The impact of population pressure on global carbon dioxide emissions, 1975-1996: evidence from pooled cross-country data

By A. Shi. 2003

673 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/1b1262c40053712934e2e9de5cc24b808c1fae06

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Citations in the corpus

Modelling the nonlinear relationship between CO2 emissions from oil and economic growth (2012, background): “Cropper and Griffiths (1994), Bruvoll and Medin (2003), Shi (2003), and Lantz and Feng (2006) each include the population variable in the regression and obtain a significantly monotonic relationship between the population and various forms of environmental variables.”
The effect of new-type urbanization on energy consumption in China: a spatial econometric analysis (2017, methodology): “The IPAT function was first designed by Ehrlich et al. (1971), and it is now widely accepted as a basic framework of modeling research in environmental issues (Harrison, 1981; Raskin, 1995; York et al., 2002; Shi, 2003; Cole and Neumayer et al., 2004; Rosa et al., 2004; Hao and Liu, 2015).”
Population aging and carbon emissions in OECD countries: Accounting for life-cycle and cohort effects (2012, background): “York et al. (2003), Shi (2003), Cole and Neumayer (2004) and Farzin and Bond (2006) combined data from developed and developing countries.”
Key Challenges to Ecological Modernization Theory (2003, background): “…of a diversity of environmental impacts that the most highly modernized nations (as indicated by per capita GDP, urbanization, and economic structure) have the highest environmental impacts (Rosa & York, 2002; Rosa et al., 2001; York et al., 2003, in press, unpublished, 2003—see also Shi, 2003).”
Transitions in pathways of human development and carbon emissions (2013, background): “…of 1 with total emissions, a standard result of cross-sectional studies (Dietz and Rosa 1997, York et al 2003b, Steinberger et al 2010), but one which may not hold for time-series analysis, where elasticities higher or lower than 1 have been observed (Shi 2003, Wei 2011, Jorgenson and Clark 2013).”
Assessing the impact of population, income and technology on energy consumption and industrial pollutant emissions in China (2015, background): “The IPAT model is limited because it analyzes a problem by changing a factor while keeping others constant, resulting in proportionate impacts on the dependent variable [20,51].”
The Ecological Footprint Intensity of National Economies (2004, background): “Other impacts with more global consequences (e.g., greenhouse gas emissions), however, generally increase monotonically with economic development (Cavlovic et al. 2000; Chertow 2001; Shi 2003; York et al. 2003a, 2003b, 2003c; Rosa et al. 2004).”
What are the carbon emissions elasticities for income and population? Bridging STIRPAT and EKC via robust heterogeneous panel estimates (2015, background): “By contrast Shi (2003) estimated a particularly high elasticity for population—between 1.4 and 1.6 for all countries samples; when Shi separated countries by income groups, the elasticity for high income countries was 0.8, whereas the elasticity for middle and low income countries ranged from 1.4…”
An empirical research on the influencing factors of regional CO2 emissions: Evidence from Beijing city, China (2012, background): “Phetkeo and Shinji also found the same results [16].”