Simple-Offer vs. Complex-Offer Auctions in Deregulated Electricity Markets

Rimvydas Baltaduonis

No 2007-14, Working papers from University of Connecticut, Department of Economics

Abstract: In my recent experimental research of wholesale electricity auctions, I discovered that the complex structure of the offers leaves a lot of room for strategic behavior, which consequently leads to anti- competitive and inefficient outcomes in the market. A specific feature of these complex-offer auctions is that the sellers submit not only the quantities and the minimum prices at which they are willing to sell, but also the start-up fees that are designed to reimburse the fixed start-up costs of the generation plants. In this paper, using the experimental method I compare the performance of two complex-offer auctions (COAs) against the performance of a simple-offer auction (SOA), in which the sellers have to recover all their generation costs --- fixed and variable ---through a uniform market-clearing price. I find that the SOA significantly reduces consumer prices and lowers price volatility. It mitigates anti-competitive effects that are present in the COAs and achieves allocative efficiency more quickly.

Keywords: strategic behavior; sealed-bid auction; complex offer auction; electricity; efficiency (search for similar items in EconPapers)
JEL-codes: C72 D4 D61 L94 (search for similar items in EconPapers)
Pages: 44 pages
Date: 2007-04
New Economics Papers: this item is included in nep-com, nep-ene, nep-exp, nep-gth and nep-ind
Note: The author would like to thank the National Science Foundation under grant SES 0648937, and the International Foundation for Research in Experimental Economics for financial support. The author is grateful to the Engineering and Economics faculty and students at the University of Connecticut working on the electricity project and the faculty and students at the Interdisciplinary Center for Economic Science at George Mason University for their helpful comments. The author would like to thank in particular Vicki Knoblauch and Bart Wilson for their valuable suggestions, Jeffrey Kirchner for writing the software for the experiments, Feng Zhao and William Blankson for explaining the complex-offer optimization algorithms. All mistakes are the responsibility of the author. The data are available upon request.
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