Journal ArticleDOI
Examining the impact factors of energy-related CO2 emissions using the STIRPAT model in Guangdong Province, China
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In this article, the authors examined the impact factors of population, economic level, technology level, urbanization level, GDP per capita, industrialization level and service level on the energy-related CO2 emissions in Guangdong Province, China from 1980 to 2010 using an extended STIRPAT model.Citations
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The impact of economic structure to the environmental Kuznets curve (EKC) hypothesis: evidence from European countries
Eyup Dogan,Roula Inglesi-Lotz +1 more
TL;DR: The main finding of the study is that the overall economic growth is the factor with which CO 2 emissions exhibit an inverted U-shaped relationship in the studied country group.
Journal ArticleDOI
Identifying key impact factors on carbon emission: Evidences from panel and time-series data of 125 countries from 1990 to 2011
TL;DR: In this paper, the STIRPAT model was combined with the use of the panel and time-series data to analyze the impacts of population, affluence and technology on the carbon emission of 125 countries at different income levels over the period of 1990-2011.
Journal ArticleDOI
Exploring the relationship between urbanization, energy consumption, and CO2 emissions in different provinces of China
TL;DR: Li et al. as discussed by the authors investigated the impact of urbanization on energy consumption and CO 2 emissions with consideration of provincial differences, finding that urbanization strongly and relatively strongly affects the regional CO2 emissions in northern China, where the major coal production areas, characterized by an energyguzzling heavy industry base, are located.
Journal ArticleDOI
Examining the impacts of socioeconomic factors, urban form, and transportation networks on CO2 emissions in China’s megacities
TL;DR: In this article, the authors examined the combined impacts of socioeconomic and spatial planning factors on CO2 emissions in cities that have experienced rapid urbanization, using an econometric model and a comprehensive panel dataset incorporating socioeconomic, urban form, and transportation factors for four Chinese megacities (Beijing, Tianjin, Shanghai and Guangzhou) in the period 1990-2010.
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Examining the driving factors of energy related carbon emissions using the extended STIRPAT model based on IPAT identity in Xinjiang
TL;DR: In this article, an extended STIRPAT model based on the classical IPAT identity was used to determine the main driving factors for energy related carbon emissions in Xinjiang, and the results showed that the impacts and influences of various factors on carbon emissions are different in the three different development stages.
References
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Journal ArticleDOI
Ridge regression: biased estimation for nonorthogonal problems
TL;DR: In this paper, an estimation procedure based on adding small positive quantities to the diagonal of X′X was proposed, which is a method for showing in two dimensions the effects of nonorthogonality.
Journal ArticleDOI
Impact of Population Growth
Paul R. Ehrlich,John P. Holdren +1 more
TL;DR: In this paper, the authors argue that population growth causes a disproportionate negative impact on the environment and that the control of population is necessary but not sufficient means of seeing us through the whole crisis of environmental deterioration.
Journal ArticleDOI
Generalized Inverses, Ridge Regression, Biased Linear Estimation, and Nonlinear Estimation
TL;DR: In this article, the authors discuss a class of biased linear estimators employing generalized inverses and establish a unifying perspective on nonlinear estimation from nonorthogonal data.
Journal ArticleDOI
STIRPAT, IPAT and ImPACT: analytic tools for unpacking the driving forces of environmental impacts
TL;DR: In this paper, the STIRPAT model is augmented with measures of ecological elasticity, which allows for a more precise specification of the sensitivity of environmental impacts to the forces driving them.
Book
Multicollinearity in Regression Analysis; the Problem Revisited
TL;DR: An attempt is made to define multicollinearity in terms of departures from a hypothesized statistical condition, and measures are proposed here that fill this need.
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STIRPAT, IPAT and ImPACT: analytic tools for unpacking the driving forces of environmental impacts
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