IDEAS home Printed from https://ideas.repec.org/a/kap/enreec/v76y2020i4d10.1007_s10640-020-00467-4.html
   My bibliography  Save this article

Real-Time Estimation of the Short-Run Impact of COVID-19 on Economic Activity Using Electricity Market Data

Author

Listed:
  • Carlo Fezzi

    (University of Trento
    University of Exeter Business School)

  • Valeria Fanghella

    (University of Trento)

Abstract

In response to the COVID-19 emergency, many countries have introduced a series of social-distancing measures including lockdowns and businesses’ shutdowns, in an attempt to curb the spread of the infection. Accordingly, the pandemic has been generating unprecedented disruption on practically every aspect of society. This paper demonstrates that high-frequency electricity market data can be used to estimate the causal, short-run impacts of COVID-19 on the economy, providing information that is essential for shaping future lockdown policy. Unlike official statistics, which are published with a delay of a few months, our approach permits almost real-time monitoring of the economic impact of the containment policies and the financial stimuli introduced to address the crisis. We illustrate our methodology using daily data for the Italian day-ahead power market. We estimate that the 3 weeks of most severe lockdown reduced the corresponding Italian Gross Domestic Product (GDP) by roughly 30%. Such negative impacts are now progressively declining but, at the end of June 2020, GDP is still about 8.5% lower than it would have been without the outbreak.

Suggested Citation

  • Carlo Fezzi & Valeria Fanghella, 2020. "Real-Time Estimation of the Short-Run Impact of COVID-19 on Economic Activity Using Electricity Market Data," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 76(4), pages 885-900, August.
  • Handle: RePEc:kap:enreec:v:76:y:2020:i:4:d:10.1007_s10640-020-00467-4
    DOI: 10.1007/s10640-020-00467-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10640-020-00467-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10640-020-00467-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Chen, Sheng-Tung & Kuo, Hsiao-I & Chen, Chi-Chung, 2007. "The relationship between GDP and electricity consumption in 10 Asian countries," Energy Policy, Elsevier, vol. 35(4), pages 2611-2621, April.
    2. Kees Jan Van Garderen & Chandra Shah, 2002. "Exact interpretation of dummy variables in semilogarithmic equations," Econometrics Journal, Royal Economic Society, vol. 5(1), pages 149-159, June.
    3. Giuseppe Cavaliere & Luca Fanelli & Attilio Gardini, 2008. "International dynamic risk sharing," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 1-16.
    4. Backus, David K & Kehoe, Patrick J, 1992. "International Evidence of the Historical Properties of Business Cycles," American Economic Review, American Economic Association, vol. 82(4), pages 864-888, September.
    5. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
    6. Taylor, James W. & de Menezes, Lilian M. & McSharry, Patrick E., 2006. "A comparison of univariate methods for forecasting electricity demand up to a day ahead," International Journal of Forecasting, Elsevier, vol. 22(1), pages 1-16.
    7. Malinauskaite, J. & Jouhara, H. & Ahmad, L. & Milani, M. & Montorsi, L. & Venturelli, M., 2019. "Energy efficiency in industry: EU and national policies in Italy and the UK," Energy, Elsevier, vol. 172(C), pages 255-269.
    8. Zeileis, Achim, 2004. "Econometric Computing with HC and HAC Covariance Matrix Estimators," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 11(i10).
    9. J. Vernon Henderson & Adam Storeygard & David N. Weil, 2012. "Measuring Economic Growth from Outer Space," American Economic Review, American Economic Association, vol. 102(2), pages 994-1028, April.
    10. Jaqueson K. Galimberti, 2020. "Forecasting GDP Growth from Outer Space," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(4), pages 697-722, August.
    11. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    12. Halvorsen, Robert & Palmquist, Raymond, 1980. "The Interpretation of Dummy Variables in Semilogarithmic Equations," American Economic Review, American Economic Association, vol. 70(3), pages 474-475, June.
    13. Carlo Fezzi & Derek Bunn, 2010. "Structural Analysis of Electricity Demand and Supply Interactions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(6), pages 827-856, December.
    14. Carlo Fezzi and Luca Mosetti, 2020. "Size Matters: Estimation Sample Length and Electricity Price Forecasting Accuracy," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 231-254.
    15. Takashi Hattori & Hoseok Nam, 2020. "Essence of Multilateral Energy Technology Collaboration:A Case Study of International Energy Agency (IEA) Technology Collaboration Programmes (TCPs)," KIER Working Papers 1023, Kyoto University, Institute of Economic Research.
    Full references (including those not matched with items on IDEAS)

    Citations

    RePEc Biblio mentions

    As found on the RePEc Biblio, the curated bibliography for Economics:
    1. > Economics of Welfare > Health Economics > Economics of Pandemics > Specific pandemics > Covid-19 > Health > Distancing and Lockdown > Effect on Economy

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Paul,Boban Varghese & Finn,Arden Jeremy & Chaudhary,Sarang & Mayer Gukovas,Renata & Sundaram,Ramya, 2021. "COVID-19, Poverty, and Social Safety Net Response in Zambia," Policy Research Working Paper Series 9571, The World Bank.
    2. Jan Niklas Buescher & Daria Gottwald & Florian Momm & Alexander Zureck, 2022. "Impact of the COVID-19 Pandemic Crisis on the Efficiency of European Intraday Electricity Markets," Energies, MDPI, vol. 15(10), pages 1-21, May.
    3. Abel Brodeur & David Gray & Anik Islam & Suraiya Bhuiyan, 2021. "A literature review of the economics of COVID‐19," Journal of Economic Surveys, Wiley Blackwell, vol. 35(4), pages 1007-1044, September.
    4. Eryarsoy, Enes & Shahmanzari, Masoud & Tanrisever, Fehmi, 2023. "Models for government intervention during a pandemic," European Journal of Operational Research, Elsevier, vol. 304(1), pages 69-83.
    5. Jasper Verschuur & Elco E Koks & Jim W Hall, 2021. "Global economic impacts of COVID-19 lockdown measures stand out in high-frequency shipping data," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-16, April.
    6. Olympia Bover & Natalia Fabra & Sandra García-Uribe & Aitor Lacuesta & Roberto Ramos, 2020. "Firms and households during the pandemic: what do we learn from their electricity consumption?," Occasional Papers 2031, Banco de España.
    7. Tung Le Thanh, 2022. "Relationship between the COVID-19 pandemic and the macroeconomic indicators: Evidence from a global analysis," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 16(1), pages 785-791, August.
    8. Werth, Annette & Gravino, Pietro & Prevedello, Giulio, 2021. "Impact analysis of COVID-19 responses on energy grid dynamics in Europe," Applied Energy, Elsevier, vol. 281(C).
    9. Guglielmo Maria Caporale & Abdurrahman Nazif Catik & Mohamad Husam Helmi & Coskun Akdeniz & Ali Ilhan, 2021. "The Effects of the Covid-19 Pandemic on Stock Markets, CDS and Economic Activity: Time-Varying Evidence from the US and Europe," CESifo Working Paper Series 9316, CESifo.
    10. García, Sebastián & Parejo, Antonio & Personal, Enrique & Ignacio Guerrero, Juan & Biscarri, Félix & León, Carlos, 2021. "A retrospective analysis of the impact of the COVID-19 restrictions on energy consumption at a disaggregated level," Applied Energy, Elsevier, vol. 287(C).
    11. Cerqueira, Pedro André & Pereira da Silva, Patrícia, 2023. "Assessment of the impact of COVID-19 lockdown measures on electricity consumption – Evidence from Portugal and Spain," Energy, Elsevier, vol. 282(C).
    12. Enza Simeone, 2024. "Assessing the effect of the COVID-19 pandemic on wellbeing: a comparison between CBA and SWF approaches for policies evaluation," Working Papers 662, ECINEQ, Society for the Study of Economic Inequality.
    13. Ai, Hongshan & Zhong, Tenglong & Zhou, Zhengqing, 2022. "The real economic costs of COVID-19: Insights from electricity consumption data in Hunan Province, China," Energy Economics, Elsevier, vol. 105(C).
    14. Fezzi, Carlo & Fanghella, Valeria, 2021. "Tracking GDP in real-time using electricity market data: Insights from the first wave of COVID-19 across Europe," European Economic Review, Elsevier, vol. 139(C).
    15. Malaczewska Paulina & Malaczewski Maciej, 2022. "Marriage, divorce and coronavirus—theoretical analysis of the influence of COVID-19 on family capital," Economics and Business Review, Sciendo, vol. 8(3), pages 126-142, October.
    16. Lazo, Joaquín & Aguirre, Gerson & Watts, David, 2022. "An impact study of COVID-19 on the electricity sector: A comprehensive literature review and Ibero-American survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    17. Mauritzen, Johannes, 2021. "The Covid-19 shock on a low-carbon grid: Evidence from the nordics," Energy Policy, Elsevier, vol. 156(C).
    18. Chen Zhu & Rigoberto A. Lopez & Yuan Gao & Xiaoou Liu, 2021. "The COVID‐19 Pandemic and Consumption of Food away from Home: Evidence from High‐frequency Restaurant Transaction Data," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 29(6), pages 73-94, November.
    19. Jacek Artur Strojny & Michał Stanisław Chwastek & Elżbieta Badach & Sławomir Jacek Lisek & Piotr Kacorzyk, 2022. "Impacts of COVID-19 on Energy Expenditures of Local Self-Government Units in Poland," Energies, MDPI, vol. 15(4), pages 1-25, February.
    20. Luis M. Abadie, 2021. "Energy Market Prices in Times of COVID-19: The Case of Electricity and Natural Gas in Spain," Energies, MDPI, vol. 14(6), pages 1-17, March.
    21. Gagnon, Joseph E. & Kamin, Steven B. & Kearns, John, 2023. "The impact of the COVID-19 pandemic on global GDP growth," Journal of the Japanese and International Economies, Elsevier, vol. 68(C).
    22. Barbara Kowal & Robert Ranosz & Łukasz Herezy & Wojciech Cichy & Olga Świniarska & Lucia Domaracka, 2022. "Overview of Taken Initiatives and Adaptation Measures in Polish Mining Companies during a Pandemic," Energies, MDPI, vol. 15(17), pages 1-20, September.

    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. Carlo Fezzi & Valeria Fanghella, 2020. "Real-time estimation of the short-run impact of COVID-19 on economic activity using electricity market data," DEM Working Papers 2020/8, Department of Economics and Management.
    2. Carlo Fezzi & Valeria Fanghella, 2020. "Real-time estimation of the short-run impact of COVID-19 on economic activity using electricity market data," Papers 2007.03477, arXiv.org.
    3. Fezzi, Carlo & Fanghella, Valeria, 2021. "Tracking GDP in real-time using electricity market data: Insights from the first wave of COVID-19 across Europe," European Economic Review, Elsevier, vol. 139(C).
    4. Jacek Artur Strojny & Michał Stanisław Chwastek & Elżbieta Badach & Sławomir Jacek Lisek & Piotr Kacorzyk, 2022. "Impacts of COVID-19 on Energy Expenditures of Local Self-Government Units in Poland," Energies, MDPI, vol. 15(4), pages 1-25, February.
    5. Bashiri Behmiri, Niaz & Fezzi, Carlo & Ravazzolo, Francesco, 2023. "Incorporating air temperature into mid-term electricity load forecasting models using time-series regressions and neural networks," Energy, Elsevier, vol. 278(C).
    6. Beyer, Robert C.M. & Franco-Bedoya, Sebastian & Galdo, Virgilio, 2021. "Examining the economic impact of COVID-19 in India through daily electricity consumption and nighttime light intensity," World Development, Elsevier, vol. 140(C).
    7. Raviv, Eran & Bouwman, Kees E. & van Dijk, Dick, 2015. "Forecasting day-ahead electricity prices: Utilizing hourly prices," Energy Economics, Elsevier, vol. 50(C), pages 227-239.
    8. Carlo Fezzi & Luca Mosetti, 2018. "Size matters: Estimation sample length and electricity price forecasting accuracy," DEM Working Papers 2018/10, Department of Economics and Management.
    9. Smith, Michael Stanley & Shively, Thomas S., 2018. "Econometric modeling of regional electricity spot prices in the Australian market," Energy Economics, Elsevier, vol. 74(C), pages 886-903.
    10. Malte Knüppel & Fabian Krüger, 2022. "Forecast uncertainty, disagreement, and the linear pool," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 23-41, January.
    11. Edward Nelson, 2012. "The correlation between money and output in the United Kingdom: resolution of a puzzle," Finance and Economics Discussion Series 2012-29, Board of Governors of the Federal Reserve System (U.S.).
    12. Haseeb Ahmed & Benjamin W. Cowan, 2019. "Mobile Money and Healthcare Use: Evidence from East Africa," NBER Working Papers 25669, National Bureau of Economic Research, Inc.
    13. Krüger, Fabian & Nolte, Ingmar, 2016. "Disagreement versus uncertainty: Evidence from distribution forecasts," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 172-186.
    14. Markus Behn & Rainer Haselmann & Vikrant Vig, 2022. "The Limits of Model‐Based Regulation," Journal of Finance, American Finance Association, vol. 77(3), pages 1635-1684, June.
    15. Blackburn, McKinley L., 2007. "Estimating wage differentials without logarithms," Labour Economics, Elsevier, vol. 14(1), pages 73-98, January.
    16. Jean-Sauveur Ay & Jean-Marc Brayer & Jean Cavailhès & Pierre Curmi & Mohamed Hilal & Marjorie Ubertosi, 2012. "La valeur des attributs naturels des terres agricoles de Côte-d'Or," INRA UMR CESAER Working Papers 2012/1, INRA UMR CESAER, Centre d'’Economie et Sociologie appliquées à l'’Agriculture et aux Espaces Ruraux.
    17. Luca Benati, 2005. "U.K. Monetary Regimes and Macroeconomic Stylised Facts," Computing in Economics and Finance 2005 107, Society for Computational Economics.
    18. Petjon Ballco & Fatma Jaafer & Tiziana de Magistris, 2022. "Investigating the price effects of honey quality attributes in a European country: Evidence from a hedonic price approach," Agribusiness, John Wiley & Sons, Ltd., vol. 38(4), pages 885-904, October.
    19. Jonathan Colmer, 2021. "Temperature, Labor Reallocation, and Industrial Production: Evidence from India," American Economic Journal: Applied Economics, American Economic Association, vol. 13(4), pages 101-124, October.
    20. Silvia Golia & Luigi Grossi & Matteo Pelagatti, 2022. "Machine Learning Models and Intra-Daily Market Information for the Prediction of Italian Electricity Prices," Forecasting, MDPI, vol. 5(1), pages 1-21, December.

    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:kap:enreec:v:76:y:2020:i:4:d:10.1007_s10640-020-00467-4. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.