We study the demand response to non-linear price schedules using data on insurance contracts and prescription drug purchases in Medicare Part D. We exploit the kink in individuals' budget set created by the famous "donut hole," where insurance becomes discontinuously much less generous on the margin, to provide descriptive evidence of the drug purchase response to a price increase. We then specify and estimate a simple dynamic model of drug use that allows us to quantify the spending response along the entire non-linear budget set. We use the model for counterfactual analysis of the increase in spending from "filling" the donut hole, as will be required by 2020 under the Affordable Care Act. In our baseline model, which considers spending decisions within a single year, we estimate that "filling" the donut hole will increase annual drug spending by about $150, or about 8 percent. About one-quarter of this spending increase reflects "anticipatory" behavior, coming from beneficiaries whose spending prior to the policy change would leave them short of reaching the donut hole. We also present descriptive evidence of cross-year substitution of spending by individuals who reach the kink, which motivates a simple extension to our baseline model that allows - in a highly stylized way - for individuals to engage in such cross year substitution. Our estimates from this extension suggest that a large share of the $150 drug spending increase could be attributed to cross-year substitution, and the net increase could be as little as $45 per year.

We develop a stylized model that allows us to estimate a value-added measure for nursing homes ("SNFs") which accounts for patient selection both into and out of a SNF. We use the model, together with detailed data on the physical and mental health of about 6 million Medicare SNF patients between 2011 and 2016, to estimate the value added for about 14,000 distinct SNFs. We document substantial heterogeneity in value added. Nationwide, compared to a 10th percentile SNF, a 90th percentile SNF is able to discharge a patient at the same health level almost a week sooner, or one quarter of the median length of stay. Heterogeneity in value added within a market is almost as large as it is nationwide. Our results point to the potential for substantial gains through policies that encourage reallocation of patients to higher-quality SNFs within their market.

We study the design of provider incentives in the post-acute care setting - a high-stakes but under-studied segment of the healthcare system. We focus on long-term care hospitals (LTCHs) and the large (approximately $13,500) jump in Medicare payments they receive when a patient s stay reaches a threshold number of days. Discharges increase substantially after the threshold, with the marginal discharged patient in relatively better health. Despite the large financial incentives and behavioral response in a high mortality population, we are unable to detect any compelling evidence of an impact on patient mortality. To assess provider behavior under counterfactual payment schedules, we estimate a simple dynamic discrete choice model of LTCH discharge decisions. When we conservatively limit ourselves to alternative contracts that hold the LTCH harmless, we find that an alternative contract can generate Medicare savings of about $2,100 per admission, or about 5% of total payments. More aggressive payment reforms can generate substantially greater savings, but the accompanying reduction in LTCH profits has potential out-of-sample consequences. Our results highlight how improved financial incentives may be able to reduce healthcare spending, without negative consequences for industry profits or patient health.

We analyze subprime consumer lending and the role played by down payment requirements in screening high-risk borrowers and limiting defaults. To do this, we develop an empirical model of the demand for financed purchases that incorporates both adverse selection and repayment incentives. We estimate the model using detailed transaction-level data on subprime auto loans. We show how different elements of loan contracts affect the quality of the borrower pool and subsequent loan performance. We also evaluate the returns to credit scoring that allows sellers to customize financing terms to individual applicants. Our approach shows how standard econometric tools for analyzing demand and supply under imperfect competition extend to settings in which firms care about the identity of their customers and their postpurchase behavior.

There is substantial waste in U.S. healthcare but little consensus on how to combat it. We identify one source of waste: long-term care hospitals (LTCHs). Using the entry of LTCHs into hospital markets in an event study design, we find that most LTCH patients would have counterfactually received care at Skilled Nursing Facilities—facilities that provide medically similar care but are paid significantly less—and that substitution to LTCHs leaves patients unaffected or worse off on all dimensions we can objectively measure. Our results imply Medicare could save about $4.6 billion per year by not allowing discharge to LTCHs.

We provide a graphical illustration of how standard consumer and producer theory can be used to quantify the welfare loss associated with inefficient pricing in insurance markets with selection. We then show how this welfare loss can be estimated empirically using identifying variation in the price of insurance. Such variation, together with quantity data, allows us to estimate the demand for insurance. The same variation, together with cost data, allows us to estimate how insurer's costs vary as market participants endogenously respond to price. The slope of this estimated cost curve provides a direct test for both the existence and nature of selection, and the combination of demand and cost curves can be used to estimate welfare. We illustrate our approach by applying it to data on employer-provided health insurance from one specific company. We detect adverse selection but estimate that the quantitative welfare implications associated with inefficient pricing in our particular application are small, in both absolute and relative terms.

We document four similarities between American human healthcare and American pet care: (i) rapid growth in spending as a share of GDP over the last two decades; (ii) strong income-spending gradient; (iii) rapid growth in the employment of healthcare providers; and (iv) similar propensity for high spending at the end of life. We speculate about possible implications of these similar patterns in two sectors that share many common features but differ markedly in institutional features, such as the prevalence of insurance and of public sector involvement.

Using data from employer-provided health insurance and Medicare Part D, we investigate whether healthcare utilization responds to the dynamic incentives created by the nonlinear nature of health insurance contracts. We exploit the fact that, because annual coverage usually resets every January, individuals who join a plan later in the year face the same initial ("spot") price of healthcare but a higher expected end-of-year ("future") price. We find a statistically significant response of initial utilization to the future price, rejecting the null that individuals respond only to the spot price. We discuss implications for analysis of moral hazard in health insurance.

The platform design, the process that helps potential buyers on the internet navigate toward products they may purchase, plays a critical role in reducing search frictions and determining market outcomes. We study a key trade-off associated with two important roles of efficient platform design: guiding consumers to their most desired product while also strengthening seller incentives to lower prices. We use simple theory to illustrate this, and then combine detailed browsing data from eBay and an equilibrium model of consumer search and price competition to quantitatively assess this trade-off in the particular context of a change in eBay's marketplace design.

We document some early effects of how mobile devices might change Internet and retail commerce. We present three main findings based on an analysis of eBay's mobile shopping application and core Internet platform. First, early adopters of mobile e-commerce applications appear to be people who already were relatively heavy Internet commerce users. Second, adoption of the mobile shopping application is associated with both an immediate and sustained increase in total platform purchasing, with little evidence of substitution from the core platform. Third, differences in user behavior across the mobile applications and the regular Internet site are not yet so dramatic.