Session 19: The Economics of Transparency

We study how increasing whistleblower incentives affect a firm’s communication decisions, price informativeness and real efficiency. An informed manager, who can divert cash for private benefit, privately communicates with his employee about project fundamentals and chooses investment. Given her information, the employee maximizes internal alignment and can leak the manager’s message with some noise. Stronger whistleblower incentives lead to more informative leaks, less misconduct and higher price informativeness. However, they can decrease firm value and real efficiency by increasing the manager’s manipulation of internal communication. More targeted policies (e.g., mandating more public disclosure) improve both price informativeness and real efficiency.

We analyze a model of a monopolistic informed investor who receives private information sequentially and faces a post-trading disclosure requirement. We show that this trading model can be transformed into a fictitious consumption-saving model with a borrowing constraint. Hence, insights from the consumption-saving literature can be adapted for the trading model. For example, analogous to the insights from the permanent income hypothesis, the informed investor "saves" more of his current information when expecting less future information advantage ("saving for rainy days") or more uncertainty about it ("precautionary saving") and smooths his information "usage" over time ("consumption smoothing").

I develop a general equilibrium model to examine the innovation and welfare effects of expanding mandatory financial disclosure to a broader set of firms. In the model, disclosure by relatively small firms reveals proprietary information about their local markets, which helps larger firms enter and compete. Inspired by previous empirical findings, the model incorporates the feature that mandatory disclosure encourages (dis- courages) innovation by larger (smaller) firms. More importantly, I identify conditions for when expanding the scope of disclosure regulation increases aggregate innovation and/or welfare. I structurally estimate the model using innovation data and plausibly exogenous variation in the extent of disclosure regulation in Europe. My estimates sug- gest that subjecting 15% more firms to full reporting requirements decreases aggregate innovation by around -0.26% but increases welfare by around 1%. This disparity is driven by the fact that production shifts to the larger firms that innovate less but can mass produce their innovations at scale.

This paper studies optimal information disclosure in dynamic insurance economies with income risk in which an incumbent firm acquires more information about an agent’s persistent type than the rest of the market. If the incumbent can commit to long-term contracts but the agent can walk away, the optimal disclosure prescribes no information revelation to minimize the high-income type’s outside option and maximize cross-subsidization. If the incumbent lacks commitment, low-income consumers receive their full information allocation and no cross-subsidization is feasible for any public information disclosure because of adverse selection. Information design aims at implementing intertemporal consumption smoothing between the first period and the second period for high type consumers. The optimal information disclosure en-tails a bad signal and a partially informative good signal. Next, we allow for idiosyncratic motives to switch firms. Idiosyncratic motives reduce adverse selection and allow for the possibility of cross-subsidization for low types. Even in this case, disclosing some information may be optimal, but full information disclosure never is. Lastly, we show that when the gains from cross-subsidization are larger than the losses from adverse selection distortions, long-term relations are harmful to consumers. Our results can be used to analyze the consequences of policy proposals like open banking.

A problem that arises in buyer-supplier relationships is that a supplier may be reluctant to undertake costly up-front innovations fearing he will be held up at the time of price negotiations with the buyer. In our model, the buyer’s concern for her reputation in a repeated game leads her to employ a relational contract to mitigate the hold-up problem. The optimal relational contract has the buyer rewarding the supplier both directly with discretionary payments and indirectly via information. The buyer’s concern for her reputation (proxied by her discount factor) facilitates both larger discretionary rewards and the use of an information system that creates a greater information asymmetry between the buyer and the supplier in order to provide the supplier with larger information rents and, hence, greater incentives for innovation. The optimal information system is downward-biased: the supplier’s profitability is sometimes under-reported but is never over-reported. While the optimal information system’s informativeness is always decreasing in the buyer’s discount factor, its bias may be increasing, decreasing, or non-monotonic in that discount factor, depending on the relative efficiency of direct rewards vs. information rents in motivating innovation.

We study the effects of the first-ever ratings for corporate securities. In 1909, John Moody published a book that partitioned the majority of listed railroad bonds into letter-graded ratings based on his assessments of their credit risk. These ratings had no regulatory implications and were largely explainable using publicly available information. Despite this, we find that lower than market-implied ratings caused a rise in secondary market bond yields. Using an instrumental- variables design, we show that bonds that were rated experienced a substantial decline in their bid-ask spreads, which is consistent with reduced information asymmetries and improved liquidity. Our findings suggest that ratings can improve information transmission, even in settings with the highest monetary stakes, and highlight their potential value for the functioning of financial markets.

Responding to the rise of hydraulic fracturing (HF) and its risks to water quality, U.S. states mandated disclosure for HF wells. We study whether targeting corporate activities with dispersed externalities with transparency reduces their environmental impact. We examine salt concentrations considered signatures for HF impact and find significant and lasting improvements in surface water quality between 9-14%, coming mostly from the intensive margin. We document that operators improve environmental performance, cause fewer HF wastewater spills and use fewer hazardous chemicals. Turning to how transparency regulation works, we show that it increases public pressure and enables social movements, which facilitates internalization.

We consider the disclosure problem of a sender with a large dataset of hard evidence. The sender has an incentive to drop observations before submitting the data to the receiver to persuade them to take a favorable action. We predict which observations the sender discloses using a model with a continuum of data, and show that this model approximates the outcomes with large, multi-variable datasets. In the receiver’s preferred equilibrium, the sender plays an imitation strategy, under which they submit evidence that imitates the natural distribution under a more desirable target state. As a result, it is enough for an experiment to record data on outcomes that maximally distinguish higher states. A characterization of these strategies shows that senders with little data or a favorable state fully disclose their data, but still suffer from the receiver’s skepticism, and therefore are worse-off than they are under full information. On the other hand, senders with large datasets can benefit from voluntary disclosure by dropping observations under low states.

We conduct an experimental analysis of selective disclosure in communication. In our model, an informed sender aims to influence a receiver by disclosing verifiable evidence that is selected from a larger pool of available evidence. Our experimental design leverages the rich comparative-statics predictions of this model, enabling a systematic test of the relative importance of evidence selection versus evidence concealment in communication. Our findings confirm the key qualitative predictions of the theory, suggesting that selection, rather than concealment, is often the dominant distortion in communication. We also identify deviations from the theory: A minority of senders over communicate relative to predictions, while some receivers partially neglect the selective nature of the evidence they observe.

Firms are allowed to use aggregate data on market salaries to set pay, a practice known as salary benchmarking. Using national payroll data, we study firms that gain access to a tool that reveals market benchmarks for each job title. Using a difference-indifferences design, we find that the benchmark information reduces salary dispersion by 25%. Thus, salary dispersion must stem partly from aggregate uncertainty about the salaries offered by other firms. Our model formalizes how salary dispersion can arise even in competitive labor markets for identical workers when such uncertainty exists, and we discuss implications for an ongoing policy debate.

This paper investigates how consumers and investors react to the standardized disclosure of data privacy practices. Since December 2020, Apple has required all apps to disclose their data collection practices by filling out privacy “nutrition” labels that are standardized and easy to read. We web-scrape these privacy labels and first document several stylized facts regarding the supply of privacy. Second, augmenting privacy labels with weekly app downloads and revenues, we examine how this disclosure affects consumer behavior. Exploiting the staggered release of privacy labels and using the nonexposed Android version of each app to construct the control group, we find that after privacy label release, an average iOS app experiences a 14% (15%) drop in weekly downloads (revenue) when compared to its Android counterpart. The effect is stronger for more privacy-invasive and substitutable apps. Moreover, we observe negative stock market reactions, especially among firms that harvest more data, corroborating the adverse impact on product markets. Our findings highlight data as a key asset for firms in the digital era.

We examine the impacts of ethical declarations on market transactions through a controlled laboratory experiment, where privately-informed sellers issue a public report prior to a first-price auction. We find that while signing an ethical statement does not reduce misreporting by sellers, it significantly increases buyer trust, often skewing the terms of the trade in favor of sellers. Contrary to rational expectations, buyers consistently struggle to undo the bias. In counterfactual scenarios, from our structural analysis, we find that price efficiency improves when buyers rationally process uncertainty about sellers’ ethical preferences, yet bias may persist even when buyers have more accurate perceptions of sellers” ethical standards. Overall, our results suggests that disclosure interventions aimed at enhancing ethical conduct in market settings may not necessarily lead to more efficient pricing or reduced bias, and in some instances, may even disadvantage certain market participants.

We present a strategic disclosure model where a manager chooses between a short-term and a long-term project. The short-term cash flow can be disclosed early but can also be temporarily hidden. Without disclosure, the stock price reflects suspicions that the manager is concealing a negative outcome of the short-term project. Consistent with the existing literature, we find that strategic disclosure may lead to inefficiency, with the manager selecting an inferior short-term project to maximize the short-run price. However, our main result demonstrates that the inefficiency is quite limited, even when the manager cares almost entirely about the short-term stock price.