• DocumentCode
    2394033
  • Title

    The Analysis of the Market of Coal Consumption in Shaanxi Province Based on the BVAR Model

  • Author

    Quanying Lu ; Zhongyu Zhang ; Jian Chai ; Qing Zhu

  • Author_Institution
    Int. Bus. Sch., Shaanxi Normal Univ., Xi´an, China
  • fYear
    2013
  • fDate
    14-16 Nov. 2013
  • Firstpage
    490
  • Lastpage
    494
  • Abstract
    In early 2013, Beijing and even the whole country of china appeared the haze weather and PM2.5 problem, environmental problems caused widespread attention again. The latest research of "Atmospheric haze tracking and control" special group of CAS results that: coal and motor vehicles are the main cause of the strong fog haze weather. For China, the coal is the primary energy in China accounted for the largest. Along with the energy-saving emission reduction as a major national policy background, the analysis of coal consumption market has increasingly aroused the attention of scientific researchers, and become the hotspot of relative research recent years. In order to solve the problem, this paper takes Shaanxi Province as an object of study, which is one of three major coal producing regions. On the basis of analyzing the core factors affecting extraction coal demand, establish VAR model and BVAR model of coal consumption. Finally, by comparing the three kinds of results of two model prediction, using BVAR model predict the coal consumption in Shaanxi in 2020 will reach 175792800 tons of standard coal.
  • Keywords
    air pollution; coal; energy conservation; energy consumption; BVAR model; Shaanxi province; atmospheric haze tracking; core factors; energy saving emission reduction; environmental problems; fog haze weather; hotspot; motor vehicles; national policy background; standard coal consumption market; Coal; Economics; Mathematical model; Predictive models; Reactive power; Sociology; Statistics; BVAR model; R software; VAR model; coal consumption;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Business Intelligence and Financial Engineering (BIFE), 2013 Sixth International Conference on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4799-4778-2
  • Type

    conf

  • DOI
    10.1109/BIFE.2013.103
  • Filename
    6961184