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Register a new userOn the Impact of Information Acquisition and Aftermarkets on Auction Efficiency
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A common assumption in auction theory is that the information available to the agents is given exogenously and that the auctioneer has full control over the market. In practice, agents might be able to acquire information about their competitors before the auction (by exerting some costly effort), and might be able to resell acquired items in an aftermarket. The auctioneer has no control over those aspects, yet their existence influences agents strategic behavior and the overall equilibrium welfare can strictly decrease as a result. We show that if an auction is smooth (e.g., first-price auction, all-pay auction), then the corresponding price of anarchy bound due to smoothness continues to hold in any environment with (a) information acquisition on opponents valuations, and/or (b) an aftermarket satisfying two mild conditions (voluntary participation and weak budget balance). We also consider the special case with two ex ante symmetric bidders, where the first-price auction is known to be efficient in isolation. We show that information acquisition can lead to efficiency loss in this environment, but aftermarkets do not: any equilibrium of a first-price or all-pay auction combined with an aftermarket is still efficient.
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How to guarantee that firms perform due diligence before launching potentially dangerous products? We study the design of liability rules when (i) limited liability prevents firms from internalizing the full damage they may cause, (ii) penalties are paid only if damage occurs, regardless of the products inherent riskiness, (iii) firms have private information about their products riskiness before performing due diligence. We show that (i) any liability mechanism can be implemented by a tariff that depends only on the evidence acquired by the firm if a damage occurs, not on any initial report by the firm about its private information, (ii) firms that assign a higher prior to product riskiness always perform more due diligence but less than is socially optimal, and (iii) under a simple and intuitive condition, any type-specific launch thresholds can be implemented by a monotonic tariff.
We study the implications of endogenous pricing for learning and welfare in the classic herding model . When prices are determined exogenously, it is known that learning occurs if and only if signals are unbounded. By contrast, we show that learning can occur when signals are bounded as long as non-conformism among consumers is scarce. More formally, learning happens if and only if signals exhibit the vanishing likelihood property introduced bellow. We discuss the implications of our results for potential market failure in the context of Schumpeterian growth with uncertainty over the value of innovations.
This note provides a critical discussion of the textit{Critical Cost-Efficiency Index} (CCEI) as used to assess deviations from utility-maximizing behavior. I argue that the CCEI is hard to interpret, and that it can disagree with other plausible measures of irrational behavior. The common interpretation of CCEI as wasted income is questionable. Moreover, I show that one agent may have more unstable preferences than another, but seem more rational according to the CCEI. This calls into question the (now common) use of CCEI as an ordinal and cardinal measure of degrees of rationality.
We consider the model of the data broker selling information to a single agent to maximize his revenue. The agent has private valuation for the additional information, and upon receiving the signal from the data broker, the agent can conduct her own experiment to refine her posterior belief on the states with additional costs. In this paper, we show that in the optimal mechanism, the agent has no incentive to acquire any additional costly information under equilibrium. Still, the ability to acquire additional information distorts the incentives of the agent, and reduces the optimal revenue of the data broker. In addition, we show that under the separable valuation assumption, there is no distortion at the top, and posting a deterministic price for fully revealing the states is optimal when the prior distribution is sufficiently informative or the cost of acquiring additional information is sufficiently high, and is approximately optimal when the type distribution satisfies the monotone hazard rate condition.
We analyze statistical discrimination in hiring markets using a multi-armed bandit model. Myopic firms face workers arriving with heterogeneous observable characteristics. The association between the workers skill and characteristics is unknown ex ante; thus, firms need to learn it. Laissez-faire causes perpetual underestimation: minority workers are rarely hired, and therefore, underestimation towards them tends to persist. Even a slight population-ratio imbalance frequently produces perpetual underestimation. We propose two policy solutions: a novel subsidy rule (the hybrid mechanism) and the Rooney Rule. Our results indicate that temporary affirmative actions effectively mitigate discrimination caused by insufficient data.
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