Auction models are convenient abstractions of informal price-formation processes that arise in markets for assets or services. These processes involve frictions like bidder recruitment costs for sellers, participation costs for bidders, and limitations on sellers’ commitment abilities. This paper develops an auction model that captures such frictions. We derive novel insights, notably that outcomes are often inefficient, that markets sometimes unravel, and that the observability of competition may have a large effect.

We study the aggregation of dispersed information in elections in which turnout may depend on the state. State-dependent turnout may arise from the actions of a biased and informed “election organizer”. Voters are symmetric ex ante and prefer policy a in state α and policy b in state β, but the organizer prefers policy a regardless of the state. Each recruited voter observes a private signal about the unknown state but does not learn the turnout. First, we characterize how the outcomes of large elections depend on the turnout pattern across states. In contrast to existing results for large elections, there are equilibria in which information aggregation fails whenever there is an asymmetry in turnout; information aggregation is only guaranteed in all equilibria if turnout is state independent. Second, when the turnout is the result of costly voter recruitment by a biased organizer, the organizer can ensure that its favourite policy a is implemented with high probability independent of the state as the voter recruitment cost vanishes. Moreover, information aggregation will fail in all equilibria. The critical observation is that a vote is more likely to be pivotal for the decision if turnout is smaller, leading to a systematic bias of the decision toward the low-turnout state.

We introduce learning into an otherwise standard two-sided search-and-bargaining market. There is uncertainty about the price distribution due to uncertainty about an underlying exogenous state of relative demand: in the high state, buyers are on the long side; otherwise, they are on the short side. In equilibrium, prices are on average higher in the high state. Individual agents learn about the distribution while searching. Agents typically start out by experimenting with a tough bargaining position—buyers may initially insist on a low price and sellers on a high price. After successive failures to trade, agents become increasingly pessimistic about the market conditions and soften their bargaining stance. When frictions are small, equilibrium transaction prices are approximately market clearing, despite aggregate demand being unknown. Thus, the search-and-bargaining procedure enables price discovery in a decentralized market.