common value auctions the same value for everyone, but different bidders have different information...
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Common value auctions
The same value for everyone, but different bidders have different
information about the underlying value
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Auction a jar full of coins (asking for an estimation)
• average bid will be significantly less than the value of the coins (bidders are risk averse)
• winning bid exceeds the value of the jar
Bazerman & Samuelson, 1983, 48 auctions• True value $8• Estimated (mean) $5.13• Bias in estimation + risk aversion should work
against over bidding
• Yet mean winning $10.01
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THE WINNER’S CURSE
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• Question first raised by Capen, Clapp and Campbell 1971.
• This is an example of a problem that comes from a field observation before becoming theory.
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• Winner's curse cannot occur among rational bidders (Cox and Isaac 1984).
• Challenge to assumption of rationality.
• But acting rationaly is difficult. Need to distinguish between:
• expected value of the object, conditioned on prior information
• expected value of the object, conditioned on winning the auction
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• Example. You have to advise the takover of firm T.
• T knows the true value, you don't: Assymetry of information.
Optimal to bid ? Cero patatero
Extreme case of winner's curse.
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• Experimental evidence (Bazerman & Samuelson 1985): Only 9% bid zero. Majority in [$50-$75].
• Would learning solve the anomaly? (Weiner, Bazerman & Carroll 1987).
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• Each subject (MBA) repeated it 20 times with feedback about true value and whether their bid was accepted and profit. Of 69 subjects 5 learned to bid 1 or less by the end of the 20 rounds. Learning seem not to be easy or fast.
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• Shell’s boss calls me about a bid
• Calls me again to tell me that the number of bidders has increased
• Should I increase or lower my previous bid?
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• need to bid more aggressively to win
• if you win more likely that you have overestimated.
• Solving it not trivial. Do people get it right?
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• Series of experiments by Kagel, Levin et al. True value x* varies from trial to trial but always between xl and xh.
• Prior is given to each one by drawing xi from uniform x*±∆.
• Increase in N -> more losses.
• Teatments: a) change of type of auction (first, second), N and ∆. Compare results with RNNE.
• This done also with construction firm managers (last price) Rules of thumb.
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• Field data. Oil tracks, Corporate takeovers, Publishing auctions. At least prevalence of mild form of winner's curse: unfulfilled expectations.
• Why is this important? It is part of a general problem of after decision blues. Bidders are under a cognitive illusion that makes them incur in systematic errors.
• What strategy to follow once you have discovered the winner’s curse? Reduce your bids and sell short others’ shares?
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• Why people succumb to it?
• “The value of victory”:
Humans assign significant future value to victories over humans but not over computer opponents, even though such victories may incur immediate losses