Using Panel Data to Evaluate the Factors Affecting Transport Energy Consumption in China’s Three Regions
Bibliographic Data
| ID | 15483874 |
|---|---|
| Authors | Tian-Xiang Lv (0000-0002-4316-1248, Beijing Jiaotong University), Xu Wu (0000-0001-5543-7742, Beijing Jiaotong University, corresponding author) |
| Year | 2019 |
| Volume | 16 |
| Issue | 4 |
| Pages | 555-555 |
| Publication date | 2019-02-14 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Environmental Research and Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1661-7827 • E-ISSN: 1660-4601 |
| Publisher | Multidisciplinary Digital Publishing Institute (PUBLISHER • CH) |
| DOI | 10.3390/ijerph16040555 |
| PMID | 30769882 |
| OpenAlex | W2914845593 |
| Language | EN |
| Citations received | 3 |
| References cited | 35 |
In China, transportation accounts for a large proportion of total energy consumption and that trend is projected to increase in the future. Through the stochastic impacts by regression on population, affluence, and technology (STIRPAT) model, OLS regressions were conducted to investigate the impacts of gross domestic product (GDP), urbanization, energy intensity and transport structure on the transport energy consumption in China's three regions. The analyses of inter-provincial panel data during the period 2006−2015 is compared to the analysis of the data from 1996 to 2005 to determine the change. There were two primary findings from this study. First, the changes of the influencing degree in three regions are considered. GDP is still the main driver of transport energy consumption in eastern region, while urbanization becomes the main driver in the other two regions. Second, the relationship between the elasticity and the value of each variable is detected. The elasticity of transport energy consumption with respect to GDP, transport structure, energy intensity and urbanization have separate positive and significant relationships. The primary measure is to optimize transport structure in the central region, while reducing energy intensity in the western region. Finally, we propose relevant policy recommendations for the three regions
China · Driving factors · Econometrics · Economic growth · Economics · Energy consumption · Energy intensity · Geography · Gross domestic product · Panel data · Population · Regression analysis · Statistics · Urbanization · Demography · Energy, Environment, and Transportation Policies · Energy, Environment, Economic Growth · Engineering · Environmental Impact and Sustainability · Environmental Science · Mathematics
Econometric Analysis of Panel Data
Effects of population and affluence on CO 2 emissions
The impacts of transport energy consumption, foreign direct investment and income on CO2 emissions in Asean-5 economies
CO2 emissions, energy consumption and economic growth in China
Carbon dioxide emissions and economic growth
Impact of Population Growth
Using Grey Relational Analysis to Evaluate Energy Consumption, CO2 Emissions and Growth Patterns in China’s Provincial Transportation Sectors
STIRPAT, Ipat and ImPact
| Citations per year | 0.5 |
|---|---|
| Citation span | 2020 - 2021 (2) |
| Highly cited | No |