If profit maximization is the objective of a firm, new information about quality should affect firm behavior only through its effects on market demand. I consider an alternate model in which suppliers are motivated by a desire to perform well in addition to profit. The introduction of quality “report cards” for cardiac surgery in Pennsylvania provides an empirical setting to isolate the relative role of extrinsic and intrinsic incentives in determining surgeon response. Information on performance that was new to surgeons and unrelated to patient demand led to an intrinsic response four times larger than surgeon response to profit incentives.

We study a randomized control trial in a large employer population of access to “wearable” technologies and the associated planning and monitoring tools on improved health behaviors (sleep and exercise). Both ITT and IV estimates based on actual plan enrollment for the treatment group suggest statistically significant but economically small changes in behavior after three months. We then implement machine learning-based models to assess treatment effect heterogeneity. We find little evidence for heterogeneous treatment effects base on observables. We also present detailed data on sleep patterns underscoring the value of this new data source to researchers.

Traditional models of insurance choice are predicated on fully informed and rational consumers protecting themselves from exposure to financial risk. In practice, choosing an insurance plan is a complicated decision often made without full information. In this paper we combine new administrative data on health plan choices and claims with unique survey data on consumer information to identify risk preferences, information frictions, and hassle costs. Our additional friction measures are important predictors of choices and meaningfully impact risk preference estimates. We study the implications of counterfactual insurance allocations to illustrate the importance of distinguishing between these micro-foundations for welfare analysis.

Measuring consumer responsiveness to medical care prices is a central issue in health economics and a key ingredient in the optimal design and regulation of health insurance markets. We leverage a natural experiment at a large self-insured firm that required all of its employees to switch from an insurance plan that provided free health care to a nonlinear, high-deductible plan. The switch caused a spending reduction between 11.8% and 13.8% of total firm-wide health spending. We decompose this spending reduction into the components of (i) consumer price shopping, (ii) quantity reductions, and (iii) quantity substitutions and find that spending reductions are entirely due to outright reductions in quantity. We find no evidence of consumers learning to price shop after two years in high-deductible coverage. Consumers reduce quantities across the spectrum of health care services, including potentially valuable care (e.g., preventive services) and potentially wasteful care (e.g., imaging services). To better understand these changes, we study how consumers respond to the complex structure of the high-deductible contract. Consumers respond heavily to spot prices at the time of care, reducing their spending by 42% when under the deductible, conditional on their true expected end-of-year price and their prior year end-of-year marginal price. There is no evidence of learning to respond to the true shadow price in the second year post-switch.

Despite evidence that many consumers in health insurance markets are subject to information frictions, approaches used to evaluate these markets typically assume informed, active consumers. We develop a general framework to study insurance market equilibrium in the presence of choice frictions and evaluate key policy interventions. We identify sufficient relationships between the underlying distributions of consumer costs, surplus from risk protection, and choice frictions that determine the welfare impact of friction-reducing policies. We implement our approach empirically, showing how these key sufficient objects can be measured and the link between these objects and policy outcomes.

The ability of web-based retailers to learn about and provide targeted consumer experiences is touted as an important distinction from traditional retailers. In principal, web-based insurance exchanges could benefit from these advantages. Using data from a large-scale experiment by a private sector health insurance exchange we estimate the returns to experimentation and targeted messaging. We find significant improvements in conversions in one treatment tested. Underlying the average impact were both intertemporal and demographic heterogeneity. We estimate that learning and targeted messaging could increase insurance applications by approximately 13 percent of the baseline conversion rate.

We develop a model of selection that incorporates a key element of recent health reforms: an individual mandate. Using data from Massachusetts, we estimate the parameters of the model. In the individual market for health insurance, we find that premiums and average costs decreased significantly in response to the individual mandate. We find an annual welfare gain of 4.1% per person or $51.1 million annually in Massachusetts as a result of the reduction in adverse selection. We also find smaller post-reform markups.

We implement an empirical test for selection into health insurance using changes in coverage induced by the introduction of mandated health insurance in Massachusetts. Our test examines changes in the cost of the newly insured relative to those who were insured prior to the reform. We find that counties with larger increases in insurance coverage over the reform period face the smallest increase in average hospital costs for the insured population, consistent with adverse selection into insurance before the reform. Additional results, incorporating cross-state variation and data on health measures, provide further evidence for adverse selection.