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Does Daylight Saving Save Energy? A Meta-Analysis

Author

Listed:
  • Tomas Havranek

    (Institute of Economic Studies, Faculty of Social Sciences, Charles University in Prague, Smetanovo nabrezi 6, 111 01 Prague 1, Czech Republic
    Czech National Bank)

  • Zuzana Irsova

    (Institute of Economic Studies, Faculty of Social Sciences, Charles University in Prague, Smetanovo nabrezi 6, 111 01 Prague 1, Czech Republic)

  • Dominik Herman

    (Institute of Economic Studies, Faculty of Social Sciences, Charles University in Prague, Smetanovo nabrezi 6, 111 01 Prague 1, Czech Republic)

Abstract

The original rationale for adopting daylight saving time (DST) was energy savings. Modern research studies, however, question the magnitude and even direction of the effect of DST on energy consumption. Representing the first meta-analysis in this literature, we collect 162 estimates from 44 studies and find that the mean reported estimate indicates modest energy savings: 0.34% during the days when DST applies. The literature is not affected by publication bias, but the results vary systematically depending on the exact data and methodology applied. Using Bayesian model averaging we identify the most important factors driving the heterogeneity of the reported effects: data frequency, estimation technique (simulation vs. regression), and, importantly, the latitude of the country considered. Energy savings are larger for countries farther away from the equator, while subtropical regions consume more energy because of DST.

Suggested Citation

  • Tomas Havranek & Zuzana Irsova & Dominik Herman, 2016. "Does Daylight Saving Save Energy? A Meta-Analysis," Working Papers IES 2016/24, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Nov 2016.
    • Handle: RePEc:fau:wpaper:wp2016_24
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    File URL: http://ies.fsv.cuni.cz/sci/publication/show/id/5576/lang/cs
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    Cited by:

    1. López, Miguel, 2020. "Daylight effect on the electricity demand in Spain and assessment of Daylight Saving Time policies," Energy Policy, Elsevier, vol. 140(C).
    2. Havranek, Tomas & Irsova, Zuzana & Vlach, Tomas, 2016. "Publication Bias in Measuring the Income Elasticity of Water Demand," MPRA Paper 75247, University Library of Munich, Germany.
    3. Vaclav Broz & Dominika Kolcunova & Lukas Pfeifer, 2018. "Risk-Sensitive Capital Regulation," Occasional Publications - Edited Volumes, Czech National Bank, Research and Statistics Department, edition 1, volume 16, number rb16/1 edited by Simona Malovana & Jan Frait, July-Dece.
    4. Havranek, Tomas & Irsova, Zuzana & Zeynalova, Olesia, 2017. "Tuition Reduces Enrollment Less Than Commonly Thought," MPRA Paper 78813, University Library of Munich, Germany.
    5. Tomas Havranek & Zuzana Irsova & Tomas Vlach, 2018. "Measuring the Income Elasticity of Water Demand: The Importance of Publication and Endogeneity Biases," Land Economics, University of Wisconsin Press, vol. 94(2), pages 259-283.
    6. Jan Bruha & Jaromir Tonner & Mojmir Hampl & Tomas Havranek & Mirko Djukic & Tibor Hledik & Jiri Polansky & Ljubica Trajcev & Jan Vlcek & Ruslan Aliyev & Dana Hajkova & Ivana Kubicova, 2017. "Effects of Monetary Policy," Occasional Publications - Edited Volumes, Czech National Bank, Research and Statistics Department, edition 2, volume 15, number rb15/2 edited by Jan Babecky & Michal Franta & Jan Bruha, July-Dece.
    7. Shaffer, Blake, 2017. "Location matters: daylight saving time and electricity use," MPRA Paper 84053, University Library of Munich, Germany.
    8. Choi, Seungmoon & Pellen, Alistair & Masson, Virginie, 2017. "How does daylight saving time affect electricity demand? An answer using aggregate data from a natural experiment in Western Australia," Energy Economics, Elsevier, vol. 66(C), pages 247-260.
    9. Bergland, Olvar & Mirza, Faisal, 2017. "Latitudinal Effect on Energy Savings from Daylight Savings Time," Working Paper Series 08-2017, Norwegian University of Life Sciences, School of Economics and Business.

    More about this item

    Keywords

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    JEL classification:

    • C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

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