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. Galdi, Giulio & Casarin, Roberto & Ferrari, Davide & Fezzi, Carlo & Ravazzolo, Francesco, 2023. "Nowcasting industrial production using linear and non-linear models of electricity demand," Energy Economics, Elsevier, vol. 126(C).
    6. 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.
    7. Olympia Bover & Natalia Fabra & Sandra García-Uribe & Aitor Lacuesta & Roberto Ramos, 2023. "Firms and Households during the Pandemic: What Do We Learn from Their Electricity Consumption?," The Energy Journal, , vol. 44(3), pages 267-288, May.
    8. 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.
    9. 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).
    10. 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.
    11. 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).
    12. 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).
    13. 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.
    14. 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).
    15. 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).
    16. 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.
    17. 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).
    18. Mauritzen, Johannes, 2021. "The Covid-19 shock on a low-carbon grid: Evidence from the nordics," Energy Policy, Elsevier, vol. 156(C).
    19. 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.
    20. Guglielmo Maria Caporale & Abdurrahman Nazif Çatık & Mohamad Husam Helmi & Coşkun Akdeniz & Ali İlhan, 2024. "Time-varying effects of the COVID-19 pandemic on stock markets and economic activity: evidence from the US and Europe," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 51(2), pages 529-558, May.
    21. Huthaifa Alqaralleh & Awon Almajali & Alessandra Canepa, 2024. "Navigating Energy Market Cycles: Insights from a Comprehensive Analysis," International Journal of Energy Economics and Policy, Econjournals, vol. 14(5), pages 35-48, September.
    22. 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.
    23. 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.
    24. 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).
    25. 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," Papers 2007.03477, arXiv.org.
    2. 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.
    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. Mehdi Abid & Rafaa Mraihi, 2015. "Energy Consumption and Industrial Production: Evidence from Tunisia at Both Aggregated and Disaggregated Levels," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 6(4), pages 1123-1137, December.
    7. 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).
    8. Menezes, Flavio & Figer, Vivian & Jardim, Fernanda & Medeiros, Pedro, 2022. "A near real-time economic activity tracker for the Brazilian economy during the COVID-19 pandemic," Economic Modelling, Elsevier, vol. 112(C).
    9. Evangelista, Rui & Ramalho, Esmeralda A. & Andrade e Silva, João, 2020. "On the use of hedonic regression models to measure the effect of energy efficiency on residential property transaction prices: Evidence for Portugal and selected data issues," Energy Economics, Elsevier, vol. 86(C).
    10. Omoniyi Alimi & Geua Boe-Gibson & John Gibson, 2022. "Noisy Night Lights Data: Effects on Research Findings for Developing Countries," Working Papers in Economics 22/12, University of Waikato.
    11. 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.
    12. Gary Gorton & Frank Schmid, 2000. "Class Struggle Inside the Firm: A Study of German Codetermination," NBER Working Papers 7945, National Bureau of Economic Research, Inc.
    13. Ball, Laurence & Carvalho, Carlos & Evans, Christopher & Antonio Ricci, Luca, 2024. "Weighted Median Inflation Around the World: A Measure of Core Inflation," Journal of International Money and Finance, Elsevier, vol. 142(C).
    14. Cecchetti, Stephen G. & Kashyap, Anil K, 1996. "International cycles," European Economic Review, Elsevier, vol. 40(2), pages 331-360, February.
    15. Salah Bouktif & Ali Fiaz & Ali Ouni & Mohamed Adel Serhani, 2018. "Optimal Deep Learning LSTM Model for Electric Load Forecasting using Feature Selection and Genetic Algorithm: Comparison with Machine Learning Approaches †," Energies, MDPI, vol. 11(7), pages 1-20, June.
    16. Timo Dimitriadis & Xiaochun Liu & Julie Schnaitmann, 2020. "Encompassing Tests for Value at Risk and Expected Shortfall Multi-Step Forecasts based on Inference on the Boundary," Papers 2009.07341, arXiv.org.
    17. Mohamad A. Abou Hamia, 2016. "Jobless growth: empirical evidences from the Middle East and North Africa region [Wachstum ohne Beschäftigung – empirische Evidenz aus Nahost und Nordafrika]," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 49(3), pages 239-251, November.
    18. 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.
    19. 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.
    20. 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.

    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.