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The Stochastic Convergence of CO2 Emissions: A Long Memory Approach

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  • Marco R Barassi
  • Matthew A Cole
  • Robert J R Elliott

Abstract

In response to equity concerns surrounding the spatial distribution of CO2 emissions and the assumptions of CO2 convergence within some climate models, this paper examines the convergence of CO2 emissions within the OECD over the period 1870-204. More specifically, using the Local Whittle estimator and its variants we examine whether relative per capita CO2 emissions are fractionally integrated, that is they are long memory processes which, although highly persistant, may revert to the mean/trend in the long run. Our results suggest that CO2 emissions within 13 out of 18 OECD countries are indeed fractionally integrated implying that they converge over time, albeit slowly. Interestingly though, the countries whose emissions are not found to be fractionally integrated are some of the highest polluters within the OECD, at least in per capita terms. Our results have implications both for future studies of CO2 convergence and for climate policy.

Suggested Citation

  • Marco R Barassi & Matthew A Cole & Robert J R Elliott, 2010. "The Stochastic Convergence of CO2 Emissions: A Long Memory Approach," Discussion Papers 10-32, Department of Economics, University of Birmingham.
  • Handle: RePEc:bir:birmec:10-32
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Catherine Wolfram & Orie Shelef & Paul Gertler, 2012. "How Will Energy Demand Develop in the Developing World?," Journal of Economic Perspectives, American Economic Association, vol. 26(1), pages 119-138, Winter.
    2. Juan Antonio Duro & Jordi Teixidó-Figueras & Emilio Padilla, 2014. "The causal factors of international inequality in co2 emissions per capita: a regression-based inequality decomposition analysis," Working Papers 2014/20, Institut d'Economia de Barcelona (IEB).
    3. Camarero, Mariam & Picazo-Tadeo, Andrés J. & Tamarit, Cecilio, 2013. "Are the determinants of CO2 emissions converging among OECD countries?," Economics Letters, Elsevier, vol. 118(1), pages 159-162.
    4. repec:bla:wireae:v:6:y:2017:i:3:p:n/a-n/a is not listed on IDEAS
    5. Belbute, José M. & Pereira, Alfredo M., 2015. "An alternative reference scenario for global CO2 emissions from fuel consumption: An ARFIMA approach," Economics Letters, Elsevier, vol. 136(C), pages 108-111.
    6. José M. Belbute & Alfredo Marvão Pereira, 2016. "Do Global CO2 Emissions from Fossil-Fuel Consumption Exhibit Long Memory? A Fractional Integration Analysis," Working Papers 165, Department of Economics, College of William and Mary.
    7. repec:eee:eneeco:v:65:y:2017:i:c:p:228-239 is not listed on IDEAS
    8. Mishra, Vinod & Smyth, Russell, 2017. "Conditional convergence in Australia's energy consumption at the sector level," Energy Economics, Elsevier, vol. 62(C), pages 396-403.
    9. Ghosh, Madhusudan & Ghoshray, Atanu & Malki, Issam, 2013. "Regional divergence and club convergence in India," Economic Modelling, Elsevier, vol. 30(C), pages 733-742.
    10. repec:eee:enepol:v:113:y:2018:i:c:p:386-400 is not listed on IDEAS
    11. Duro, Juan Antonio, 2013. "International mobility in carbon dioxide emissions," Energy Policy, Elsevier, vol. 55(C), pages 208-216.
    12. José M. Belbute & Alfredo Marvão Pereira, 2016. "Updated Reference Forecasts for Global CO2 Emissions from Fossil-Fuel Consumption," Working Papers 170, Department of Economics, College of William and Mary.
    13. José Belbute & Alberto Marvão Pereira, 2015. "Do Global CO2 Emissions from Fuel Consumption Exhibit Long Memory? A Fractional Integration Analysis," CEFAGE-UE Working Papers 2015_14, University of Evora, CEFAGE-UE (Portugal).
    14. repec:eee:rensus:v:75:y:2017:i:c:p:86-97 is not listed on IDEAS
    15. Dayong Zhang and David C. Broadstock, 2016. "Club Convergence in the Energy Intensity of China," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    16. repec:eee:eneeco:v:63:y:2017:i:c:p:365-372 is not listed on IDEAS

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    Keywords

    Fractional Integration; Local Whittle Estimation;

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