1. A method for determining an auction format for a market, said method comprising the steps of: selecting, performed by a computer system, characteristics of said market based at least in part on stored historical bids data that includes data for historical auctions performed in the past for a plurality of bidders, wherein said historical bids data is stored on computer readable medium that is accessed by said computer system; selecting, performed by said computer system, a relevant bidding model that specifies past bidding behavior as a function of information held privately by a bidder, that is determined based at least in part on said historical auctions data, and said characteristics of said market based on segments of said historical auctions related to a specified item; selecting, performed by said computer system, at least a first estimated structure of said market, which describes at least a first factor that affects how bidders behave, and a second estimated structure of said market, which describes a second factor that affects how bidders behave, at least in part by inverting said relevant bidding model; predicting, performed by said computer system, a first bidding behavior utilizing said first estimated structure of said market, said characteristics of said market and said relevant bidding model; predicting, performed by said computer system, a first outcome of said market based on said first bidding behavior; predicting, performed by said computer system, at least a second bidding behavior utilizing at least said second estimated structure of said market, said characteristics of said market and said relevant bidding model; predicting, performed by said computer system, a second outcome of said market based on at least said second bidding behavior prediction; and determining, performed by said computer system, said auction format for said market by evaluating said first outcome of said market and at least said second outcome of said market.
1. A method for determining an auction format for a market, said method comprising the steps of: selecting, performed by a computer system, characteristics of said market based at least in part on stored historical bids data that includes data for historical auctions performed in the past for a plurality of bidders, wherein said historical bids data is stored on computer readable medium that is accessed by said computer system; selecting, performed by said computer system, a relevant bidding model that specifies past bidding behavior as a function of information held privately by a bidder, that is determined based at least in part on said historical auctions data, and said characteristics of said market based on segments of said historical auctions related to a specified item; selecting, performed by said computer system, at least a first estimated structure of said market, which describes at least a first factor that affects how bidders behave, and a second estimated structure of said market, which describes a second factor that affects how bidders behave, at least in part by inverting said relevant bidding model; predicting, performed by said computer system, a first bidding behavior utilizing said first estimated structure of said market, said characteristics of said market and said relevant bidding model; predicting, performed by said computer system, a first outcome of said market based on said first bidding behavior; predicting, performed by said computer system, at least a second bidding behavior utilizing at least said second estimated structure of said market, said characteristics of said market and said relevant bidding model; predicting, performed by said computer system, a second outcome of said market based on at least said second bidding behavior prediction; and determining, performed by said computer system, said auction format for said market by evaluating said first outcome of said market and at least said second outcome of said market. 6. The method as recited in claim 1 , wherein said predicting of said first outcome of said market step comprises the steps of: receiving a second user input, wherein said second user input comprises: an evaluation criterion; a candidate auction format; and a constraint; receiving said first estimated structure of said market; receiving said first bidding behavior prediction for said candidate auction format, wherein said first bidding behavior prediction further comprises a prediction under said constraint; obtaining a value of said evaluation criterion, wherein said value is based on said first estimated structure of said market, said first bidding behavior prediction, said candidate auction format, and said constraint, wherein said value comprising said first outcome of said market; and outputting said value.