Session 3: The Economics of Transparency

This paper examines how over-the-counter drug labels influence consumer perceptions of efficacy, distort decision-making, and shape equilibrium outcomes under counterfactual regulatory scenarios. It addresses a key identification challenge—the un-observability of perceived efficacy under different information structures—by conducting a randomized controlled trial and integrating its findings into a structural model. Using data from a control group and three treatment arms, I construct product-level measures of perceived efficacy beliefs based on pairwise product comparisons. Leveraging control group data supplemented with NielsenIQ data, I estimate a structural demand model that isolates the role of efficacy beliefs while accounting for heterogeneous preferences. I then incorporate updated beliefs to assess equilibrium effects under each information treatment. In equilibrium, the most effective intervention—emphasizing equivalent efficacy—increases substitution between biologically equivalent products by 26%, reduces consumer spending by 12%, but also introduces second-degree price discrimination driven by symptom-label preferences.

Preregistration at public research registries is considered a promising solution to the credibility crisis in science, but empirical evidence of its actual benefit is limited. Guaranteeing research integrity is especially vital in clinical research, where human lives are at stake and investigators might suffer from financial pressure. This paper analyzes the distribution of p-values from pre-approval drug trials reported to Clini-calTrials.gov, the largest registry for research studies in human volunteers, conditional on the preregistration status. The z-score density of non-preregistered trials displays a significant upward discontinuity at the salient 5% threshold for statistical significance, indicative of p-hacking or selective reporting. The density of preregistered trials ap-pears smooth at this threshold. With caliper tests, we establish that these differences between preregistered and non-preregistered trials are robust when conditioning on sponsor fixed effects and other design features commonly indicative of research in-tegrity, such as blinding and data monitoring committees. Our results suggest that preregistration is a credible signal for the integrity of clinical trials, as far as it can be assessed with the currently available methods to detect p-hacking.

We develop a model to study how the Corporate Alternative Minimum Tax (CAMT) affects firms' financial reporting behavior and their resulting tax burdens. We show that managers gradually reduce accrual-based earnings management as their book income exceeds the level that triggers the CAMT, which increases stock-price sensitivity to reported earnings. The CAMT's impact on reporting quality varies with managerial incentives: it improves this quality when managers prioritize stock prices, but reduces it when they focus on cash flows. However, it does not affect the informativeness of earnings. More profitable firms tend to pay a lower percentage of their income in CAMT, whereas firms with higher reporting precision and price-focused managers face a higher tax burden. We further study real earnings management, finding that it increases, rather than decreases, when the CAMT is triggered.

Open banking enables small businesses to share their bank financial data with potential lenders. I examine the effect of open banking on collateralization in small business lending. For identification, I exploit institutional features of the UK’s open banking policy that creates a discontinuity in firms’ eligibility to share data. Using a novel loan-level dataset covering the entire UK secured business loan market, I document that open banking eases the pledge of assets like accounts receivable and inventory. Firms eligible to share data are more likely to pledge such assets as collateral, thereby improving their access to credit. These effects are more pronounced for firms facing greater information asymmetry and those with greater information available to share. These findings highlight the role of open banking in reducing collateral constraints by mitigating information asymmetry.

How concerning is real-asset regulatory leakage after corporate social responsibility (CSR) disclosure mandates? To address this question, we examine changes in firms’ real-asset investment decisions and safety outcomes following the 2010 Dodd-Frank Section 1503 (DF1503) requirement to disclose mine-safety records in SEC filings. Using data on publicly owned (regulated) and privately owned (unregulated) mines from 2000 to 2021, we find that, after DF1503, the share of the least-safe US mines owned by public firms decreases by 36%. We estimate that 74% of this reduction reflects genuine mine-level safety improvements, while the remaining 26% is attributable to real-asset regulatory leakage—that is, ownership transfers and the avoidance of new investments in high-safety-risk mines. Most of the reported safety gains attributable to leakage (90%) stem from transferring inherently high-risk mines to unregulated firms, rather than from subsequent declines in safety under private ownership, which are relatively minor (10%). Overall, our findings suggest that, while roughly one-quarter of the observed safety improvement following DF1503 results from the reallocation of high-CSR-risk assets, the modest declines in CSR performance of the leaked assets were more than offset by safety improvements in the retained assets, consistent with an economy-wide CSR improvement. Nonetheless, overlooking the nontrivial shift of high-risk assets to the private sector may overstate the true extent of CSR gains.

Firms and jurisdictions are increasingly adopting ESG reporting, driving a growing empirical literature on the consequences of ESG reporting for investors, firms, and other stakeholders. We develop a model to understand the nuanced effects of the intro-duction of ESG reporting. In our model, a firm provides ESG and financial reports, which investors use to price the firm’s stock, influencing management’s real and reporting incen -tives. We characterize how investors respond to new ESG reporting; how the introduction of ESG reports affects corporate performance, stock prices, and market responses to financial disclosures; and trace these effects to ESG performance, expected cash flows, and financial misreporting. We provide conditions under which the introduction of ESG reporting dis- courages corporate ESG, and under which it encourages corporate ESG but lowers equity price at the same time. Comparative statics show how investor preferences (e.g., concern for ESG) and ESG efforts’ cash flow implications (e.g., penalties, subsidies, physical or transi-tion risk) affect market responses to reports, misreporting, and outcomes, suggesting effect heterogeneity in empirical tests. Finally, we discuss how our model can be applied to other settings involving non-ESG disclosures.

This paper investigates the impact of price transparency on equilibrium prices and fees by considering a policy change implemented by Airbnb that affected the transparency of cleaning fees for IP addresses from the European Union (EU). Using a difference-in-differences approach, we find a reduction in clean- ing fees of 2-4%. Consistent with our theoretical framework, we also find that listings without a cleaning fee, something that is common on Airbnb, appear more affordable after the policy change and react by increasing their nightly price by 5-6%. We argue that this result is driven by some hosts learning about the full prices of their rivals due to the transparency policy, finding themselves more affordable. This analysis uncovers a new mechanism through which greater price transparency can lead to price increases.

The past few years have seen a shift in many universities’ admission policies from test-required to either test-optional or test-blind. This paper uses laboratory experiments to examine students’ reporting behavior given their application package and the school’s interpretation of non-reported standardized test scores. We find that voluntary disclosure is incomplete and selective, supporting both the incentive of partial unraveling (students with higher scores are more likely to report) and the incentive of reverse unraveling (students facing a more favorable school interpretation of non-reporting are less likely to report). Subjects exhibit some ability to learn about the hidden school interpretation, though their learning is imperfect. Using a structural model of student reporting behavior, we simulate the potential tradeoff between academic preparedness and diversity in a school’s admission cohort. We find that, if students have perfect information about the school’s interpretation of non-reporting, test-blind is the worst and test-required is the best in both dimensions, while test-optional lies between the two extremes. When students do not have perfect information, some test-optional policies can generate more diversity than test-required, because some students with better observable attributes may underestimate the penalty on their non-reporting. This allows the school to admit more students that have worse observable attributes but report standardized test scores. The results are robust to a variety of extensions, including when schools have access to alternative signals of academic ability and standardized test score is a noisy but sufficiently informative measure of student ability.

This paper analyzes a model of firms’ decisions to publicly disclose information and investors’ incentives to provide private capital to non-disclosing firms. In this model, (i) disclosure externalities and scope for welfare-improving policy interventions arise via a financing channel; (ii) interdependencies between firms’ disclosure strategies emerge even if all information is independent across firms (i.e., without information spillovers); (iii) the equilibrium level of disclosure and private capital provision is socially inefficient; and (iv), whereas mandatory disclosure rules are strictly worse than not having any regulation, taxes and subsidies on disclosing and supplying outside capital can restore efficiency.

We propose that investors misreact differently to technological innovations based on novelty, and that these misreactions exert a real impact on firms' future innovations. First, using textual measures of novelty, we find that investors underreact to the issuance of path-breaking innovations but overreact to trend-following ones. Novel patent issuance predicts lower risk and positive forecast errors, consistent with a non-risk-based mispricing mechanism. A model where boundedly-rational investors are unsure about the true novelty of a patent at issuance, explains the empirical patterns well. Second, using exogenous distraction shocks, such as sensational news, we present causal evidence that, after disappointing returns to patent news, novel firms shift from creating and following up on novel innovations to copycatting. The findings highlight that investors' misreactions to patent novelty steer innovation away from higher-valued, groundbreaking research.

Managerial incentives are substantially related to a firm’s market value, so how information is revealed to the market affects managerial behavior. We analyze a model in which the manager needs to exert costly effort to implement a risky, long-term project and the project may generate verifiable information revealing its value. The optimal disclosure rule to motivate managerial effort is the manager’s strategic disclosure because it protects the manager from the downside of the project and induces the rational market to punish nondisclosure. A more transparent information regime is not always preferred because it may reduce the manager’s discretion over disclosure. We also derive the optimal disclosure when both effort stimulation and project selection are considered.

We study mediated information tranmission with intrinsic privacy concerns. A receiver faces a decision whose payo depends on an un-known state. A sender has an informative signal, but prefers the receiver to know as little about it as possible. A platform with an independent informative signal relates the combined information to the receiver to maximize her payoff. We show that it is possible to convey valuable information without incurring any privacy loss, but impossible to do so via simple restrictions such as prohibiting the platform to condition its messages on the sender's signal, or only disclosing sucient statistics for the receiver's decision. We show that such restrictions result in Pareto loss in the environment where the tension lies betwen providing useful information and privacy concerns, but not when the tension lies between providing useful information and incentivizing truthful report of the sender.