Estimation on oil demand and oil saving potential of China's road transport sector
China is currently in the stage of industrialization and urbanization, which is characterized by rigid energy demand and rapid growth of energy consumption. Therefore, energy conservation will become a major strategy for China in a transition to low-carbon economy. China's transport industry is of high energy consumption. In 2010, oil consumption in transport industry takes up 38.2% of the country's total oil demand, of which 23.6% is taken up by road transport sector. As a result, oil saving in China's road transport sector is vital to the whole nation. The co-integration method is developed to find a long-run relationship between oil consumption and affecting factors such as GDP, road condition, labor productivity and oil price, to estimate oil demand and to predict future oil saving potential in China's transport sector under different oil-saving scenarios. Monte Carlo simulation is further used for risk analysis. Results show that under BAU condition, oil demand of China's road transport sector will reach 278.5millionton of oil equivalents (MTOE) in 2020. Oil saving potential will be 86MTOE and 131MTOE under moderate oil-saving scenario and advanced oil-saving scenario, respectively. This paper provides a reference to establishing oil saving policy for China's road transport sector.
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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Shukla, Priyadarshi R. & Chaturvedi, Vaibhav, 2012. "Low carbon and clean energy scenarios for India: Analysis of targets approach," Energy Economics, Elsevier, vol. 34(S3), pages 487-495.
- Amarawickrama, Himanshu A. & Hunt, Lester C., 2008.
"Electricity demand for Sri Lanka: A time series analysis,"
Elsevier, vol. 33(5), pages 724-739.
- Himanshu A. Amarawickrama & Lester C Hunt, 2007. "Electricity Demand for Sri Lanka: A Time Series Analysis," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 118, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
- Liu, Wen & Lund, Henrik & Mathiesen, Brian Vad, 2013. "Modelling the transport system in China and evaluating the current strategies towards the sustainable transport development," Energy Policy, Elsevier, vol. 58(C), pages 347-357.
- Lin, Boqiang & Wu, Ya & Zhang, Li, 2011. "Estimates of the potential for energy conservation in the Chinese steel industry," Energy Policy, Elsevier, vol. 39(6), pages 3680-3689, June.
- Lardic, Sandrine & Mignon, Valérie, 2008. "Oil prices and economic activity: An asymmetric cointegration approach," Energy Economics, Elsevier, vol. 30(3), pages 847-855, May.
- Galindo, Luis Miguel, 2005. "Short- and long-run demand for energy in Mexico: a cointegration approach," Energy Policy, Elsevier, vol. 33(9), pages 1179-1185, June.
- Dowling, Paul & Russ, Peter, 2012. "The benefit from reduced energy import bills and the importance of energy prices in GHG reduction scenarios," Energy Economics, Elsevier, vol. 34(S3), pages 429-435.
- Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992.
"Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?,"
Journal of Econometrics,
Elsevier, vol. 54(1-3), pages 159-178.
- Denis Kwiatkowski & Peter C.B. Phillips & Peter Schmidt, 1991. "Testing the Null Hypothesis of Stationarity Against the Alternative of a Unit Root: How Sure Are We That Economic Time Series Have a Unit Root?," Cowles Foundation Discussion Papers 979, Cowles Foundation for Research in Economics, Yale University.
- Kwiatkowski, D. & Phillips, P.C.B. & Schmidt, P., 1990. "Testing the Null Hypothesis of Stationarity Against the Alternative of Unit Root : How Sure are we that Economic Time Series have a Unit Root?," Papers 8905, Michigan State - Econometrics and Economic Theory.
- Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
- Lin, Boqiang & Jiang, Zhujun, 2011. "Estimates of energy subsidies in China and impact of energy subsidy reform," Energy Economics, Elsevier, vol. 33(2), pages 273-283, March.
- Yuan, Chaoqing & Liu, Sifeng & Wu, Junlong, 2010. "The relationship among energy prices and energy consumption in China," Energy Policy, Elsevier, vol. 38(1), pages 197-207, January.
- Yan, Xiaoyu & Crookes, Roy J., 2009. "Reduction potentials of energy demand and GHG emissions in China's road transport sector," Energy Policy, Elsevier, vol. 37(2), pages 658-668, February.
- Wolde-Rufael, Yemane, 2010. "Bounds test approach to cointegration and causality between nuclear energy consumption and economic growth in India," Energy Policy, Elsevier, vol. 38(1), pages 52-58, January.
- Hua Liao & Yi-Ming Wei, 2009.
"China's energy consumption: A perspective from Divisia aggregation approach,"
CEEP-BIT Working Papers
1, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
- Liao, Hua & Wei, Yi-Ming, 2010. "China's energy consumption: A perspective from Divisia aggregation approach," Energy, Elsevier, vol. 35(1), pages 28-34.
- Jiang, Zhujun & Lin, Boqiang, 2012. "China's energy demand and its characteristics in the industrialization and urbanization process," Energy Policy, Elsevier, vol. 49(C), pages 608-615.
- Rao, B. Bhaskara & Rao, Gyaneshwar, 2008.
"Cointegration and the demand for gasoline,"
11396, University Library of Munich, Germany.
- Lin, Boqiang & Wang, Ting, 2012. "Forecasting natural gas supply in China: Production peak and import trends," Energy Policy, Elsevier, vol. 49(C), pages 225-233.
- Rozakis, S. & Sourie, J. -C., 2005. "Micro-economic modelling of biofuel system in France to determine tax exemption policy under uncertainty," Energy Policy, Elsevier, vol. 33(2), pages 171-182, January.
- Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
- Kulshreshtha, Mudit & Parikh, Jyoti K., 2000. "Modeling demand for coal in India: vector autoregressive models with cointegrated variables," Energy, Elsevier, vol. 25(2), pages 149-168.
- Akinboade, Oludele A. & Ziramba, Emmanuel & Kumo, Wolassa L., 2008. "The demand for gasoline in South Africa: An empirical analysis using co-integration techniques," Energy Economics, Elsevier, vol. 30(6), pages 3222-3229, November.
- Ramanathan, R., 1999. "Short- and long-run elasticities of gasoline demand in India: An empirical analysis using cointegration techniques," Energy Economics, Elsevier, vol. 21(4), pages 321-330, August.
- Park, Nyun-Bae & Yun, Sun-Jin & Jeon, Eui-Chan, 2013. "An analysis of long-term scenarios for the transition to renewable energy in the Korean electricity sector," Energy Policy, Elsevier, vol. 52(C), pages 288-296.
- Engle, Robert & Granger, Clive, 2015.
"Co-integration and error correction: Representation, estimation, and testing,"
Publishing House "SINERGIA PRESS", vol. 39(3), pages 106-135.
- Engle, Robert F & Granger, Clive W J, 1987. "Co-integration and Error Correction: Representation, Estimation, and Testing," Econometrica, Econometric Society, vol. 55(2), pages 251-276, March.
- Apergis, Nicholas & Payne, James E., 2009. "Energy consumption and economic growth in Central America: Evidence from a panel cointegration and error correction model," Energy Economics, Elsevier, vol. 31(2), pages 211-216.
- Spinney, Peter J & Watkins, G Campbell, 1996. "Monte Carlo simulation techniques and electric utility resource decisions," Energy Policy, Elsevier, vol. 24(2), pages 155-163, February.
- Lin, Boqiang & Liu, Jianghua, 2011. "Principles, effects and problems of differential power pricing policy for energy intensive industries in China," Energy, Elsevier, vol. 36(1), pages 111-118.
- Liu, Yingqi & Kokko, Ari, 2013. "Who does what in China’s new energy vehicle industry?," Energy Policy, Elsevier, vol. 57(C), pages 21-29.
- Lin, Boqiang & Li, Aijun, 2012. "Impacts of removing fossil fuel subsidies on China: How large and how to mitigate?," Energy, Elsevier, vol. 44(1), pages 741-749.
- Kalashnikov, Victor & Gulidov, Ruslan & Ognev, Alexander, 2011. "Energy sector of the Russian Far East: Current status and scenarios for the future," Energy Policy, Elsevier, vol. 39(11), pages 6760-6780.
- Roinioti, Argiro & Koroneos, Christopher & Wangensteen, Ivar, 2012. "Modeling the Greek energy system: Scenarios of clean energy use and their implications," Energy Policy, Elsevier, vol. 50(C), pages 711-722.
- Vithayasrichareon, Peerapat & MacGill, Iain F., 2012. "A Monte Carlo based decision-support tool for assessing generation portfolios in future carbon constrained electricity industries," Energy Policy, Elsevier, vol. 41(C), pages 374-392.
- Price, Lynn & Levine, Mark D. & Zhou, Nan & Fridley, David & Aden, Nathaniel & Lu, Hongyou & McNeil, Michael & Zheng, Nina & Qin, Yining & Yowargana, Ping, 2011. "Assessment of China's energy-saving and emission-reduction accomplishments and opportunities during the 11th Five Year Plan," Energy Policy, Elsevier, vol. 39(4), pages 2165-2178, April.
- MacKinnon, James G, 1996.
"Numerical Distribution Functions for Unit Root and Cointegration Tests,"
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 11(6), pages 601-618, Nov.-Dec..
- James G. MacKinnon, 1995. "Numerical Distribution Functions for Unit Root and Cointegration Tests," Working Papers 918, Queen's University, Department of Economics.
- Alves, Denisard C. O. & De Losso da Silveira Bueno, Rodrigo, 2003. "Short-run, long-run and cross elasticities of gasoline demand in Brazil," Energy Economics, Elsevier, vol. 25(2), pages 191-199, March.
- Park, Sung Y. & Zhao, Guochang, 2010. "An estimation of U.S. gasoline demand: A smooth time-varying cointegration approach," Energy Economics, Elsevier, vol. 32(1), pages 110-120, January.
- Lin, Boqiang & Zhang, Li & Wu, Ya, 2012. "Evaluation of electricity saving potential in China's chemical industry based on cointegration," Energy Policy, Elsevier, vol. 44(C), pages 320-330.
- Zhang, Chuanguo & Xu, Jiao, 2012. "Retesting the causality between energy consumption and GDP in China: Evidence from sectoral and regional analyses using dynamic panel data," Energy Economics, Elsevier, vol. 34(6), pages 1782-1789.
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