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Strategic Demand Response to Dynamic Pricing: A Lab Experiment for the Electricity Market




Despite the efforts of restructuring power markets over the last decades, the lack of demand response in the retail electricity markets remains a significant concern. Possible demand response would help to reduce prices and volatility by better matching supply and demand through improved price signals. In this paper we develop a laboratory tool to experimentally investigate the demand response in the electricity market. The baseline treatment constitutes a two-period ‘wait-or-buy’ game with an exogenous first period, an automated supplier, and twenty subject buyers. While the seller offers a fixed number of a product in the market, consumers decide on purchasing the product immediately or waiting until the next period, taking (i) price uncertainty and (ii) inventory risk into account. This treatment captures demand response in the retail market with scarce products. We design an additional treatment by removing the inventory constraint and introducing a devaluation rule, where consumers only bear the price risk – thus mimicking the demand response in the electricity market. We find that in both retail and electricity market treatments consumers play on average the equilibrium predictions and buy strategically. However, there are systematic deviations from rationality in both settings, i.e., consumers buy too soon or wait too long.

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  • Atasoy, Ayse Tugba & Harmsen-van Hout, Marjolein & Madlener, Reinhard, 2018. "Strategic Demand Response to Dynamic Pricing: A Lab Experiment for the Electricity Market," FCN Working Papers 5/2018, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN), revised 22 Jan 2020.
  • Handle: RePEc:ris:fcnwpa:2018_005

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    1. Armin Falk & Anke Becker & Thomas Dohmen & David Huffman & Uwe Sunde, 2016. "The Preference Survey Module: A Validated Instrument for Measuring Risk, Time, and Social Preferences," Working Papers 2016-003, Human Capital and Economic Opportunity Working Group.
    2. Chloé Coq & Henrik Orzen & Sebastian Schwenen, 2017. "Pricing and capacity provision in electricity markets: an experimental study," Journal of Regulatory Economics, Springer, vol. 51(2), pages 123-158, April.
    3. Stanley S. Reynolds, 2000. "Durable-Goods Monopoly: Laboratory Market and Bargaining Experiments," RAND Journal of Economics, The RAND Corporation, vol. 31(2), pages 375-394, Summer.
    4. Schneider, Ian & Sunstein, Cass R., 2017. "Behavioral considerations for effective time-varying electricity prices," Behavioural Public Policy, Cambridge University Press, vol. 1(2), pages 219-251, November.
    5. Heberlein, Thomas A. & Warriner, G. Keith, 1983. "The influence of price and attitude on shifting residential electricity consumption from on- to off-peak periods," Journal of Economic Psychology, Elsevier, vol. 4(1-2), pages 107-130, October.
    6. Faruqui, Ahmad & George, Stephen S., 2002. "The Value of Dynamic Pricing in Mass Markets," The Electricity Journal, Elsevier, vol. 15(6), pages 45-55, July.
    7. Ahmad Faruqui, Sanem Sergici, and Lamine Akaba, 2014. "The Impact of Dynamic Pricing on Residential and Small Commercial and Industrial Usage: New Experimental Evidence from Connecticut," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    8. Timothy N. Cason & Tridib Sharma, 2001. "Durable Goods, Coasian Dynamics, and Uncertainty: Theory and Experiments," Journal of Political Economy, University of Chicago Press, vol. 109(6), pages 1311-1354, December.
    9. Werner Güth & Sabine Kröger & Hans-Theo Normann, 2004. "Durable-Goods Monopoly with Privately Known Impatience: A Theoretical and Experimental Study," Economic Inquiry, Western Economic Association International, vol. 42(3), pages 413-424, July.
    10. Chavas, Jean-Paul & Holt, Matthew T, 1996. "Economic Behavior under Uncertainty: A Joint Analysis of Risk Preferences and Technology," The Review of Economics and Statistics, MIT Press, vol. 78(2), pages 329-335, May.
    11. Ahmad Faruqui & Sanem Sergici, 2010. "Household response to dynamic pricing of electricity: a survey of 15 experiments," Journal of Regulatory Economics, Springer, vol. 38(2), pages 193-225, October.
    12. Vincent Mak & Amnon Rapoport & Eyran J. Gisches & Jiaojie Han, 2014. "Purchasing Scarce Products Under Dynamic Pricing: An Experimental Investigation," Manufacturing & Service Operations Management, INFORMS, vol. 16(3), pages 425-438, July.
    13. Urs Fischbacher, 2007. "z-Tree: Zurich toolbox for ready-made economic experiments," Experimental Economics, Springer;Economic Science Association, vol. 10(2), pages 171-178, June.
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    Cited by:

    1. Wolff, Stefanie & Madlener, Reinhard, 2019. "Charged up? Preferences for Electric Vehicle Charging and Implications for Charging Infrastructure Planning," FCN Working Papers 3/2019, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    2. Specht, Jan Martin & Madlener, Reinhard, 2018. "Business Models for Energy Suppliers Aggregating Flexible Distributed Assets and Policy Issues Raised," FCN Working Papers 7/2018, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    3. Liu, Xueying & Madlener, Reinhard, 2019. "The Sky is the Limit: Assessing Aircraft Market Diffusion with Agent-Based Modeling," FCN Working Papers 16/2019, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    4. Liu, Xueying & Madlener, Reinhard, 2019. "Get Ready for Take-Off: A Two-Stage Model of Aircraft Market Diffusion," FCN Working Papers 15/2019, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).

    More about this item


    Demand Response; Electricity; Dynamic Pricing; Strategic Behavior;

    JEL classification:

    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • M11 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Production Management
    • Q31 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Demand and Supply; Prices

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