Demographic Dynamics and Per Capita Environmental Impact: Using Panel Regressions and Household Decompositions to Examine Population and Transport

By Brantley Liddle. 2003

204 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/7e9e011b8ad5e756bc34c6e02c1fb71f19400b53

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Muhammad Shahbaz
2. Ilhan Ozturk
3. Yang Zhou
4. Yan-sui Liu
5. Emrah Koçak
6. Faik Bilgili
7. Avik Sinha
8. Eyup Dogan

In Environmental Engineering

1. Muhammad Shahbaz
2. Yan-sui Liu
3. Yang Zhou
4. Ilhan Ozturk
5. Faik Bilgili
6. Wenxiang Wu
7. Emrah Koçak
8. A. Dhaoui

In Renewable Energy, Sustainability and the Environment

1. Muhammad Shahbaz
2. Ilhan Ozturk
3. Emrah Koçak
4. Faik Bilgili
5. Yan-sui Liu
6. Yang Zhou
7. Avik Sinha
8. Umit Bulut

Citations in the corpus

• Impact of population, age structure, and urbanization on carbon emissions/energy consumption: evidence from macro-level, cross-country analyses (2013, unknown): “Indeed, Liddle and Lung (2013) uncovered a long-run, causal relationship from several aggregations of electricity consumption (i.”
• Urban Density and Climate Change: A STIRPAT Analysis Using City-Level Data (2013, background): “Indeed, Liddle (5) The turning points had to be estimated since Romero-Lankao et al. (2009) do not report such statistics.”
• Assessing the impact of population, income and technology on energy consumption and industrial pollutant emissions in China (2015, background): “Although most existing studies have claimed that urbanisation is positively correlated with energy consumption and carbon emissions, Liddle [18] argued that the correlation is a function of income’s/development’s positive association with both urbanisation and energy/emissions.”
• On the Causal Nexus of Road Transport CO2 Emissions and Macroeconomic Variables in Tunisia: Evidence from Combined Cointegration Tests (2015, background): “[7,40,41,22,36].”
• Green inventions and greenhouse gas emission dynamics: a close examination of provincial Italian data (2016, background): “Finally, researchers working with micro-level data have shown that activities such as transport and residential energy consumption vary according to age structure and household size (e.g., O‘Neill & Chen 2002; Liddle 2004; Prskawetz et al. 2004; Zagheni 2011).”
• Consumption-Driven Environmental Impact and Age Structure Change in OECD Countries: A Cointegration-STIRPAT Analysis (2011, unknown): “…of national-level studies to examine consumptiondriven environmental impacts (like Liddle 2004 and Liddle and Lung 2010) and to consider the influence of population structure (i.e., household size or age cohorts) on environment (e.g., Cole and Neumayer 2004; Liddle 2004; and Liddle and Lung 2010).”
• The effect of urbanization, affluence and trade openness on energy consumption: A time series analysis in Malaysia (2015, unknown): “Liddle [15] considered the influence of”
• The impact of urbanization on energy intensity: Panel data evidence considering cross-sectional dependence and heterogeneity (2017, background): “Liddle [65] 1960e2000 23 OECD countries OLS negative”
• Does urbanization cause increasing energy demand in Pakistan? Empirical evidence from STIRPAT model (2017, background): “Urbanization increases the road use due to industrial activities [45], pressurizes agriculture sector to produce more food both for rural as well as urban population [12], increases commercialization [46], changes urban structure [19], stimulates financial development which leads to promotion of inv”
• Economic Complexity and Environmental Performance: Evidence from a World Sample (2019, background): “We also include two demographic variables: population density (number of people per square kilometer of land area) and urban population (the proportion of urban population) to identify the consequences of demographic changes on the environment [61, 68, 81, 97, 110, 121].”