ORIGINAL RESEARCH
Probing Energy-Related CO2 Emissions
in the Beijing-Tianjin-Hebei Region Based
on Ridge Regression Considering
Population Factors
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Department of Economics and Management, North China Electric Power University, Baoding, China
Submission date: 2019-05-30
Final revision date: 2019-06-28
Acceptance date: 2019-07-07
Online publication date: 2020-02-06
Publication date: 2020-03-31
Corresponding author
Lei Wen
Department of Economics and Management, North China Electric Power University, Baoding 071003, China, baoding, 071003, baoding, China
Pol. J. Environ. Stud. 2020;29(3):2413-2427
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ABSTRACT
The main driving force for huge energy consumption is population growth and economic
development, and many studies have analyzed the factors that influence carbon dioxide emissions.
But the influencing factors mainly refer to the economic and social fields. Few studies have looked
at population factors, and the extended STIRPAT model and ridge regression method are used to pay
attention to the impact of population factors on carbon dioxide emissions in the Beijing-Tianjin-Hebei
region. The conclusions drawn are as follows:
1) For Beijing, the urbanization level, population density, per capita disposable income, education
level, GDP and energy intensity have a positive impact on CO2 emissions. However, age structure, family
size and industrial structure play negative roles. The improvement of urbanization level has a distinctive
positive influence on CO2 emissions.
2) For Tianjin, most impact factors have a positive effect on CO2 emissions, except family size and
energy intensity. The decrease of family size is the first contributor to CO2 emissions growth.
3) For Hebei, the urbanization level, population density, per capita disposable income, age structure,
GDP and industrial structure, have a positive influence on CO2 emissions.
Education level, family size and energy intensity have a negative impact on CO2 emissions, and
population density is the most important factor.