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 unobservability 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.

No one can remain neutral regarding health information about their conditions. While some focus on the worst-case scenario, others seek justifications for not visiting the doctor. The complexity and diversity of current online health information (OHI) cater to both groups. This paper explains this behavior through the modification of the information acquisition model and further examines its relationship with healthcare utilization. It introduces a rational inattention model with a modified cost function that accounts for individual heterogeneity in perceiving the absence of illness. The model demonstrates that information acquisition costs are influenced by individuals’ concerns about overlooking signs of illness, causing information sources to act as thought accelerators rather than purely educational material. Empirical analysis supports the theoretical framework. First, the data shows that OHI usage generally leads to higher healthcare utilization. Second, OHI users who are concerned about missing illness signs use healthcare services more than those less worried. Third, the statistically insignificant difference in how OHI affects healthcare usage between groups that might benefit from increased concern and those that do not suggests that patients’ overconfidence, rather than knowledgeable worry, drives higher healthcare use. These findings raise critical policy questions about managing OHI-induced overconfidence and offer recommendations for enhancing physician–patient interactions in the context of OHI. (New update coming soon)

This paper shows that in regulated healthcare markets, delayed reimbursement can improve hospital technology adoption by acting as a screening device. We study transcatheter aortic valve replacement (TAVR) from 2010–2020 and show that 20% of eventual adopters entered when per-case margins were negative, largely because TAVR served as a quality signal that attracted patients across hospital boundaries. A hospital-choice model shows that adoption reduced travel disutility by 22%, making patients willing to travel 29% farther to reach an adopting hospital. Early adoption therefore reveals low-cost hospitals, while non-adoption identifies financially constrained ones. In a dynamic adoption model, delayed reimbursement combined with targeted subsidies to these constrained hospitals outperforms immediate uniform reimbursement, making delay an informational instrument rather than merely a friction.

This paper discuss theoretically and empirically second degree price discrimination under the condition when companies use pricing strategies to prevent consumers form learning about equivalence in quality.