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Just Starting Out: Learning and Equilibrium in a New Market

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  • Ulrich Doraszelski
  • Gregory Lewis
  • Ariel Pakes

Abstract

We document the evolution of the newly created market for frequency response within the UK electricity system over a six-year period. Firms competed in price while facing considerable initial uncertainty about market demand and rival behavior. We show that over time prices stabilized, converging to a rest point that is consistent with equilibrium play, and then adjusted to subsequent changes in the market quite quickly. We draw on models of fictitious play and adaptive learning to analyze how this convergence occurs and show that these models predict behavior better than Nash equilibrium prior to convergence.

Suggested Citation

  • Ulrich Doraszelski & Gregory Lewis & Ariel Pakes, 2016. "Just Starting Out: Learning and Equilibrium in a New Market," NBER Working Papers 21996, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:21996
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    1. Dan Bernhardt & Bart Taub, 2015. "Learning about common and private values in oligopoly," RAND Journal of Economics, RAND Corporation, vol. 46(1), pages 66-85, March.
    2. Rothschild, Michael, 1974. "A two-armed bandit theory of market pricing," Journal of Economic Theory, Elsevier, vol. 9(2), pages 185-202, October.
    3. Sergiu Hart & Andreu Mas-Colell, 2013. "A Simple Adaptive Procedure Leading To Correlated Equilibrium," World Scientific Book Chapters, in: Simple Adaptive Strategies From Regret-Matching to Uncoupled Dynamics, chapter 2, pages 17-46, World Scientific Publishing Co. Pte. Ltd..
    4. Ernst Fehr & Jean-Robert Tyran, 2008. "Limited Rationality and Strategic Interaction: The Impact of the Strategic Environment on Nominal Inertia," Econometrica, Econometric Society, vol. 76(2), pages 353-394, March.
    5. Borgers, Tilman & Sarin, Rajiv, 1997. "Learning Through Reinforcement and Replicator Dynamics," Journal of Economic Theory, Elsevier, vol. 77(1), pages 1-14, November.
    6. Mirman, Leonard J & Samuelson, Larry & Urbano, Amparo, 1993. "Duopoly Signal Jamming," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 3(1), pages 129-149, January.
    7. Colin Camerer & Teck-Hua Ho, 1999. "Experience-weighted Attraction Learning in Normal Form Games," Econometrica, Econometric Society, vol. 67(4), pages 827-874, July.
    8. Julian Kozlowski & Laura Veldkamp & Venky Venkateswaran, 2015. "The Tail that Wags the Economy: Belief-Driven Business Cycles and Persistent Stagnation," Working Papers 15-10, New York University, Leonard N. Stern School of Business, Department of Economics.
    9. Lee, Robin S. & Pakes, Ariel, 2009. "Multiple equilibria and selection by learning in an applied setting," Economics Letters, Elsevier, vol. 104(1), pages 13-16, July.
    10. Joskow, Paul L & Schmalensee, Richard & Bailey, Elizabeth M, 1998. "The Market for Sulfur Dioxide Emissions," American Economic Review, American Economic Association, vol. 88(4), pages 669-685, September.
    11. Herbert A. Simon, 1955. "A Behavioral Model of Rational Choice," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 69(1), pages 99-118.
    12. Julian Kozlowski & Laura Veldkamp & Venky Venkateswaran, 2020. "The Tail That Wags the Economy: Beliefs and Persistent Stagnation," Journal of Political Economy, University of Chicago Press, vol. 128(8), pages 2839-2879.
    13. Godfrey Keller & Sven Rady & Martin Cripps, 2005. "Strategic Experimentation with Exponential Bandits," Econometrica, Econometric Society, vol. 73(1), pages 39-68, January.
    14. Timothy C. Salmon, 2001. "An Evaluation of Econometric Models of Adaptive Learning," Econometrica, Econometric Society, vol. 69(6), pages 1597-1628, November.
    15. Michael H. Riordan, 1985. "Imperfect Information and Dynamic Conjectural Variations," RAND Journal of Economics, The RAND Corporation, vol. 16(1), pages 41-50, Spring.
    16. Akerlof, George A & Yellen, Janet L, 1985. "Can Small Deviations from Rationality Make Significant Differences to Economic Equilibria?," American Economic Review, American Economic Association, vol. 75(4), pages 708-720, September.
    17. Daniel A. Ackerberg, 2003. "Advertising, learning, and consumer choice in experience good markets: an empirical examination," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(3), pages 1007-1040, August.
    18. Andrew Sweeting, 2007. "Market Power In The England And Wales Wholesale Electricity Market 1995-2000," Economic Journal, Royal Economic Society, vol. 117(520), pages 654-685, April.
    19. C. Lanier Benkard, 2000. "Learning and Forgetting: The Dynamics of Aircraft Production," American Economic Review, American Economic Association, vol. 90(4), pages 1034-1054, September.
    20. Sims, Christopher A., 2003. "Implications of rational inattention," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 665-690, April.
    21. Timothy G. Conley & Christopher R. Udry, 2010. "Learning about a New Technology: Pineapple in Ghana," American Economic Review, American Economic Association, vol. 100(1), pages 35-69, March.
    22. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    23. Fudenberg Drew & Kreps David M., 1993. "Learning Mixed Equilibria," Games and Economic Behavior, Elsevier, vol. 5(3), pages 320-367, July.
    24. Erev, Ido & Roth, Alvin E, 1998. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria," American Economic Review, American Economic Association, vol. 88(4), pages 848-881, September.
    25. Chaim Fershtman & Ariel Pakes, 2012. "Dynamic Games with Asymmetric Information: A Framework for Empirical Work," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 127(4), pages 1611-1661.
    26. Pakes, Ariel & Pollard, David, 1989. "Simulation and the Asymptotics of Optimization Estimators," Econometrica, Econometric Society, vol. 57(5), pages 1027-1057, September.
    27. Sargent, Thomas J., 1993. "Bounded Rationality in Macroeconomics: The Arne Ryde Memorial Lectures," OUP Catalogue, Oxford University Press, number 9780198288695.
    28. Easley, David & Kiefer, Nicholas M, 1988. "Controlling a Stochastic Process with Unknown Parameters," Econometrica, Econometric Society, vol. 56(5), pages 1045-1064, September.
    29. Tülin Erdem & Michael P. Keane, 1996. "Decision-Making Under Uncertainty: Capturing Dynamic Brand Choice Processes in Turbulent Consumer Goods Markets," Marketing Science, INFORMS, vol. 15(1), pages 1-20.
    30. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
    31. Severin Borenstein & James B. Bushnell & Frank A. Wolak, 2002. "Measuring Market Inefficiencies in California's Restructured Wholesale Electricity Market," American Economic Review, American Economic Association, vol. 92(5), pages 1376-1405, December.
    32. Camerer, Colin F. & Ho, Teck-Hua & Chong, Juin-Kuan, 2002. "Sophisticated Experience-Weighted Attraction Learning and Strategic Teaching in Repeated Games," Journal of Economic Theory, Elsevier, vol. 104(1), pages 137-188, May.
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    More about this item

    JEL classification:

    • D02 - Microeconomics - - General - - - Institutions: Design, Formation, Operations, and Impact
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L10 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - General
    • L51 - Industrial Organization - - Regulation and Industrial Policy - - - Economics of Regulation

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