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Electricity Use as a Real Time Indicator of the Economic Burden of the COVID-19-Related Lockdown: Evidence from Switzerland

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  • Benedikt Janzen
  • Doina Radulescu

Abstract

We employ hourly electricity load data for Switzerland as a real time indicator of the economic e ects of the lockdown following the spread of SARS-CoV-2. Our findings reveal that following the drastic lockdown, overall electricity use decreased by 4 per cent, with a reduction of even 11.3 per cent in the Canton of Ticino where the number of confirmed cases per capita was one of the highest in Switzerland and also stricter measures such as closures of construction sites and industrial companies were implemented on top of federal regulations. Looking at working days only, we estimate a Swiss-wide decrease in electricity consumption of 6.3 per cent. Assuming industry, services, transport and agriculture account for 67 per cent of electricity demand, the 4 per cent decrease in electricity use implies a 6 per cent output reduction in these sectors. In addition, the reduced electricity imports and the change in the generation mix of neighbouring countries, also translates into reduced CO2 emissions related to these imports.

Suggested Citation

  • Benedikt Janzen & Doina Radulescu, 2020. "Electricity Use as a Real Time Indicator of the Economic Burden of the COVID-19-Related Lockdown: Evidence from Switzerland," Diskussionsschriften dp2010, Universitaet Bern, Departement Volkswirtschaft.
    • Handle: RePEc:ube:dpvwib:dp2010
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    References listed on IDEAS

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    1. Kovacs, Roxanne & Dunaiski, Maurice & Tukiainen, Janne, 2020. "Compulsory face mask policies do not affect community mobility in Germany," EconStor Preprints 218945, ZBW - Leibniz Information Centre for Economics.
    2. Csereklyei, Zsuzsanna, 2020. "Price and income elasticities of residential and industrial electricity demand in the European Union," Energy Policy, Elsevier, vol. 137(C).
    3. Sophia Chen & Ms. Deniz O Igan & Mr. Nicola Pierri & Mr. Andrea F Presbitero, 2020. "Tracking the Economic Impact of COVID-19 and Mitigation Policies in Europe and the United States," IMF Working Papers 2020/125, International Monetary Fund.
    4. Tiba, Sofien & Omri, Anis, 2017. "Literature survey on the relationships between energy, environment and economic growth," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 1129-1146.
    5. Baranzini, Andrea & Weber, Sylvain & Bareit, Markus & Mathys, Nicole A., 2013. "The causal relationship between energy use and economic growth in Switzerland," Energy Economics, Elsevier, vol. 36(C), pages 464-470.
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    Cited by:

    1. 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).
    2. Asli Demirgüç-Kunt & Michael Lokshin & Iván Torre, 2021. "Opening-Up Trajectories and Economic Recovery: Lessons after the First Wave of the COVID-19 Pandemic," CESifo Economic Studies, CESifo Group, vol. 67(3), pages 332-369.
    3. Robert Lehmann & Sascha Möhrle, 2024. "Forecasting regional industrial production with novel high‐frequency electricity consumption data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 1918-1935, September.
    4. Benedikt Janzen & Doina Maria Radulescu, 2021. "Effects of Covid-19 Related Government Response Stringency and Support Policies: Evidence from European Firms," CESifo Working Paper Series 9116, CESifo.
    5. Romano, Elliot & Patel, Martin K. & Hollmuller, Pierre, 2024. "Applying trade mechanisms to quantify dynamic GHG emissions of electricity consumption in an open economy - The case of Switzerland," Energy, Elsevier, vol. 311(C).
    6. Janzen, Benedikt & Radulescu, Doina, 2022. "Effects of COVID-19 related government response stringency and support policies: Evidence from European firms," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 129-145.

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    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables

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