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Population, Affluence, and Environmental Impact Across Development: Evidence from Panel Cointegration Modeling

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  • Liddle, Brantley

Abstract

This paper analyzes urban population’s and affluence’s (GDP per capita’s) influence on environmental impact in developed and developing countries by taking as its starting point the STIRPAT framework. In addition to considering environmental impacts particularly influenced by population and affluence (carbon emissions from transport and residential electricity consumption), the paper determines whether and, if so, how those environmental impact relationships vary across development levels by analyzing panels consisting of poor, middle, and rich countries. The development-based panels approach is an improvement on the GDP per capita polynomial model used in the Environmental Kuznets Curve and other literatures for several reasons: (i) it allows one to determine whether the elasticity of all variables considered varies according to development; (ii) it is arguably a more accurate description of the development process; (iii) it avoids potentially spurious regressions involving nonlinear transformations of nonstationary variables (GDP per capita squared); and (iv) unlike the polynomial model, it allows for the possibility that elasticities are significantly different across development levels but still positive—precisely the relationship expected for the environmental impacts considered here. Whether or not the elasticity for affluence was greater than that for population was a function of both the choice of dependent variable and the makeup of the panel (all countries, poor, middle, or rich). Furthermore, the estimated elasticities varied, in a nonlinear fashion, according to the development process: U-shaped, inverted U-shaped, and monotonic patterns were revealed, again, depending on the dependent variable.

Suggested Citation

  • Liddle, Brantley, 2013. "Population, Affluence, and Environmental Impact Across Development: Evidence from Panel Cointegration Modeling," MPRA Paper 52088, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:52088
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    Cited by:

    1. Wang, Yuan & Li, Li & Kubota, Jumpei & Han, Rong & Zhu, Xiaodong & Lu, Genfa, 2016. "Does urbanization lead to more carbon emission? Evidence from a panel of BRICS countries," Applied Energy, Elsevier, vol. 168(C), pages 375-380.
    2. Laureti, Tiziana & Montero, José-María & Fernández-Avilés, Gema, 2014. "A local scale analysis on influencing factors of NOx emissions: Evidence from the Community of Madrid, Spain," Energy Policy, Elsevier, vol. 74(C), pages 557-568.
    3. Sarah Harper, 2013. "Population–Environment Interactions: European Migration, Population Composition and Climate Change," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 55(4), pages 525-541, August.
    4. Wang, Yuan & Zhang, Chen & Lu, Aitong & Li, Li & He, Yanmin & ToJo, Junji & Zhu, Xiaodong, 2017. "A disaggregated analysis of the environmental Kuznets curve for industrial CO2 emissions in China," Applied Energy, Elsevier, vol. 190(C), pages 172-180.
    5. Liddle, Brantley & Messinis, George, 2015. "Revisiting sulfur Kuznets curves with endogenous breaks modeling: Substantial evidence of inverted-Us/Vs for individual OECD countries," Economic Modelling, Elsevier, vol. 49(C), pages 278-285.
    6. Wang, Yuan & Han, Rong & Kubota, Jumpei, 2016. "Is there an Environmental Kuznets Curve for SO2 emissions? A semi-parametric panel data analysis for China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1182-1188.
    7. Liddle, Brantley, 2014. "Impact of population, age structure, and urbanization on carbon emissions/energy consumption: Evidence from macro-level, cross-country analyses," MPRA Paper 61306, University Library of Munich, Germany.
    8. Brantley Liddle & George Messinis, 2018. "Revisiting carbon Kuznets curves with endogenous breaks modeling: evidence of decoupling and saturation (but few inverted-Us) for individual OECD countries," Empirical Economics, Springer, vol. 54(2), pages 783-798, March.
    9. repec:eee:enepol:v:107:y:2017:i:c:p:678-687 is not listed on IDEAS
    10. Tiba, Sofien & Omri, Anis, 2017. "Literature survey on the relationships between energy, environment and economic growth," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 1129-1146.
    11. Andrew Jorgenson & Daniel Auerbach & Brett Clark, 2014. "The (De-) carbonization of urbanization, 1960–2010," Climatic Change, Springer, vol. 127(3), pages 561-575, December.
    12. Hasanov, Fakhri J. & Bulut, Cihan & Suleymanov, Elchin, 2016. "Do population age groups matter in the energy use of the oil-exporting countries?," Economic Modelling, Elsevier, vol. 54(C), pages 82-99.
    13. Sinha, Avik & Shahbaz, Muhammad & Balsalobre, Daniel, 2017. "Exploring the Relationship between Energy Usage Segregation and Environmental Degradation in N-11 Countries," MPRA Paper 81212, University Library of Munich, Germany, revised 07 Sep 2017.
    14. Toru Ota & Makoto Kakinaka & Koji Kotani, 2017. "Demographic effects on residential electricity and city gas consumption in aging society of Japan," Working Papers SDES-2017-7, Kochi University of Technology, School of Economics and Management, revised Jun 2017.
    15. Annageldy Arazmuradov, 2016. "Economic prospect on carbon emissions in Commonwealth of Independent States," Economic Change and Restructuring, Springer, vol. 49(4), pages 395-427, November.

    More about this item

    Keywords

    STIRPAT; population and environment; FMOLS panel cointegration; environment and development; IPAT; GHG emissions; Environmental/Carbon Kuznets Curve;

    JEL classification:

    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth

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