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The zonal and seasonal CO2 marginal emissions factors for the Italian power market

Author

Listed:
  • Filippo Beltrami

    (Department of Economics (University of Verona))

  • Fulvio Fontini

    (University of Padua)

  • Monica Giulietti

    (Loughborough University)

  • Luigi Grossi

    (Department of Economics (University of Verona))

Abstract

This paper estimates the seasonal and zonal CO2 marginal emissions factors (MEFs) from electricity production in the Italian electricity system. The inclusion of the zonal configuration of the Italian wholesale power market leads to a complete measurement of marginal emission factors which takes into account the heterogeneous distribution of RES power plants, their penetration rate and their variability within the zonal power generation mix. This article relies on the fractional cointegration methodology to incorporate the typical features of long memory processes into the estimation of MEFs. We find high variability in annual MEFs estimated at the zonal level. Sardinia reports the highest MEF (0.7189 tCO2/MWh), followed by the Center South (0.7022 tCO2/MWh), the Center North (0.4236 tCO2/MWh), the North (0.2018 tCO2/MWh) and Sicily (0.146 tCO2/MWh). The seasonal analysis also shows a large variability of MEFs in each zone across time. The heterogeneity of results leads us to recommend that policymakers consider the zonal configuration of the power market and the large seasonal variability related to carbon emissions and electricity generation when designing incentives for Renewable Energy Sources (RES) expansion and for achieving emission reduction targets.

Suggested Citation

  • Filippo Beltrami & Fulvio Fontini & Monica Giulietti & Luigi Grossi, 2021. "The zonal and seasonal CO2 marginal emissions factors for the Italian power market," Working Papers 01/2021, University of Verona, Department of Economics.
    • Handle: RePEc:ver:wpaper:01/2021
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    References listed on IDEAS

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    1. Søren Johansen & Morten Ørregaard Nielsen, 2012. "Likelihood Inference for a Fractionally Cointegrated Vector Autoregressive Model," Econometrica, Econometric Society, vol. 80(6), pages 2667-2732, November.
    2. Maggie E. C. Jones & Morten Ørregaard Nielsen & Michał Ksawery Popiel, 2014. "A fractionally cointegrated VAR analysis of economic voting and political support," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 47(4), pages 1078-1130, November.
    3. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    4. Voorspools, Kris R. & D'haeseleer, William D., 2000. "An evaluation method for calculating the emission responsibility of specific electric applications," Energy Policy, Elsevier, vol. 28(13), pages 967-980, November.
    5. Anna Cretì & Fulvio Fontini, 2019. "Economics of Electricity. Markets, Competition and Rules," Post-Print hal-02304345, HAL.
    6. Zivot, Eric & Andrews, Donald W K, 2002. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 25-44, January.
    7. Cretì,Anna & Fontini,Fulvio, 2019. "Economics of Electricity," Cambridge Books, Cambridge University Press, number 9781316636626.
    8. Sepideh Dolatabadi & Morten Ørregaard Nielsen & Ke Xu, 2015. "A Fractionally Cointegrated VAR Analysis of Price Discovery in Commodity Futures Markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 35(4), pages 339-356, April.
    9. Federico Carlini & Paolo Santucci de Magistris, 2019. "On the Identification of Fractionally Cointegrated VAR Models With the Condition," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(1), pages 134-146, January.
    10. Hawkes, A.D., 2014. "Long-run marginal CO2 emissions factors in national electricity systems," Applied Energy, Elsevier, vol. 125(C), pages 197-205.
    11. Beltrami, Filippo & Burlinson, Andrew & Giulietti, Monica & Grossi, Luigi & Rowley, Paul & Wilson, Grant, 2020. "Where did the time (series) go? Estimation of marginal emission factors with autoregressive components," Energy Economics, Elsevier, vol. 91(C).
    12. Lucas Bretschger & Karen Pittel, 2020. "Twenty Key Challenges in Environmental and Resource Economics," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 77(4), pages 725-750, December.
    13. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    14. Tensay Hadush Meles & Lisa Ryan & Joe Wheatley, 2020. "COVID-19 and EU Climate Targets: Can We Now Go Further?," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 76(4), pages 779-787, August.
    15. Morten Ø. Nielsen & Michal Ksawery Popiel, 2018. "A Matlab Program And User's Guide For The Fractionally Cointegrated Var Model," Working Paper 1330, Economics Department, Queen's University.
    16. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    17. Pelagatti, Matteo M. & Sen, Pranab K., 2013. "Rank tests for short memory stationarity," Journal of Econometrics, Elsevier, vol. 172(1), pages 90-105.
    18. Johansen, Søren & Nielsen, Morten Ørregaard, 2016. "The Role Of Initial Values In Conditional Sum-Of-Squares Estimation Of Nonstationary Fractional Time Series Models," Econometric Theory, Cambridge University Press, vol. 32(5), pages 1095-1139, October.
    19. Morten Ørregaard Nielsen & Michał Ksawery Popiel, 2018. "A Matlab program and user's guide for the fractionally cointegrated VAR model," Working Papers 1330, Queen's University, Department of Economics.
    20. Carson, Richard T. & Novan, Kevin, 2013. "The private and social economics of bulk electricity storage," Journal of Environmental Economics and Management, Elsevier, vol. 66(3), pages 404-423.
    21. Johansen, SØren, 2008. "A Representation Theory For A Class Of Vector Autoregressive Models For Fractional Processes," Econometric Theory, Cambridge University Press, vol. 24(3), pages 651-676, June.
    22. Bettle, R. & Pout, C.H. & Hitchin, E.R., 2006. "Interactions between electricity-saving measures and carbon emissions from power generation in England and Wales," Energy Policy, Elsevier, vol. 34(18), pages 3434-3446, December.
    23. Valeria Di Cosmo & Laura Malaguzzi Valeri, 2018. "How Much Does Wind Power Reduce $$\text {CO}_{2}$$ CO 2 Emissions? Evidence from the Irish Single Electricity Market," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 71(3), pages 645-669, November.
    24. Rafal Weron, 2006. "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach," HSC Books, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number hsbook0601, December.
    25. Oliveira, Tiago & Varum, Celeste & Botelho, Anabela, 2019. "Econometric modeling of CO2 emissions abatement: Comparing alternative approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 105(C), pages 310-322.
    26. James G. MacKinnon & Morten Ørregaard Nielsen, 2014. "Numerical Distribution Functions Of Fractional Unit Root And Cointegration Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(1), pages 161-171, January.
    27. C. W. J. Granger & Roselyne Joyeux, 1980. "An Introduction To Long‐Memory Time Series Models And Fractional Differencing," Journal of Time Series Analysis, Wiley Blackwell, vol. 1(1), pages 15-29, January.
    28. Beltrami, Filippo & Fontini, Fulvio & Grossi, Luigi, 2021. "The value of carbon emission reduction induced by Renewable Energy Sources in the Italian power market," Ecological Economics, Elsevier, vol. 189(C).
    29. Hawkes, A.D., 2010. "Estimating marginal CO2 emissions rates for national electricity systems," Energy Policy, Elsevier, vol. 38(10), pages 5977-5987, October.
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    Cited by:

    1. Beltrami, Filippo, 2024. "The impact of hydroelectric storage in Northern Italy’s power market," Energy Policy, Elsevier, vol. 191(C).
    2. Beltrami, Filippo & Fontini, Fulvio & Grossi, Luigi, 2021. "The value of carbon emission reduction induced by Renewable Energy Sources in the Italian power market," Ecological Economics, Elsevier, vol. 189(C).

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    More about this item

    Keywords

    Decarbonization; Electricity Price; Fractional Cointegration; Marginal Emission Factor (MEF); Renewable Energy Sources (RES);
    All these keywords.

    JEL classification:

    • P18 - Political Economy and Comparative Economic Systems - - Capitalist Economies - - - Energy; Environment
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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