Journal of Economic Perspectives, 23(3): 145-164.

16.

US Congressional Budget Office (2006). “China’s Growing Demand for Oil and Its Impact of U.S. Petroleum Markets”. http://www.cbo.gov/ftpdocs/71xx/doc7128/04-07-ChinaOil.pdf (accessed Sep 13, 2010)