IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i20p7501-d939921.html
   My bibliography  Save this article

Electricity Demand Elasticity, Mobility, and COVID-19 Contagion Nexus in the Italian Day-Ahead Electricity Market

Author

Listed:
  • Carlo Andrea Bollino

    (Perugia Energy Environment Research Center, 06123 Perugia, Italy
    KAPSARC, Riyadh 11672, Saudi Arabia)

  • Maria Chiara D’Errico

    (Department of Economics, University of Perugia, 06123 Perugia, Italy)

Abstract

The magnitude of the impact of the pandemic on key variables, such as electricity demand, mobility of people and number of COVID-19 hospitalization cases, has been unprecedented. Existing economic models have not estimated the impact of sucokh events. This paper fills this gap, investigating the nexus among electricity demand elasticity, shifting behaviors of mobility and COVID-19 contagion with econometric estimation techniques. Firstly, using the single bids to purchase recorded in the Italian day-ahead wholesale electricity market in 2020, we estimate hourly electricity demand and price elasticity directly from short-run consumer behavior. Then, we analyze the effects of the main aspects of the pandemic, the health situation and the mobility contraction at the national level, on the estimated price elasticities. The period of heavy lockdown between 10 March and 3 June recorded a reduction in the price elasticity of electricity demand. However, when the pandemic broke out again at the beginning of October, elasticity increased, highlighting how companies and economic activities had adopted countermeasures to avoid the arrest of the economy and, consequently, the sharp contraction in electricity demand.

Suggested Citation

  • Carlo Andrea Bollino & Maria Chiara D’Errico, 2022. "Electricity Demand Elasticity, Mobility, and COVID-19 Contagion Nexus in the Italian Day-Ahead Electricity Market," Energies, MDPI, vol. 15(20), pages 1-26, October.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:20:p:7501-:d:939921
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/20/7501/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/20/7501/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Simona Bigerna and Carlo Andrea Bollino, 2014. "Electricity Demand in Wholesale Italian Market," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    2. Qu, Hui & Duan, Qingling & Niu, Mengyi, 2018. "Modeling the volatility of realized volatility to improve volatility forecasts in electricity markets," Energy Economics, Elsevier, vol. 74(C), pages 767-776.
    3. Apadula, Francesco & Bassini, Alessandra & Elli, Alberto & Scapin, Simone, 2012. "Relationships between meteorological variables and monthly electricity demand," Applied Energy, Elsevier, vol. 98(C), pages 346-356.
    4. Wang, Qiang & Li, Shuyu & Li, Rongrong, 2018. "Forecasting energy demand in China and India: Using single-linear, hybrid-linear, and non-linear time series forecast techniques," Energy, Elsevier, vol. 161(C), pages 821-831.
    5. Bollino, Carlo Andrea, 1987. "Gaids: a generalised version of the almost ideal demand system," Economics Letters, Elsevier, vol. 23(2), pages 199-202.
    6. Faheem Jan & Ismail Shah & Sajid Ali, 2022. "Short-Term Electricity Prices Forecasting Using Functional Time Series Analysis," Energies, MDPI, vol. 15(9), pages 1-15, May.
    7. Halbrügge, Stephanie & Buhl, Hans Ulrich & Fridgen, Gilbert & Schott, Paul & Weibelzahl, Martin & Weissflog, Jan, 2022. "How Germany achieved a record share of renewables during the COVID-19 pandemic while relying on the European interconnected power network," Energy, Elsevier, vol. 246(C).
    8. Şahin, Utkucan & Ballı, Serkan & Chen, Yan, 2021. "Forecasting seasonal electricity generation in European countries under Covid-19-induced lockdown using fractional grey prediction models and machine learning methods," Applied Energy, Elsevier, vol. 302(C).
    9. Maria Chiara D'Errico & Carlo Andrea Bollino, 2015. "Bayesian Analysis of Demand Elasticity in the Italian Electricity Market," Sustainability, MDPI, vol. 7(9), pages 1-22, September.
    10. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-326, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rowland, Christopher S. & Mjelde, James W. & Dharmasena, Senarath, 2017. "Policy implications of considering pre-commitments in U.S. aggregate energy demand system," Energy Policy, Elsevier, vol. 102(C), pages 406-413.
    2. Tarek Atalla & Simona Bigerna & Carlo Andrea Bollino, 2018. "Energy demand elasticities and weather worldwide," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 35(1), pages 207-237, April.
    3. James W. Mjelde & Kannika Duangnate, 2023. "Overview of Committed Quantities in Commodity Demand Analysis with a Focus on Energy," Energies, MDPI, vol. 16(11), pages 1-17, May.
    4. Hovhannisyan, Vardges & Stiegert, Kyle W. & Bozic, Marin, 2013. "On Endogeneity Of Retail Market Power In An Equilibrium Analysis: A Control Function Approach," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 149830, Agricultural and Applied Economics Association.
    5. Anonymous & Bosch, Darrell J., 2013. "Table of contents," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 45(01), February.
    6. Faheem Jan & Ismail Shah & Sajid Ali, 2022. "Short-Term Electricity Prices Forecasting Using Functional Time Series Analysis," Energies, MDPI, vol. 15(9), pages 1-15, May.
    7. Rahman, Kazi Tamim & Shanoyan, Aleksan & Hovhannisyan, Vardges, 2021. "Food Commodity Price Hikes, Public Policy, and Consumer Welfare: Lessons from Bangladesh," 2021 Annual Meeting, August 1-3, Austin, Texas 314076, Agricultural and Applied Economics Association.
    8. Hovhannisyan, Vardges & Shanoyan, Aleksan, 2018. "An Empirical Analysis Of Welfare Consequences Of Rising Food Prices In Urban China: The Easi Approach," 2018 Annual Meeting, August 5-7, Washington, D.C. 273987, Agricultural and Applied Economics Association.
    9. Vardges Hovhannisyan & Hayk Khachatryan, 2017. "Ornamental Plants in the United States: An Econometric Analysis of a Household‐Level Demand System," Agribusiness, John Wiley & Sons, Ltd., vol. 33(2), pages 226-241, April.
    10. Vardges Hovhannisyan & Sachintha Mendis & Chris Bastian, 2019. "An econometric analysis of demand for food quantity and quality in urban China," Agricultural Economics, International Association of Agricultural Economists, vol. 50(1), pages 3-13, January.
    11. Gallet, Craig A., 2010. "The income elasticity of meat: a meta-analysis," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 54(4), pages 1-14.
    12. Vardges Hovhannisyan & Marin Bozic, 2017. "Price Endogeneity and Food Demand in Urban China," Journal of Agricultural Economics, Wiley Blackwell, vol. 68(2), pages 386-406, June.
    13. Simona Bigerna and Carlo Andrea Bollino, 2015. "A System Of Hourly Demand in the Italian Electricity Market," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    14. Tarek Atalla & Simona Bigerna & Carlo Andrea Bollino & Rolando Fuentes, 2017. "Analyzing the effects of renewable energy and climate conditions on consumer welfare," The Energy Journal, , vol. 38(1_suppl), pages 115-136, June.
    15. Ghazaryan, Armen & Bonanno, Alessandro & Carlson, Andrea, 2023. "I Say Milk, You Say Mylk. Demand Separability in a Broadened Milk Category," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 48(2), May.
    16. Vardges Hovhannisyan & Brian W. Gould, 2014. "Structural change in urban Chinese food preferences," Agricultural Economics, International Association of Agricultural Economists, vol. 45(2), pages 159-166, March.
    17. Hasnain Iftikhar & Josue E. Turpo-Chaparro & Paulo Canas Rodrigues & Javier Linkolk López-Gonzales, 2023. "Forecasting Day-Ahead Electricity Prices for the Italian Electricity Market Using a New Decomposition—Combination Technique," Energies, MDPI, vol. 16(18), pages 1-23, September.
    18. Kamel Elouhichi & Pascal Tillie & Aymeric Ricome & Sergio Gomez-Y-Paloma, 2020. "Modelling Farm-household Livelihoods in Developing Economies: Insights from three country case studies using LSMS-ISA data," JRC Research Reports JRC118822, Joint Research Centre.
    19. Simona Bigerna & Carlo Andrea Bollino & Maria Chiara D’Errico, 2020. "A general expenditure system for estimation of consumer demand functions," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 37(3), pages 1071-1088, October.
    20. Okrent, Abigail M. & Alston, Julian M., 2011. "Demand for Food in the United States: A Review of Literature, Evaluation of Previous Estimates, and Presentation of New Estimates of Demand," Monographs, University of California, Davis, Giannini Foundation, number 251908.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:20:p:7501-:d:939921. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.