Demand Forecast of Petroleum Product Consumption in the Chinese Transportation Industry

Jian Chai, Shubin Wang, Shouyang Wang and Ju’e Guo
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Jian Chai: Shaanxi Normal University, International Business School, Xi’an 710062, China
Shubin Wang: Shaanxi Normal University, International Business School, Xi’an 710062, China
Shouyang Wang: Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China
Ju’e Guo: The School of Management Xi’an Jiao Tong University, Xi’an 710049, China

Energies, 2012, vol. 5, issue 3, 1-22

Abstract: In this paper, petroleum product (mainly petrol and diesel) consumption in the transportation sector of China is analyzed. This was based on the Bayesian linear regression theory and Markov Chain Monte Carlo method (MCMC), establishing a demand-forecast model of petrol and diesel consumption introduced into the analytical framework with explanatory variables of urbanization level, per capita GDP, turnover of passengers (freight) in aggregate (TPA, TFA), and civilian vehicle number (CVN) and explained variables of petrol and diesel consumption. Furthermore, we forecast the future consumer demand for oil products during “The 12th Five Year Plan” (2011–2015) based on the historical data covering from 1985 to 2009, finding that urbanization is the most sensitive factor, with a strong marginal effect on petrol and diesel consumption in this sector. From the viewpoint of prediction interval value, urbanization expresses the lower limit of the predicted results, and CVN the upper limit of the predicted results. Predicted value from other independent variables is in the range of predicted values which display a validation range and reference standard being much more credible for policy makers. Finally, a comparison between the predicted results from autoregressive integrated moving average models (ARIMA) and others is made to assess our task.

Keywords: petroleum products consumption; transportation sector; Bayesian linear regression; Markov Chain Monte Carlo method (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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