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Household Response to Time-Varying Electricity Prices

Author

Listed:
  • Matthew Harding

    (Department of Economics, University of California, Irvine, California 92697)

  • Steven Sexton

    (Sanford School of Public Policy, Duke University, Durham, North Carolina 27708)

Abstract

The diffusion of smart metering technology and intermittent renewable electricity generation capacity makes the deployment of time-varying electricity rates increasingly feasible and important to the functioning of electricity grids. Such rates, which economists advocate to more efficiently match supply and demand, remain rare, though experiments assessing consumer responses are not. This review synthesizes evaluations of these experiments in the context of a theory of consumer inattention and adjustment costs that posits a role for automation technology to boost the short-run price elasticity of demand and affect demand-side reductions that can lower generation costs.

Suggested Citation

  • Matthew Harding & Steven Sexton, 2017. "Household Response to Time-Varying Electricity Prices," Annual Review of Resource Economics, Annual Reviews, vol. 9(1), pages 337-359, October.
  • Handle: RePEc:anr:reseco:v:9:y:2017:p:337-359
    DOI: 10.1146/annurev-resource-100516-053437
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    Citations

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    Cited by:

    1. 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.
    2. Harding, Matthew & Kettler, Kyle & Lamarche, Carlos & Ma, Lala, 2023. "The (alleged) environmental and social benefits of dynamic pricing," Journal of Economic Behavior & Organization, Elsevier, vol. 205(C), pages 574-593.
    3. Alexandre Mayol & Carine Staropoli, 2021. "Giving consumers too many choices: a false good idea? A lab experiment on water and electricity tariffs," European Journal of Law and Economics, Springer, vol. 51(2), pages 383-410, April.
    4. Stelmach, Greg & Zanocco, Chad & Flora, June & Rajagopal, Ram & Boudet, Hilary S., 2020. "Exploring household energy rules and activities during peak demand to better determine potential responsiveness to time-of-use pricing," Energy Policy, Elsevier, vol. 144(C).
    5. Kim, Jihyo & Lee, Soomin & Jang, Heesun, 2022. "Lessons from residential electricity demand analysis on the time of use pricing experiment in South Korea," Energy Economics, Elsevier, vol. 113(C).
    6. Leslie A. Martin, 2022. "Driving on Sunbeams: Interactions Between Price Incentives for Electric Vehicles, Residential Solar Photovoltaics and Household Battery Systems," Economic Papers, The Economic Society of Australia, vol. 41(4), pages 369-384, December.
    7. Fabra, Natalia, 2021. "The energy transition: An industrial economics perspective," International Journal of Industrial Organization, Elsevier, vol. 79(C).
    8. Kapeller, Rudolf & Cohen, Jed J. & Kollmann, Andrea & Reichl, Johannes, 2023. "Incentivizing residential electricity consumers to increase demand during periods of high local solar generation," Energy Economics, Elsevier, vol. 127(PA).
    9. Gosnell, Greer & McCoy, Daire, 2023. "Market failures and willingness to accept smart meters: Experimental evidence from the UK," Journal of Environmental Economics and Management, Elsevier, vol. 118(C).
    10. Megan R. Bailey & David P. Brown & Blake C. Shaffer & Frank A. Wolak, 2023. "Show Me the Money! Incentives and Nudges to Shift Electric Vehicle Charge Timing," NBER Working Papers 31630, National Bureau of Economic Research, Inc.
    11. Satre-Meloy, Aven & Diakonova, Marina & Grünewald, Philipp, 2020. "Cluster analysis and prediction of residential peak demand profiles using occupant activity data," Applied Energy, Elsevier, vol. 260(C).
    12. Bailey, Megan & Brown, David P. & Myers, Erica & Shaffer, Blake & Wolak, Frank A., 2024. "Electric Vehicles and the Energy Transition: Unintended Consequences of a Common Retail Rate Design," Working Papers 2024-4, University of Alberta, Department of Economics.
    13. Harding, Matthew & Lamarche, Carlos, 2019. "A panel quantile approach to attrition bias in Big Data: Evidence from a randomized experiment," Journal of Econometrics, Elsevier, vol. 211(1), pages 61-82.
    14. Garnache, Cloé & Hernaes, Øystein & Imenes, Anders Gravir, 2022. "Which Households Respond to Electricity Peak Pricing amid High Levels of Electrification?," IZA Discussion Papers 15194, Institute of Labor Economics (IZA).
    15. Hofmann, Matthias & Lindberg, Karen Byskov, 2024. "Evidence of households' demand flexibility in response to variable hourly electricity prices – Results from a comprehensive field experiment in Norway," Energy Policy, Elsevier, vol. 184(C).
    16. Wong, Pui Ting & Rau, Henrike, 2023. "Time of Use tariffs, childcare and everyday temporalities in the US and China: Evidence from time-use and sequence-network analysis," Energy Policy, Elsevier, vol. 172(C).
    17. Hirth, Lion & Khanna, Tarun & Ruhnau, Oliver, 2023. "How aggregate electricity demand responds to hourly wholesale price fluctuations," EconStor Preprints 272048, ZBW - Leibniz Information Centre for Economics.
    18. Muttaqee, Mahmood & Stelmach, Greg & Zanocco, Chad & Flora, June & Rajagopal, Ram & Boudet, Hilary S., 2024. "Time of use pricing and likelihood of shifting energy activities, strategies, and timing," Energy Policy, Elsevier, vol. 187(C).
    19. John List & Ioannis Pragidis & Michael Price, 2024. "Toward an Understanding of the Economics of Prosumers: Evidence from a Natural Field Experiment in Energy," Natural Field Experiments 00791, The Field Experiments Website.

    More about this item

    Keywords

    electricity; dynamic prices; time-of-use rate; demand response; peak load; automation;
    All these keywords.

    JEL classification:

    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles

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