Abstract
In many auction settings we find a self-interested information broker, that can potentially disambiguate the uncertainty associated with the common value of the auctioned item (e.g., the true condition of an auctioned car, the sales forecast for a company offered for sale). This paper extends prior work, that has considered mostly the information pricing question in this archetypal three-ply bidders-auctioneer-information broker model, by enabling the information broker a richer strategic behavior in the form of anonymously eliminating some of the uncertainty associated with the common value, for free. The analysis of the augmented model enables illustrating two somehow non-intuitive phenomena in such settings: (a) the information broker indeed may benefit from disclosing for free some of the information she wishes to sell, even though this seemingly reduces the uncertainty her service aims to disambiguate; and (b) the information broker may benefit from publishing the free information to the general public rather than just to the auctioneer, hence preventing the edge from the latter, even if she is the only prospective customer of the service. While the extraction of the information broker’s optimal strategy is computationally hard, we propose two heuristics that rely on the variance between the different values, as means for generating potential solutions that are highly efficient. The importance of the results is primarily in providing information brokers with a new paradigm for improving their expected profit in auction settings. The new paradigm is also demonstrated to result, in some cases, in a greater social welfare, hence can be of much interest to market designers as well.
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