In this paper a market where a buyer (job seeker) is searching in a known order among sellers (e.g., a motorist driving along a road looking for gasoline) is described. Both sellers and buyers are assumed to behave strategically. There are many types of buyers. The sellers know only the distribution of all possible buyers; similarly, buyers have imperfect information about sellers. The analysis is conducted by modeling the market as a game with incomplete information; the equilibrium is characterized. A central feature of the game is that both buyers and sellers rationally update their prior information about each other as the game unfolds sequentially. It is shown that prices need not vary monotonically along the search process.

Citation indices are regularly used to inform critical decisions about promotion, tenure, and the allocation of billions of research dollars. Nevertheless, most indices (e.g., the h-index) are motivated by intuition and rules of thumb, resulting in undesirable conclusions. In contrast, five natural properties lead us to a unique new index, the Euclidean index, that avoids several shortcomings of the h-index and its successors. The Euclidean index is simply the Euclidean length of an individual's citation list. Two empirical tests suggest that the Euclidean index outperforms the h-index in practice. (JEL A14, C43)

An evidence game is a strategic disclosure game in which an informed agent who has some pieces of verifiable evidence decides which ones to disclose to an uninformed principal who chooses a reward. The agent, regardless of his information, prefers the reward to be as high as possible. We compare the setup in which the principal chooses the reward after the evidence is disclosed to the mechanism-design setup where he can commit in advance to a reward policy, and show that under natural conditions related to the evidence structure and the inherent prominence of truth, the two setups yield the same outcome. (JEL C72, D82, D83, K41)

We study a novel mechanism design model in which agents each arrive sequentially and choose one action from a set of actions with unknown rewards. The information revealed by the principal affects the incentives of the agents to explore and generate new information. We characterize the optimal disclosure policy of a planner whose goal is to maximize social welfare. One interpretation of our result is the implementation of what is known as the “wisdom of the crowd.” This topic has become increasingly relevant with the rapid spread of the Internet over the past decade.