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(1) See Bresnahan (1989) on empirical models of oligopolistic markets and Hendricks and Porter (forthcoming) and Athey and Haile (forthcoming) for reviews of the recent empirical literature on auctions. Klemperer (2003) and Einav (2004) clarify the connections between oligopoly models and auction models.

(2) Several other papers use "outside" estimates of marginal cost to measure price-cost margins and test strategic oligopoly models. For example, Genesove and Mullin (1998) analyze the sugar industry in the early 20th century. Hendricks, Porter, and Boudreau (1987) investigate the ex post returns of bidders in Outer Continental Shelf oil and gas lease auctions using drilling and production data from auctioned tracts. Bajari and Hortacsu (2005) use experimental data with assigned bidder valuations to gauge the performance of structural econometric models of auctions.

(3) Ausubel and Cramton (2002), Wang and Zender (2002), Hortacsu (2002b), and Viswanathan, Wang, and Witelski (2002) develop this theoretical framework further. See Cramton (2004) for a particularly accessible account of these models.

(4) Wolak (2000) and Bushnell, Mansur, and Saravia (forthcoming) also point out that forward contract positions are important determinants of bidding behavior.

(5) The SFE model has been influential in the modelling and analysis of electricity markets, as in Green and Newbery (1992), Green (1996), Rudkevich (1999), Baldick, Grant, and Kahn (2004), and Crawford, Crespo, and Tauchen (forthcoming).

(6) Sweeting (2007), in contrast, makes the assumption that the generators have 80% contract cover, and tests robustness to alternative assumptions.

(7) Wolak (2003a) demonstrates how one can obtain contract quantities under the assumption of profit maximization. Because our goal is to test profit maximization, the method proposed by Wolak is not feasible in our context.

(8) See Wilson (2002) and Joskow (2000) for more detailed discussions of transactions in restructured electricity markets. Further details on the ERCOT market are in Baldick and Niu (2005).

(9) Examples of both the bidding and operations interfaces can be found in a supplementary materials Section at econweb.tamu.edu/puller/HPsupplementary.htm. We thank the real time trading desk at Bryan Texas Utilities and Reliant/TexasGenco for allowing us to visit and observe their trading desk and allowing us to interview their traders. A variety of other market participants provided very helpful insights into trading in the balancing market.

(10) To compare this with other intervals, the average MW transacted across all intervals varies only slightly over the day with an average volume of 890. Note that because firms can submit only one bid function for each hour, optimal bids must cover a wide range of possible demand quantities. Demand varies by an average of 617 MW during each 6:00-7:00 pm bidding hour.

(11) In our application, we assume that demand is perfectly inelastic. However, our model generalizes to the ease where D'(p) [less than or equal to] 0.

(12) Although the analysis of the two-stage game with endogenous contract quantity choices adds a further and interesting strategic dimension, we found that traders who negotiate forward contracts and traders who bid in the balancing (real-time) market are distinct, and often belong to different trading desks. Thus, our model can be thought of as applying to the real-time trader.