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Empowering Consumers Through Data and Smart Technology: Experimental Evidence on the Consequences of Time‐of‐Use Electricity Pricing Policies

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  • Matthew Harding
  • Carlos Lamarche

Abstract

This paper investigates the extent to which technology used to automate household responses to time‐of‐use pricing for electricity leads to higher energy savings than simply providing households with information on current prices and quantities. Using a large randomized field trial, we find that informed households with “smart” thermostats achieve impressive reductions in consumption during on‐peak periods of up to 48 percent, but also engage in substantial load shifting to off‐peak hours. We also document the extent to which household responses to time‐of‐use pricing are heterogeneous and vary significantly by demographics, weather, and across the usage distribution.

Suggested Citation

  • Matthew Harding & Carlos Lamarche, 2016. "Empowering Consumers Through Data and Smart Technology: Experimental Evidence on the Consequences of Time‐of‐Use Electricity Pricing Policies," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 35(4), pages 906-931, September.
    • Handle: RePEc:wly:jpamgt:v:35:y:2016:i:4:p:906-931
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    File URL: http://hdl.handle.net/10.1002/pam.21928
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    Citations

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    Cited by:

    1. Chakraborty, Chiranjit & Joseph, Andreas, 2017. "Machine learning at central banks," Bank of England working papers 674, Bank of England.
    2. Jacobsen, Grant D. & Stewart, James I., 2022. "How do consumers respond to price complexity? Experimental evidence from the power sector," Journal of Environmental Economics and Management, Elsevier, vol. 116(C).
    3. 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.
    4. Löschel, Andreas & Price, Michael Keith & Razzolini, Laura & Werthschulte, Madeline, 2022. "COVID-19 and the formation of energy conservation routines: Disentangling the relative importance of attention and income shocks," ZEW Discussion Papers 22-068, ZEW - Leibniz Centre for European Economic Research.
    5. Daniel J. Mallinson & Saahir Shafi, 2022. "Smart home technology: Challenges and opportunities for collaborative governance and policy research," Review of Policy Research, Policy Studies Organization, vol. 39(3), pages 330-352, May.
    6. Manuel Frondel and Gerhard Kussel, 2019. "Switching on Electricity Demand Response: Evidence for German Households," The Energy Journal, International Association for Energy Economics, vol. 0(Number 5).
    7. Federico A. Bugni & Joel L. Horowitz, 2021. "Permutation tests for equality of distributions of functional data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(7), pages 861-877, November.
    8. Lomas, K.J. & Oliveira, S. & Warren, P. & Haines, V.J. & Chatterton, T. & Beizaee, A. & Prestwood, E. & Gething, B., 2018. "Do domestic heating controls save energy? A review of the evidence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 52-75.
    9. 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.
    10. 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.
    11. 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.
    12. Heather Hodges & Colin Kuehl & Sarah E. Anderson & Phillip J. Ehret & Cameron Brick, 2020. "How Managers Can Reduce Household Water Use Through Communication: A Field Experiment," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 39(4), pages 1076-1099, September.
    13. Bryan K. Bollinger & Wesley R. Hartmann, 2020. "Information vs. Automation and Implications for Dynamic Pricing," Management Science, INFORMS, vol. 66(1), pages 290-314, January.
    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. Schäuble, Dominik & Marian, Adela & Cremonese, Lorenzo, 2020. "Conditions for a cost-effective application of smart thermostat systems in residential buildings," Applied Energy, Elsevier, vol. 262(C).
    16. 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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