Research

Directing consumers to higher-quality service providers has been considered an effective policy to improve service outcomes and consumer welfare in various contexts. However, higher-quality providers may tend to be more congested, and congestion may be detrimental to outcomes and welfare. We study this congestion-quality trade-off and its policy implications in the context of Japanese nursing facilities. We find that (1) within nursing facilities, higher occupancy leads to poorer care outcomes but (2) between nursing facilities, occupancy and outcome-based quality measures are positively correlated. To evaluate the welfare impact of patient reallocation policy, we then develop and estimate a model of demand for nursing facility care where choice set is potentially constrained in an unobserved manner by providers' rationing behavior. We find that congested nursing facilities are less likely to admit patients as occupancy increases but no evidence that patients dislike congestion. A simulation of a reallocation policy suggests a potential gain from occupancy smoothing even though the policy sends patients to lower-quality providers on average.

Keywords: congestion, value added, long-term care, demand estimation, choice constraint, consideration set.

This paper studies the trade-offs in healthcare capacity between access to care and supplier-induced demand. We first develop an economic model where admission/discharge decisions of healthcare facilities depend on bed occupancy through capacity constraints and demand inducements. We show that the relative importance of the two mechanisms is testable using admission/discharge responses to occupancy fluctuations at different baseline occupancy levels. Applying the framework to Japanese nursing facilities, with patient deaths as exogenous occupancy shocks, we find that short-run admission decisions are mainly driven by capacity constraints. We discuss the assignment of healthcare capacity to improve access while controlling supplier-induced demand.

Keywords: capacity constraint, congestion, supplier-induced demand, nursing facility, long-term care

Social norms are an important determinant of behavior, but the behavioral and welfare effects of norms are not well understood. We propose and axiomatize a decision-theoretic model in which a reference point is formed by the decision maker's perceptions of which actions are admired (prescriptive norms) and which are prevalent (descriptive norms), and utility depends on the pride of exceeding the reference point or the shame of falling below it. The model is simple, yet provides a unified explanation for previous empirical findings, and is useful for behavioral and welfare analysis of norm-evoking policies with a revealed preference approach. 

Keywords: norms, reference dependence, pride, shame, public recognition, norm nudge

We study the effect of complementing public health care with private care. Leveraging a policy at the Veterans Health Administration that generates discontinuity in private care access, we find that expanding coverage to private care increases private outpatient care by $53 (SE: 5) and decreases VA outpatient care by $20 (SE: 7), with no impact on inpatient care. The policy led to a marginally significant 0.1 p.p. (2.8%, SE: 0.04) decrease in one-year mortality, possibly because of decreased wait times and increased access to certain specialty care. Given our estimates, the benefit of access expansion significantly outweighs the increased costs.

Keywords: veterans, healthcare access, public health care, public policy, regression discontinuity

We estimate how the spatial assortment of offline stores near a consumer affects their online spending. Our data on US business locations and internet usage permits a comparison of this relationship across retailers and product categories that is informative about the relative sizes of business-stealing effects, cross-channel complementarities, and showrooming effects. We find that a consumer’s spending at a multichannel retailer’s online store falls (1.1–5.2%, on average) when a rival adds a nearby storefront but rises (12.5–57.9%) when the retailer opens its own storefront. Offline stores often boost Amazon’s sales, especially in categories in which showrooming effects are likely relevant.