Optimal Disclosure Policy Research Articles

To disclose or to conceal? Comparison of different disclosure policies in queues with loss-averse customers

In many service industries, information disclosure about the product can alleviate customers’ loss aversion induced by uncertain product valuation. In this paper, we consider a single-server queueing system in which the manager who privately learns the valuation information discloses the valuation information strategically to loss-averse customers. We investigate the impact of the customers’ loss aversion on the system’s equilibrium arrival rate and the manager’s optimal disclosure policy. We find that loss aversion restrains customers from joining the queue. Surprisingly, we find that there is no one disclosure policy that always prevails over other disclosure policies. Specifically, the full disclosure policy is optimal only when the valuation is large and the degree of loss aversion is moderate. The full non-disclosure policy is optimal when the degree of loss aversion is too large or too small, or the valuation is small. The threshold disclosure policy is optimal when the valuation and the degree of loss aversion are moderate. Furthermore, under the threshold disclosure policy, the increasing degree of loss aversion makes managers be more reluctant to disclose the valuation.

Optimal Allocation via Waitlists: Simplicity Through Information Design

Abstract We study non-monetary markets where objects that arrive over time are allocated to unit-demand agents with private types, such as in the allocation of public housing or deceased-donor organs. An agent’s value for an object is supermodular in her type and the object quality, and her payoff is her value minus her waiting cost. The social planner’s objective is a weighted sum of allocative efficiency (i.e. the sum of values) and welfare (i.e. the sum of payoffs). We identify optimal mechanisms in the class of direct-revelation mechanisms. When the social planner can design the information disclosed to the agents about the objects, the optimal mechanism has a simple implementation: a first-come first-served waitlist with deferrals. In this implementation, the object qualities are partitioned into intervals; only the interval containing the object quality is disclosed to agents. When the planner places a higher weight on welfare, optimal disclosure policies become coarser.

Stress tests and model monoculture

We study whether regulators should reveal stress test results that contain imperfect information about banks' financial health. Although disclosure restores market confidence in banks, it misclassifies some healthy banks as risky. This encourages banks to choose portfolios deemed safe by regulators, leading to model monoculture and making the financial system less diversified. Under the ex-ante optimal disclosure policy, the regulator addresses this tradeoff by fully revealing stress test results when adverse selection is very severe or very mild, but never disclosing the results otherwise.

Morale, performance and disclosure

AbstractWe study the optimal disclosure policy in a sender–receiver communication game where the receiver's morale, defined as his expected state of the world, affects his performance. The sender observes the state and chooses whether to disclose it to the receiver, who then decides whether to participate in a task. The receiver wins if his performance in the task meets a target. No disclosure is optimal if the receiver wins with average morale in each state. Otherwise, in the threshold disclosure equilibrium that Pareto‐dominates full disclosure, the receiver quits as the sender discloses the worst states and wins as the sender withholds the rest. The receiver wins in more states in the Pareto‐optimal equilibrium as the sender chooses a non‐monotonic disclosure policy. Our theory reveals a trade‐off between transparency and efficiency when morale affects performance. It has applications in a broad range of areas including military, family, education and business.

Optimal stress tests and liquidation cost

We study stress tests as Bayesian persuasion within the fundamental bank run framework. This paper shows that the optimal disclosure policy depends on the liquidation cost of the long-term asset. In particular, when the liquidation cost is low, the optimal stress test fully discloses information about banks: it increases the likelihood of enjoying the high asset return. When the liquidation cost is high, the optimal stress test partially discloses information: it reduces the likelihood of costly bank runs. The central trade-off in stress test design is between the bank run cost and the high asset return. The theory suggests regulatory policy coordination and offers insights on different stress testing experiences across countries.

When to disclose the number of contestants: Theory and experimental evidence

This paper investigates whether it is optimal for a contest organizer to disclose the actual number of contestants for total effort optimization when entry in a contest is costly and endogenous. Our model suggests that in a Tullock (1980) contest, the answer depends on the convexity of the cost of effort function. Even though the equilibrium entry rate and rent dissipation are invariant to the disclosure policy, disclosing (concealing) the actual number of entrants can lead to a higher total effort when the cost function is concave (convex). To test these theoretical predictions, we design a 2×3 between-subjects laboratory experiment using lottery contests. We vary the disclosure policy (fully disclosed vs. fully concealed) in one dimension and the curvature of the cost of effort function (concave, linear, or convex) in the other dimension. Our results are largely consistent with the theoretical predictions regarding the optimal disclosure policy, despite the presence of moderate over-entry and over-exertion behavior that is commonly observed in experimental studies of contests.

Harnessing beliefs to optimally disclose contestants’ types

AbstractA contestant’s effort depends on her knowledge of her rival’s type. This knowledge is often limited in real-life contests. We propose a model where the principal of a contest has commitment power to verifiably disclose contestants’ types. We investigate the optimal disclosure policy to stimulate contestants’ efforts. Full disclosure stimulates more (less) effort than full concealment if high-types are more (less) likely than low-types. However, regardless of the likelihood of types, the optimal policy is that of contingent disclosure; it is optimal to commit to disclosing if both contestants are high types and concealing otherwise.

Deterministic state-based information disclosure policies and social welfare maximization in strategic queueing systems

Understanding the impact of the queue length information on the behavior of customers is nowadays a hot topic for strategic queueing problems. Particularly, it is important to understand how this information impacts the equilibrium behavior and therefore global performance metrics in order to give some recommendations to service providers for optimizing their objective. Recent works are focused on information policies in order to optimize the provider’s profit. In this work, the aim is to maximize the expected social welfare. It is intuitive that the expected social welfare is higher when more information is available to new customers. In some circumstances, and particularly when the queue is overloaded, providing the information up to a particular level of occupancy yields a better expected social welfare compared to always providing queue length information to new customers. This counterintuitive result comes mainly from the strategic behavior of customers at equilibrium when queue length information is not available. After proving that there exists such an optimal information disclosure policy (IDP) for arbitrary arrival and service rates, we go further and study the expected social welfare for the overloaded context in which the arrival rate equals the service rate. Finally, numerical illustrations corroborate our contributions, and moreover, they show that an admission control policy can be also proposed, combined with an IDP, in order to optimize the expected social welfare of the system.

Optimal certification policy, entry, and investment in the presence of public signals

AbstractWe explore the optimal disclosure policy of a certification intermediary where (i) the seller decides on entry and investment in product quality, and (ii) the buyers observe an additional public signal on quality. The optimal policy maximizes rent extraction from the seller by trading off incentives for entry and investment. We identify conditions under which full, partial or no disclosure can be optimal. The intermediary's report becomes noisier as the public signal gets more precise, but if the public signal is sufficiently precise, the intermediary resorts to full disclosure. However, the social welfare may reduce when the public signal becomes more informative.

Information Design in Financial Markets

We study the optimal disclosure policy of a firm that wishes to maximize its expected stock price in the classic setting in which its stock is traded by risk-averse investors and noise traders. The optimal policy is imprecise and leads to skewed posterior beliefs. This policy subjects short positions to tail risk, causing investors to demand a large increase in price to absorb noise-trader purchases and leading to overvaluation. Despite providing purely firm-specific information, this policy impacts the firm's expected returns. We further show the firm can inflate its price even when restricted to simple policies that withhold news lying above or below a threshold.

Information disclosure on the contest mechanism

In this paper, we study how to disclose the precision of the winner selection mechanism (i.e., the contest success function) that determines how effective a player’s effort is in determining his/her winning probability. Specifically, we focus on the disclosure of the adopted discriminatory power r of the Tullock contest. The discriminatory power r is exogenously given, and the contest organizer knows more than contestants about the true state of r. We examine the optimal disclosure policy that maximizes the expected sum of contestants’ efforts. In addition to public disclosure, we study private disclosure over groups with independent signals. We establish the optimality of full disclosure/concealment.

On the optimal disclosure of queue length information

AbstractSimhon et al. (2016) proved that disclosing queue length to customers when the queue is shorter than some threshold and concealing the information otherwise cannot maximize the throughout of M/M/1 queues—when customers are familiar with the policy and the threshold. We show that said policy indeed maximizes throughput when customers do not have information of the policy. Furthermore, we prove that the socially optimal disclosure policy under this setting contains a “hole,” that is, it is socially optimal to disclose queue length to the customers when the queue is sufficiently short or sufficiently long but not disclose otherwise.

Optimal Dynamic Allocation: Simplicity through Information Design

We study dynamic nonmonetary markets where objects are allocated to unit-demand agents with private types. An agent’s value for an object is supermodular in her type and the quality of the object, and her payoff is quasilinear in her waiting cost. We identify the welfare-maximizing mechanism in the class of direct-revelation mechanisms that elicit agents’ types and assign them to objects over time. When the social planner can design the information disclosed to the agents about the objects, this mechanism can be implemented by a first-come first-served wait-list with deferrals. The optimal disclosure policy pools adjacent object types. Moreover, the hazard rate of the distribution of the agents’ types determines the structure of the optimal disclosure policy, when the agents’ utility function is separable. A single-peaked (single-dipped) hazard rate leads to the optimality of a lower censorship (upper censorship) policy.

Optimal Stress Tests and Liquidation Cost

We study stress tests as Bayesian persuasion within the fundamental bank run framework. This paper shows that the optimal disclosure policy depends on the liquidation cost of the long-term asset. In particular, when the liquidation cost is high, the optimal stress test partially discloses information about banks' asset: it reduces the likelihood of bank runs. When the liquidation cost is low, the optimal stress test fully discloses information: it increases the likelihood of enjoying the high asset return. The central trade-off in the design of a stress test is between the bank run cost and the high asset return. The theory suggests regulatory policy coordination - joint design of the stress test and other policies that affect asset market liquidity.

Disclosure in Epidemics

We study information disclosure as a policy tool to minimize welfare losses in epidemics through mitigating healthcare congestion. We first present a stylized model of the healthcare congestion game to show that congestion occurs only when individuals expect the disease to be sufficiently severe, and it leads to misallocation of scarce healthcare resources. Coarse information disclosure, compared with full transparency, can be welfare-improving, as it can help avoid some congestion when the true severity level is high. The optimal disclosure policy features a middle censorship rule, which censors an intermediate range of severity levels and fully reveals all other states. Under the optimal policy, when information is censored, the healthcare system is run at its full capacity without congestion and, thus, achieves ex post efficiency. In an epidemic outbreak, the optimal censorship range expands if the disease is more infectious; and the optimal disclosure policy censors (weakly) higher severity levels but fully reveals (strictly) lower severity levels if the healthcare system is more prepared.

Contest Architecture with Public Disclosures

I study optimal disclosure policies in sequential contests. A contest designer chooses at which periods to publicly disclose the efforts of previous contestants. I provide results for a wide range of possible objectives for the contest designer. While different objectives involve different trade-offs, I show that under many circumstances the optimal contest is one of the three basic contest structures widely studied in the literature: simultaneous, first-mover, or sequential contest.

Information disclosure in optimal auctions

This paper analyzes a situation in which the seller controls the accuracy of what potential buyers learn about their valuation of a good to be sold. This setting is related to many real situations such as home sales, antique auctions, and digital platforms such as Google and Facebook selling online advertising slots. Two important questions arise: what is the optimal selling mechanism, and what is the optimal disclosure policy of the seller. Under the assumption of private values, a simple auction with a reserve price is the optimal mechanism. What we show is that the amount of (costly) information provided increases with the number of potential bidders when using the optimal mechanism and is greater than when the object is always sold. Because information changes the distribution of a bidder’s expected valuations, the optimal reserve price also changes, so that the number of bidders (indirectly) affects the reserve price. We show that as the number of bidders increases, the optimal reserve price becomes more restrictive.

When the principal knows better than the agent: Subjective evaluations as an optimal disclosure mechanism

AbstractWhen the firm has some private and unverifiable information about an employee’s ability, it can design a subjective evaluation mechanism, whereby payments are tied to evaluations, to communicate such information. In this paper, I investigate how to design an optimal disclosure mechanism for the firm. I characterize the firm’s optimal disclosure policy as a function of the worker’s ability distribution, with the hazard rate function playing a key role. I also demonstrate that with some reasonable restrictions on the ability distribution, the firm’s optimal strategy exhibits a particular pattern: it will reward the best workers aggressively, fire the worst ones, and assign one central rating to the rest. The predictions are consistent with the way firms utilize subjective evaluations in reality.

Preemption Through Non-Disclosure

An informed bidder can voluntarily disclose his private information on the value of an auctioned asset to rival bidders and the seller. We examine the informed bidder's optimal disclosure policy and the resulting consequences on the seller's payoff. We show that the informed bidder strategically withholds information to create a winner's curse for rival bidders, which has a preemptive effect on the rival's participation. Taking into account this strategic response, we show that increased competition among bidders may reduce the seller's payoff a surprising result that is contrary to the common belief that bidder competition generally increases the seller's payoff.

Stress tests and information disclosure

We study an optimal disclosure policy of a regulator that has information about banks (e.g., from conducting stress tests). In our model, disclosure can destroy risk-sharing opportunities for banks (the Hirshleifer effect). Yet, in some cases, some level of disclosure is necessary for risk sharing to occur. We provide conditions under which optimal disclosure takes a simple form (e.g., full disclosure, no disclosure, or a cutoff rule). We also show that, in some cases, optimal disclosure takes a more complicated form (e.g., multiple cutoffs or nonmonotone rules), which we characterize. We relate our results to the Bayesian persuasion literature.