Aviation fuel demand development in China

Jian Chai, Zhong-Yu Zhang, Shou-Yang Wang, Kin Keung Lai, John Liu

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    18 Citations (Scopus)

    Abstract

    This paper analyzes the core factors and the impact path of aviation fuel demand in China and conducts a structural decomposition analysis of the aviation fuel cost changes and increase of the main aviation enterprises' business profits. Through the establishment of an integrated forecast model for China's aviation fuel demand, this paper confirms that the significant rise in China's aviation fuel demand because of increasing air services demand is more than offset by higher aviation fuel efficiency. There are few studies which use a predictive method to decompose, estimate and analyze future aviation fuel demand. Based on a structural decomposition with indirect prediction, aviation fuel demand is decomposed into efficiency and total amount (aviation fuel efficiency and air transport total turnover). The core influencing factors for these two indexes are selected using path analysis. Then, univariate and multivariate models (ETS/ARIMA model and Bayesian multivariate regression) are used to analyze and predict both aviation fuel efficiency and air transport total turnover. At last, by integrating results, future aviation fuel demand is forecast. The results show that the aviation fuel efficiency goes up by 0.8% as the passenger load factor increases 1%; the air transport total turnover goes up by 3.8% and 0.4% as the urbanization rate and the per capita GDP increase 1%, respectively. By the end of 2015, China's aviation fuel demand will have increased to 28 million tonnes, and is expected to be 50 million tonnes by 2020. With this in mind, increases in the main aviation enterprises' business profits must be achieved through the further promotion of air transport.
    Original languageEnglish
    Pages (from-to)224-235
    JournalEnergy Economics
    Volume46
    Online published22 Sept 2014
    DOIs
    Publication statusPublished - Nov 2014

    Research Keywords

    • ARIMA
    • Aviation fuel demand
    • Aviation fuel efficiency
    • Bayes
    • ETS

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