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Do Global CO2 Emissions from Fossil-Fuel Consumption Exhibit Long Memory? A Fractional Integration Analysis

Author

Listed:
  • José M. Belbute

    (Department of Economics, University of Évora, Portugal)

  • Alfredo Marvão Pereira

    (Department of Economics, The College of William and Mary)

Abstract

In this paper we use an ARFIMA approach to measure the degree of fractional integration of aggregate world CO2 emissions and its five components – coal, oil, gas, cement, and gas flaring. We find that all variables are stationary and mean reverting, but exhibit long-term memory. With aggregate CO2 emissions as a reference, our results suggest that both coal and oil combustion emissions have the weakest degree of long-range dependence, while emissions from gas, and gas flaring have the strongest. With evidence of long memory, we conclude that transitory policy shocks are likely to have long-lasting effects. Although the effects of any active policy on CO2 emissions take longer to disappear, they preserve their temporary nature. Accordingly, permanent effects on CO2 emissions require a more permanent policy stance. In this context, if one were to rely only on testing for stationarity and non-stationarity, one would likely conclude in favor of non-stationarity, and therefore that even transitory policy shocks have permanent effects. Our fractional integration analysis highlights that this is not the case.

Suggested Citation

  • 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.
    • Handle: RePEc:cwm:wpaper:165
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    File URL: http://economics.wm.edu/wp/cwm_wp165_rev2.pdf
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    References listed on IDEAS

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    More about this item

    Keywords

    CO2 emissions; Long memory; ARFIMA model;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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