Demand Forecast of Petroleum Product Consumption in the Chinese Transportation IndustryReport as inadecuate


Demand Forecast of Petroleum Product Consumption in the Chinese Transportation Industry


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1

Shaanxi Normal University, International Business School, Xi’an 710062, China

2

Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China

3

The School of Management Xi’an Jiao Tong University, Xi’an 710049, China





*

Author to whom correspondence should be addressed.



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. View Full-Text

Keywords: petroleum products consumption; transportation sector; Bayesian linear regression; Markov Chain Monte Carlo method petroleum products consumption; transportation sector; Bayesian linear regression; Markov Chain Monte Carlo method





Author: Jian Chai 1,2,3,* , Shubin Wang 1, Shouyang Wang 2 and Ju’e Guo 3

Source: http://mdpi.com/



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