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An Alternative Reference Scenario for Global CO2Emissions from Fuel Consumption: An ARFIMA Approach

Author

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  • 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 note, we establish an alternative reference scenario based on an ARFIMA estimated using global CO2 emissions from 1750 to 2013. These new reference forecasts are free from additional assumptions on demographic and economic variables, often used in most reference forecasts. Instead, we only rely on the properties of the underlying stochastic process for global CO2 emissions that are, in this sense, closer to fundamentals. Our reference forecasts are clearly below the levels proposed by other reference scenarios available in the literature. This is important, as it suggests that the ongoing policy goals are actually easier to reach than what is implied by the standard reference scenarios. Having lower and more realistic reference emissions projections gives a truer assessment of the policy efforts that are needed, and highlights the lower costs involved in mitigation efforts, thereby maximizing the likelihood of more widespread environmental policy efforts.

Suggested Citation

  • José M. Belbute & Alfredo Marvão Pereira, 2015. "An Alternative Reference Scenario for Global CO2Emissions from Fuel Consumption: An ARFIMA Approach," Working Papers 164, Department of Economics, College of William and Mary.
  • Handle: RePEc:cwm:wpaper:164
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    References listed on IDEAS

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    1. repec:pre:wpaper:201528 is not listed on IDEAS
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    Cited by:

    1. Abas, N. & Kalair, A. & Khan, N. & Kalair, A.R., 2017. "Review of GHG emissions in Pakistan compared to SAARC countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 990-1016.
    2. Sugiawan, Yogi & Kurniawan, Robi & Managi, Shunsuke, 2019. "Are carbon dioxide emission reductions compatible with sustainable well-being?," Applied Energy, Elsevier, vol. 242(C), pages 1-11.
    3. Bikramaditya Ghosh & Spyros Papathanasiou & Georgios Pergeris, 2022. "Did cryptocurrencies exhibit log‐periodic power law signature during the second wave of COVID‐19?," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 51(3), November.
    4. Chun-Cheng Lin & Rou-Xuan He & Wan-Yu Liu, 2018. "Considering Multiple Factors to Forecast CO 2 Emissions: A Hybrid Multivariable Grey Forecasting and Genetic Programming Approach," Energies, MDPI, vol. 11(12), pages 1-25, December.
    5. Belbute, José M. & Pereira, Alfredo M., 2020. "Reference forecasts for CO2 emissions from fossil-fuel combustion and cement production in Portugal," Energy Policy, Elsevier, vol. 144(C).
    6. 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.
    7. José M. Belbute & Alfredo M. Pereira, 2021. "The Relationship between Consumption and CO 2 Emissions: Evidence for Portugal," Sustainability, MDPI, vol. 13(21), pages 1-16, November.
    8. 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).

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    More about this item

    Keywords

    Forecasting; reference scenario; CO2emissions; fuel; long memory; ARFIMA.;
    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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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