Journal ArticleDOI
Examining the impact factors of energy-related CO2 emissions using the STIRPAT model in Guangdong Province, China
TLDR
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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Journal ArticleDOI
Determinants of the global and regional CO2 emissions: What causes what and where?
TL;DR: Using the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model and an unbalanced panel dataset of 128 countries covering 1990-2014, this paper examined t...
Journal ArticleDOI
Examining the influences of urbanization on carbon dioxide emissions in the Yangtze River Delta, China: Kuznets curve relationship.
TL;DR: This study conducts a comprehensive assessment of the multiple effects of urbanization on carbon dioxide emissions in the Yangtze River Delta, based on city panel remote sensing and statistical data covering the years 1992 to 2013, and casts new light on the importance of exploring the multiple Effects of Urbanization in relation to emissions.
Journal ArticleDOI
Impacts of energy consumption, energy structure, and treatment technology on SO2 emissions: A multi-scale LMDI decomposition analysis in China
TL;DR: In this paper, the authors investigated the impacts of three dominant direct factors: total energy consumption (EC), energy structure (ES) and treatment technology (TT) on sulfur dioxide (SO2) emissions in China during 1995-2014 using the logarithmic mean divisia index method.
Journal ArticleDOI
How does urbanization affect residential CO2 emissions? An analysis on urban agglomerations of China
TL;DR: Wang et al. as mentioned in this paper applied fixed effects two-stage least squares (2SLS) to explore the relationship between urbanization and residential CO2 emissions, using an augmented Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model.
Journal ArticleDOI
Does population have a larger impact on carbon dioxide emissions than income? Evidence from a cross-regional panel analysis in China
TL;DR: Li et al. as mentioned in this paper used an improved STIRPAT model to reassess the impact of demographic and income changes on China's energy-related CO2 emissions at the national and regional levels using balanced provincial panel data from the 1990-2012 period.
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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