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Effectiveness of Real Time Information Provision with Time of Use Pricing

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  • Pon, Shirley

    (Department of Agricultural and Resource Economics - University of Maryland)

Abstract

Real time information feedback combined with various pricing schemes has been found to reduce residential energy consumption more than information and pricing policies alone. I examine the effect of information provision with bi-monthly, monthly, and real time pricing with in-home displays with a time-of-use pricing scheme on consumption over each month of the Irish Consumer Behavior Trial. I find that time-of-use pricing with real time pricing information reduce electricity usage up to 8.7 percent during peak times at the start of the trial but the effect decays over the first three months and after three months the trial group is indistinguishable from the control group. I do not find statistically significant improvements in energy savings when comparing monthly and bi-monthly billing treatments. These findings suggest that increasing billing reports to the monthly level or a web application providing real time information may be more cost effective than providing in-home displays.

Suggested Citation

  • Pon, Shirley, 2015. "Effectiveness of Real Time Information Provision with Time of Use Pricing," FCN Working Papers 8/2015, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN), revised Oct 2015.
    • Handle: RePEc:ris:fcnwpa:2015_008
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    1. Newsham, Guy R. & Bowker, Brent G., 2010. "The effect of utility time-varying pricing and load control strategies on residential summer peak electricity use: A review," Energy Policy, Elsevier, vol. 38(7), pages 3289-3296, July.
    2. Victor Stango & Jonathan Zinman, 2014. "Limited and Varying Consumer Attention: Evidence from Shocks to the Salience of Bank Overdraft Fees," The Review of Financial Studies, Society for Financial Studies, vol. 27(4), pages 990-1030.
    3. Joachain, Hélène & Klopfert, Frédéric, 2014. "Smarter than metering? Coupling smart meters and complementary currencies to reinforce the motivation of households for energy savings," Ecological Economics, Elsevier, vol. 105(C), pages 89-96.
    4. Iacus, Stefano & King, Gary & Porro, Giuseppe, 2009. "cem: Software for Coarsened Exact Matching," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 30(i09).
    5. Torriti, Jacopo, 2012. "Price-based demand side management: Assessing the impacts of time-of-use tariffs on residential electricity demand and peak shifting in Northern Italy," Energy, Elsevier, vol. 44(1), pages 576-583.
    6. Sexton, Richard J & Johnson, Nancy Brown & Konakayama, Akira, 1987. "Consumer Response to Continuous-Display Electricity-Use Monitors in a Time-of-Use Pricing Experiment," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 14(1), pages 55-62, June.
    7. Katrina Jessoe & David Rapson, 2014. "Knowledge Is (Less) Power: Experimental Evidence from Residential Energy Use," American Economic Review, American Economic Association, vol. 104(4), pages 1417-1438, April.
    8. Hargreaves, Tom & Nye, Michael & Burgess, Jacquelin, 2013. "Keeping energy visible? Exploring how householders interact with feedback from smart energy monitors in the longer term," Energy Policy, Elsevier, vol. 52(C), pages 126-134.
    9. Matthew Blackwell & Stefano Iacus & Gary King & Giuseppe Porro, 2009. "cem: Coarsened exact matching in Stata," Stata Journal, StataCorp LP, vol. 9(4), pages 524-546, December.
    10. Ivanov, Chris & Getachew, Lullit & Fenrick, Steve A. & Vittetoe, Bethany, 2013. "Enabling technologies and energy savings: The case of EnergyWise Smart Meter Pilot of Connexus Energy," Utilities Policy, Elsevier, vol. 26(C), pages 76-84.
    11. Eugenio J. Miravete, 2003. "Choosing the Wrong Calling Plan? Ignorance and Learning," American Economic Review, American Economic Association, vol. 93(1), pages 297-310, March.
    12. Sridhar Narayanan & Pradeep Chintagunta & Eugenio Miravete, 2007. "The role of self selection, usage uncertainty and learning in the demand for local telephone service," Quantitative Marketing and Economics (QME), Springer, vol. 5(1), pages 1-34, March.
    13. Sebastien Houde, Annika Todd, Anant Sudarshan, June A. Flora , and K. Carrie Armel, 2013. "Real-time Feedback and Electricity Consumption: A Field Experiment Assessing the Potential for Savings and Persistence," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    14. Richins, Marsha L. & Bloch, Peter H., 1991. "Post-purchase product satisfaction: Incorporating the effects of involvement and time," Journal of Business Research, Elsevier, vol. 23(2), pages 145-158, September.
    15. Richins, Marsha L & Bloch, Peter H, 1986. "After the New Wears Off: The Temporal Context of Product Involvement," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 13(2), pages 280-285, September.
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    More about this item

    Keywords

    time-of-use pricing; information provision; feedback; energy efficiency behavior;
    All these keywords.

    JEL classification:

    • D04 - Microeconomics - - General - - - Microeconomic Policy: Formulation; Implementation; Evaluation
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • Q49 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Other

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