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Price and Quantity Discovery without Commitment

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  • Cantillon, Estelle
  • Bergheimer, Stefan
  • Reguant, Mar

Abstract

Wholesale electricity markets solve a complex allocation problem: electricity is not storable, demand is uncertain, and production involves dynamic cost considerations and indivisibilities. The New Zealand wholesale electricity market attempts to solve this complex allocation problem by using an indicative price and quantity discovery mechanism that ends at dispatch. Can such a market mechanism without commitment provide useful information? We document that indicative prices and quantities are increasingly informative of the final prices and quantities and that bid revisions are consistent with information-based updating. We argue that the reason why the predispatch market is informative despite the lack of commitment is that it generates private benefits in terms of improved intertemporal optimization of production plans.

Suggested Citation

  • Cantillon, Estelle & Bergheimer, Stefan & Reguant, Mar, 2023. "Price and Quantity Discovery without Commitment," CEPR Discussion Papers 18189, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:18189
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    1. David P. Brown & Andrew Eckert, 2022. "Pricing Patterns in Wholesale Electricity Markets: Unilateral Market Power or Coordinated Behavior?," Journal of Industrial Economics, Wiley Blackwell, vol. 70(1), pages 168-216, March.
    2. Frank A. Wolak, 2007. "Quantifying the supply-side benefits from forward contracting in wholesale electricity markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(7), pages 1179-1209.
    3. Lawrence M. Ausubel & Peter Cramton & Marek Pycia & Marzena Rostek & Marek Weretka, 2014. "Demand Reduction and Inefficiency in Multi-Unit Auctions," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 81(4), pages 1366-1400.
    4. Barclay, Michael J. & Hendershott, Terrence, 2008. "A comparison of trading and non-trading mechanisms for price discovery," Journal of Empirical Finance, Elsevier, vol. 15(5), pages 839-849, December.
    5. Bolle, Friedel, 1992. "Supply function equilibria and the danger of tacit collusion : The case of spot markets for electricity," Energy Economics, Elsevier, vol. 14(2), pages 94-102, April.
    6. Nils-Henrik M. von der Fehr, 2013. "Transparency in Electricity Markets," Economics of Energy & Environmental Policy, International Association for Energy Economics, vol. 0(Number 2).
    7. Hong, Jieying & Pouget, Sébastien, 2021. "Liquidity Formation and Preopening Periods in Financial Markets," TSE Working Papers 21-1283, Toulouse School of Economics (TSE).
    8. Bruno Biais & Christophe Bisière & Sébastien Pouget, 2014. "Equilibrium Discovery and Preopening Mechanisms in an Experimental Market," Management Science, INFORMS, vol. 60(3), pages 753-769, March.
    9. Jieying Hong & Sébastien Pouget, 2021. "Liquidity Formation and Preopening Periods in Financial Markets," Economica, London School of Economics and Political Science, vol. 88(351), pages 697-723, July.
    10. Jorge Balat & Juan Esteban Carranza & Juan David Martin & Alvaro Riascos, 2022. "The effects of changes in the regulation of the Colombian wholesale electricity market in a structural model of complex auctions," Borradores de Economia 1211, Banco de la Republica de Colombia.
    11. Steve Cicala, 2022. "Imperfect Markets versus Imperfect Regulation in US Electricity Generation," American Economic Review, American Economic Association, vol. 112(2), pages 409-441, February.
    12. Lawrence M. Ausubel & Peter Cramton, 2004. "Auctioning Many Divisible Goods," Journal of the European Economic Association, MIT Press, vol. 2(2-3), pages 480-493, 04/05.
    13. Robert Wilson, 2002. "Architecture of Power Markets," Econometrica, Econometric Society, vol. 70(4), pages 1299-1340, July.
    14. Mar Reguant, 2014. "Complementary Bidding Mechanisms and Startup Costs in Electricity Markets," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 81(4), pages 1708-1742.
    15. Charles Cao & Eric Ghysels & Frank Hatheway, 2000. "Price Discovery without Trading: Evidence from the Nasdaq Preopening," Journal of Finance, American Finance Association, vol. 55(3), pages 1339-1365, June.
    16. Milgrom, Paul R & Weber, Robert J, 1982. "A Theory of Auctions and Competitive Bidding," Econometrica, Econometric Society, vol. 50(5), pages 1089-1122, September.
    17. David P. Brown & Andrew Eckert & James Lin, 2018. "Information and transparency in wholesale electricity markets: evidence from Alberta," Journal of Regulatory Economics, Springer, vol. 54(3), pages 292-330, December.
    18. Lawrence M. Ausubel, 2004. "An Efficient Ascending-Bid Auction for Multiple Objects," American Economic Review, American Economic Association, vol. 94(5), pages 1452-1475, December.
    19. Nisan, Noam & Segal, Ilya, 2006. "The communication requirements of efficient allocations and supporting prices," Journal of Economic Theory, Elsevier, vol. 129(1), pages 192-224, July.
    20. Bruno Biais & Pierre Hillion & Chester Spatt, 1999. "Price Discovery and Learning during the Preopening Period in the Paris Bourse," Journal of Political Economy, University of Chicago Press, vol. 107(6), pages 1218-1248, December.
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    More about this item

    Keywords

    Intertemporal optimization;

    JEL classification:

    • D47 - Microeconomics - - Market Structure, Pricing, and Design - - - Market Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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