Abstract: We develop a novel framework for costly information acquisition in which a decision-maker learns about an unobserved state by choosing a signal distribution, with the cost of information determined by the distribution of noise in the signal. We show that a natural set of axioms admits a unique integral representation of the cost function, and we establish the uniform dominance principle: there always exists an optimal experiment that generates signals with uniform noise. The uniform dominance principle allows us to reduce the infinite-dimensional optimization problem of finding an optimal information structure to finding a single parameter that measures the level of noise. We show that an optimal experiment exists under natural conditions, and we characterize it using generalized first-order conditions that accommodate non-smooth payoff functions and decision rules. Finally, we demonstrate the tractability of our framework in a bilateral trade setting in which a buyer learns about product quality.

Abstract: We study a static bilateral trade setting with moral hazard, where a seller privately chooses quality and a buyer may pay to verify it. We show that buyer-side information acquisition can lead to informational holdup through a mechanism we call surplus squeezing: precise verification enables the seller to extract all buyer surplus, deterring inspection and causing trade to unravel. When verification is noisy, uncertainty preserves buyer surplus and sustains trade. Our framework highlights how strategic responses to learning can distort investment incentives, offering a new perspective on the limits of information precision in mitigating moral hazard.

Abstract: This paper studies the dynamics of trust and oversight in long-term relationships with limited commitment and no money. A principal continually decides whether to approve an allocation to an agent. To remain eligible, the agent must exert effort, but eligibility is observable to the principal through costly verification only. Tension between trust and oversight arises at high trust levels, where effort and verification incentives work in opposite directions. At a low trust level, incentives align, but a coordination problem arises which can be overcome through vol- untary disclosure by the agent. We fully characterize robust Markov Perfect Equilibria and show how underlying equilibrium properties can be traced back to intertemporal and contemporaneous strategic interactions.

Abstract: In this paper, we investigate monopoly pricing when the buyer can acquire information about the value of the seller's product from an independent expert. We demonstrate that the expert is advantageous to the buyer only when the cost of seeking advice is not too low. When the buyer faces a moderate cost of obtaining information from the expert, the seller ’prices out’ the expert by offering discounts to dissuade the buyer from seeking advice. This approach generates a positive surplus for the buyer. In contrast, when the buyer’s cost is low, the seller ’prices in’ the expert, capitalizing on the buyer’s easy access to information to demand a premium. We also show that the seller and intermediary may benefit from tacit collusion and direct payments in pricing-out equilibria but never in pricing-in equilibria.

Abstract: We develop a model of oligopolistic price competition in information markets where buyers purchase and combine signals from multiple sellers. This nonexclusivity transforms competition into "portfolio competition", with sellers competing against all possible coalitions rather than individual competitors. We fully characterize its pure-strategy competition equilibria and study endogenous entry. In every equilibrium, buyers purchase efficiently from all active sellers. Whether competition protects buyers from rent extraction depends on information complementarities: in duopoly, full extraction occurs if and only if signals are complements; in oligopoly this if-and-only-if condition generalizes to a coalitional "balancedness" condition. With symmetric sellers, balancedness reduces to a geometric test. Entry can paradoxically reduce competitive pressure when entrants provide strong complementarities. Entry is never excessive, contrasting standard oligopoly models where excess results from business-stealing externalities. Instead, efficient entry is always an equilibrium, though insufficient entry equilibria may exist, prompting regulatory intervention.

This paper studies a principal who incentivizes an agent to achieve and maintain compliance and voluntarily disclose incidences of non-compliance. Compliance is modeled as a persistent binary process that jumps at random times arriving at a rate that depends on the agent’s efforts. The state of compliance is verifiable by the principal only at isolated instances through costly inspections. We show that in principal-optimal equilibria, the principal attains maximum compliance by using deterministic inspections. The optimal equilibrium features periodic inspection cycles which are suspended during periods of self-reported non-compliance, in which the agent is fined. We explain how commitment to random inspections benefits the principal by relaxing the agent's incentive-compatibility constraints, and we discuss possible ways for the principal to overcome her commitment problem through third-party involvement.

We study social learning from actions and outcomes. Agents learn about future returns through privately observed signals, others' investment decisions and public experimentation outcomes when returns are realized. We characterize symmetric equilibria, and relate the extent of strategic delay of investments in equilibrium to the primitives of the information structure. Agents invest without delay in equilibrium when the most optimistic interim belief exceeds a threshold. Otherwise, delay in investments induces a learning feedback that may either raise or depress beliefs and investment choices. We show that, although ours is a strategic-experimentation game of pure informational externalities, private information may increase ex-ante welfare.

This paper studies a principal who incentivizes an agent to achieve and maintain compliance and voluntarily disclose incidences of non-compliance. Compliance is modeled as a persistent binary process that jumps at random times arriving at a rate that depends on the agent’s efforts. The state of compliance is verifiable by the principal only at isolated instances through costly inspections. We show that in principal-optimal equilibria, the principal attains maximum compliance by using deterministic inspections. The optimal equilibrium features periodic inspection cycles which are suspended during periods of self-reported non-compliance, in which the agent is fined. We explain how commitment to random inspections benefits the principal by relaxing the agent's incentive-compatibility constraints, and we discuss possible ways for the principal to overcome her commitment problem through third-party involvement.