Analysis of road transportation energy consumption demand in China. (October 2016)
- Record Type:
- Journal Article
- Title:
- Analysis of road transportation energy consumption demand in China. (October 2016)
- Main Title:
- Analysis of road transportation energy consumption demand in China
- Authors:
- Chai, Jian
Lu, Quan-Ying
Wang, Shou-Yang
Lai, Kin Keung - Abstract:
- Highlights: Road transportation energy consumption is forecasted on the basis of model selection and combine. The combined model includes univariate (ETS & ARIMA models) and multivariate (multiple regression) models. Bayesian model average method is adopted to select the core factors. Road transportation energy consumption and GDP presented 'S' type pattern. Financial credit and employment are considered as the factors. Abstract: In this paper, we first analyze the historical trends in road transportation energy consumption and GDP in developed economies to find out the development characteristics of road energy consumption. The two indexes present obvious 'S' type patterns. Then, in order to explore the current status and future trend of road energy transportation in China, we employ path analysis to analyze the impact mechanism of the factors related to road transportation energy consumption. Next, we adopt the BMA model to select the core factors related to road transportation energy consumption in China, and on the basis of the model selection as well as univariate (ETS & ARIMA models) and multivariate (multiple regression) models, the road transportation energy consumption is analyzed and forecast. The results showed that the road transportation energy consumption rises by 0.33 percent for every percent increase in GDP and by 1.26 percentage points for every percent increase in urbanization. The road transportation energy consumption in China is expected to reach aroundHighlights: Road transportation energy consumption is forecasted on the basis of model selection and combine. The combined model includes univariate (ETS & ARIMA models) and multivariate (multiple regression) models. Bayesian model average method is adopted to select the core factors. Road transportation energy consumption and GDP presented 'S' type pattern. Financial credit and employment are considered as the factors. Abstract: In this paper, we first analyze the historical trends in road transportation energy consumption and GDP in developed economies to find out the development characteristics of road energy consumption. The two indexes present obvious 'S' type patterns. Then, in order to explore the current status and future trend of road energy transportation in China, we employ path analysis to analyze the impact mechanism of the factors related to road transportation energy consumption. Next, we adopt the BMA model to select the core factors related to road transportation energy consumption in China, and on the basis of the model selection as well as univariate (ETS & ARIMA models) and multivariate (multiple regression) models, the road transportation energy consumption is analyzed and forecast. The results showed that the road transportation energy consumption rises by 0.33 percent for every percent increase in GDP and by 1.26 percentage points for every percent increase in urbanization. The road transportation energy consumption in China is expected to reach around 226181.1 ktoe by the end of 2015, and about 347, 363 ktoe by 2020. … (more)
- Is Part Of:
- Transportation research. Volume 48(2016)
- Journal:
- Transportation research
- Issue:
- Volume 48(2016)
- Issue Display:
- Volume 48, Issue 2016 (2016)
- Year:
- 2016
- Volume:
- 48
- Issue:
- 2016
- Issue Sort Value:
- 2016-0048-2016-0000
- Page Start:
- 112
- Page End:
- 124
- Publication Date:
- 2016-10
- Subjects:
- Road transportation energy consumption -- Trend analysis -- Path analysis -- BMA -- ETS -- ARIMA
Transportation -- Research -- Periodicals
Transportation -- Environmental aspects -- Periodicals
354.76 - Journal URLs:
- http://www.sciencedirect.com/science/journal/13619209 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.trd.2016.08.009 ↗
- Languages:
- English
- ISSNs:
- 1361-9209
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9026.274630
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