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Peaking Interest: How Awareness Drives the Effectiveness of Time-of-Use Electricity Pricing

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  • Brian C. Prest

Abstract

I apply and extend a new machine-learning method to estimate heterogeneous electricity demand responses to time-varying prices in an experiment on Irish households. The most important source of heterogeneity is consumer awareness, followed by information provision and baseline consumption. In-home electricity monitors doubled responses. Other household characteristics like demographics, appliance ownership, or house characteristics, were not predictive of heterogeneous effects. Surprisingly, households appeared to violate a central law of demand theory: while they responded to the existence of a price change, they were extremely insensitive to the magnitude of the price change. This suggests that “getting the prices right” is less important than getting consumers to pay attention in the first place.

Suggested Citation

  • Brian C. Prest, 2020. "Peaking Interest: How Awareness Drives the Effectiveness of Time-of-Use Electricity Pricing," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 7(1), pages 103-143.
    • Handle: RePEc:ucp:jaerec:doi:10.1086/705798
    DOI: 10.1086/705798
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    Cited by:

    1. Singhal, Puja, 2024. "Inform me when it matters: Cost salience, energy consumption, and efficiency investments," Energy Economics, Elsevier, vol. 133(C).
    2. Jing Liang & Yueming Qiu & Bo Xing, 2021. "Social Versus Private Benefits of Energy Efficiency Under Time-of-Use and Increasing Block Pricing," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 78(1), pages 43-75, January.
    3. Brewer, Dylan, 2023. "Household responses to winter heating costs: Implications for energy pricing policies and demand-side alternatives," Energy Policy, Elsevier, vol. 177(C).
    4. Singhal, Puja & Pahle, Michael & Kalkuhl, Matthias & Levesque, Antoine & Sommer, Stephan & Berneiser, Jessica, 2022. "Beyond good faith: Why evidence-based policy is necessary to decarbonize buildings cost-effectively in Germany," Energy Policy, Elsevier, vol. 169(C).
    5. Puja Singhal, 2020. "Inform Me When It Matters: Cost Salience, Energy Consumption, and Efficiency Investments," Discussion Papers of DIW Berlin 1891, DIW Berlin, German Institute for Economic Research.
    6. Hortay, Olivér & Kökény, László, 2020. "A villamosenergia-fogyasztás elhalasztásával kapcsolatos lakossági attitűd felmérése Magyarországon [A survey of popular attitudes to deferment of electricity consumption in Hungary]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(7), pages 657-687.
    7. Jesse Burkhardt & Kenneth Gillingham & Praveen K. Kopalle, 2019. "Experimental Evidence on the Effect of Information and Pricing on Residential Electricity Consumption," NBER Working Papers 25576, National Bureau of Economic Research, Inc.
    8. Axenbeck, Janna & Berner, Anne & Kneib, Thomas, 2022. "What drives the relationship between digitalization and industrial energy demand? Exploring firm-level heterogeneity," ZEW Discussion Papers 22-059, ZEW - Leibniz Centre for European Economic Research.
    9. O'Neill, E. & Weeks, M., 2018. "Causal Tree Estimation of Heterogeneous Household Response to Time-Of-Use Electricity Pricing Schemes," Cambridge Working Papers in Economics 1865, Faculty of Economics, University of Cambridge.
    10. Enrich, Jacint & Li, Ruoyi & Mizrahi, Alejandro & Reguant, Mar, 2024. "Measuring the impact of time-of-use pricing on electricity consumption: Evidence from Spain," Journal of Environmental Economics and Management, Elsevier, vol. 123(C).
    11. Lang, Corey & Qiu, Yueming (Lucy) & Dong, Luran, 2023. "Increasing voluntary enrollment in time-of-use electricity rates: Findings from a survey experiment," Energy Policy, Elsevier, vol. 173(C).
    12. Gianluca Trotta & Kirsten Gram-Hanssen & Pernille Lykke Jørgensen, 2020. "Heterogeneity of Electricity Consumption Patterns in Vulnerable Households," Energies, MDPI, vol. 13(18), pages 1-17, September.
    13. Pates, Nicholas J. & Hendricks, Nathan P., 2018. "Estimating Heterogeneous Corn Price Response in the United States," 2018 Annual Meeting, August 5-7, Washington, D.C. 274393, Agricultural and Applied Economics Association.
    14. Blonz, Joshua & Palmer, Karen & Wichman, Casey & Wietelman, Derek C., 2021. "Smart Thermostats, Automation, and Time-Varying Prices," RFF Working Paper Series 21-20, Resources for the Future.
    15. Eoghan O'Neill & Melvyn Weeks, 2018. "Causal Tree Estimation of Heterogeneous Household Response to Time-Of-Use Electricity Pricing Schemes," Papers 1810.09179, arXiv.org, revised Oct 2019.

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