Journal ArticleDOI
Examining the impact factors of energy-related CO2 emissions using the STIRPAT model in Guangdong Province, China
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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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Examining the effects of income inequality on CO2 emissions: Evidence from non-spatial and spatial perspectives
TL;DR: Li et al. as mentioned in this paper investigated how the level of income distribution within 30 Chinese provinces influenced that province's CO2 emissions, using panel data from 1996 to 2014 to estimate both the Gini coefficient and Global Moran's I.
Journal ArticleDOI
Panel estimation for the impacts of population-related factors on CO2 emissions: A regional analysis in China
TL;DR: In this paper, the authors examined the impact of population size, per capita consumption, energy intensity, urbanization and aging population on CO 2 emissions by adopting panel data of 30 provinces from 1997 to 2012.
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Spatiotemporal variations of CO2 emissions and their impact factors in China: A comparative analysis between the provincial and prefectural levels
TL;DR: Wang et al. as mentioned in this paper investigated the spatiotemporal variations (SV) of CO2 emissions and their impact factors (IF) across different levels to develop more effective and reasonable policies and measures for emissions mitigation.
Journal ArticleDOI
Using the STIRPAT model to explore the factors driving regional CO2 emissions: a case of Tianjin, China
Bo Li,Xuejing Liu,Zhenhong Li +2 more
TL;DR: In this article, an extended stochastic impact by regression on population, affluence, and technology model is conducted to systematically identify the determinant factors driving CO2 emissions in Tianjin during the period 1996-2012.
Journal ArticleDOI
Impact of energy consumption and human activities on carbon emissions in Pakistan: application of STIRPAT model.
TL;DR: It is recommended that a transition from fossil fuel energy to renewable and hydroelectric energy could prove an effective strategy to improve the affluence level, to alleviate poverty and effective to reduce carbon emissions in Pakistan.
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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