License prices for financially constrained firms

It is often alleged that high auction prices inhibit service deployment. We investigate this claim under the extreme case of financially constrained bidders. If demand is just slightly elastic, auctions maximize consumer surplus if consumer surplus is a convex function of quantity (a common assumption), or if consumer surplus is concave and the proportion of expenditure spent on deployment is greater than one over the elasticity of demand. The latter condition appears to be true for most of the large telecom auctions in the US and Europe. Thus, even if high auction prices inhibit service deployment, auctions appear to be optimal from the consumers’ point of view

Sequential auctions for objects with common and private values

Sequential auctions are an important mechanism for buying/selling multiple objects. Existing work has studied sequential auctions for objects that are exclusively either common value or private value. However, in many real-world cases an object has both features. Also, in such cases, the common value component (which is the same for all bidders) depends on how much each bidder values the object. Moreover, an individual bidder generally does not know how much the other bidders value it. On the other hand, a bidder's private value is independent of the others' private values. Given this, we study settings that have both common and private value elements by treating each bidder's information about the common value as uncertain. We first determine equilibrium bidding strategies for each auction in a sequence using English auction rules. On the basis of this equilibrium, we analyse the efficiency of auctions. Specifically, we show that the inefficiency that arises as a result of uncertainty about the common values can be reduced if the auctioneer makes its information about the common value known to all bidders. Moreover, our analysis also shows that the inefficiency of auctions in an agent-based setting is higher than that in an all-human setting