Research

We study the effects of defaults on charitable giving in a large-scale field experiment on an online fundraising platform. We exogenously vary default options along two choice dimensions: the charitable donation decision and the “co-donation” decision regarding how much to contribute to supporting the platform. We document a strong effect of defaults on individual behavior but nevertheless find that aggregate donation levels are unaffected by defaults. In contrast, co-donations increase in the default amount. We complement our experimental results with a structural model that investigates whether personalizing defaults based on individuals' donation histories can increase donation revenues.

Job differentiation gives employers market power, allowing them to pay workers less than their marginal productivity. We estimate a differentiated jobs model using application data from Careerbuilder.com. We find direct evidence of substantial job differentiation. Without the use of instruments for wages, job applications appear very inelastic with respect to wages. Plausible instruments produce elastic firm level application supply curves. Under some assumptions, the implied market level labor supply elasticity is 0.5, while the firm level labor elasticity is 4.8. This suggests that workers may produce 21% more than their wage level, consistent with significant monopsony power.

We document that an experimental intervention offering transport subsidies for poor rural households to migrate seasonally in Bangladesh improved risk sharing. A theoretical model of endogenous migration and risk sharing shows that the effect of subsidizing migration depends on the underlying economic environment. If migration is risky, a temporary subsidy can induce an improvement in risk sharing and enable profitable migration. We estimate the model and find that the migration experiment increased welfare by 12.9%. Counterfactual analysis suggests that a permanent, rather than temporary, decline in migration costs in the same environment would result in a reduction in risk sharing.

Many countries face growing concerns that population aging may make voting and policy-making myopic. This concern begs for electoral reform to better reflect voices of the youth, such as weighting votes by voters' life expectancy. This paper predicts the effect of the counterfactual electoral reform on the 2016 U.S. presidential election. Using the American National Election Studies (ANES) data, I find that Hillary Clinton would have won the election if votes were weighted by life expectancy. I also discuss limitations due to data issues.

We use insurance claims data covering 28% of individuals with employer-sponsored health insurance in the United States to study the variation in health spending on the privately insured, examine the structure of insurer-hospital contracts, and analyze the variation in hospital prices across the nation. Health spending per privately insured beneficiary differs by a factor of three across geographic areas and has a very low correlation with Medicare spending. For the privately insured, half of the spending variation is driven by price variation across regions, and half is driven by quantity variation. Prices vary substantially across regions, across hospitals within regions, and even within hospitals. For example, even for a nearly homogeneous service such as lower-limb magnetic resonance imaging, about a fifth of the total case-level price variation occurs within a hospital in the cross section. Hospital market structure is strongly associated with price levels and contract structure. Prices at monopoly hospitals are 12% higher than those in markets with four or more rivals. Monopoly hospitals also have contracts that load more risk on insurers (e.g., they have more cases with prices set as a share of their charges). In concentrated insurer markets the opposite occurs—hospitals have lower prices and bear more financial risk. Examining the 366 mergers and acquisitions that occurred between 2007 and 2011, we find that prices increased by over 6% when the merging hospitals were geographically close (e.g., 5 miles or less apart), but not when the hospitals were geographically distant (e.g., over 25 miles apart). JEL Codes: I11, L10, L11.

Evidence suggests that growth in providers’ prices drives growth in health care spending on the privately insured. However, existing work has not systematically differentiated between the growth rate of hospital prices and that of physician prices. We analyzed growth in both types of prices for inpatient and hospital-based outpatient services using actual negotiated prices paid by insurers.

We found that in the period 2007–14 hospital prices grew substantially faster than physician prices. For inpatient care, hospital prices grew 42 percent, while physician prices grew 18 percent. Similarly, for hospital-based outpatient care, hospital prices grew 25 percent, while physician prices grew 6 percent. A majority of the growth in payments for inpatient and hospital-based outpatient care was driven by growth in hospital prices, not physician prices.

Our work suggests that efforts to reduce health care spending should be primarily focused on addressing growth in hospital rather than physician prices. Policymakers should consider a range of options to address hospital price growth, including antitrust enforcement, administered pricing, the use of reference pricing, and incentivizing referring physicians to make more cost-efficient referrals.

We examined the growth in health spending on people with employer-sponsored private insurance in the period 2007–14. Our analysis relied on information from the Health Care Cost Institute data set, which includes insurance claims from Aetna, Humana, and UnitedHealthcare. In the study period private health spending per enrollee grew 16.9 percent, while growth in Medicare spending per fee-for-service beneficiary decreased 1.2 percent. There was substantial variation in private spending growth rates across hospital referral regions (HRRs): Spending in HRRs in the tenth percentile of private spending growth grew at 0.22 percent per year, while HRRs in the ninetieth percentile experienced 3.45 percent growth per year. The correlation between the growth in HRR-level private health spending and growth in fee-for-service Medicare spending in the study period was only 0.211. The low correlation across HRRs suggests that different factors may be driving the growth in spending on the two populations.

This paper examines the impact of a government programme which facilitated the entry of for-profit surgical centres to compete against incumbent National Health Service hospitals in England. We examine the impact of competition from these surgical centres on the efficiency – measured by pre-surgery length of stay for hip and knee replacement patients – and case mix of incumbent public hospitals. We exploit the fact that the government chose the broad locations where these surgical centres (Independent Sector Treatment Centres or ISTCs) would be built based on local patient waiting times – not length of stay or clinical quality – to construct treatment and control groups that are comparable with respect to key outcome variables of interest. Using a difference-in-difference estimation strategy, we find that the government-facilitated entry of surgical centres led to shorter pre surgery length of stay at nearby public hospitals. However, these new entrants took on healthier patients and left incumbent hospitals treating patients who were sicker. This paper highlights a potential trade-off that policymakers face when they promote competition from private, for-profit firms in markets for the provision of public services.

A growing number of school districts use centralized assignment mechanisms to allocate school seats in a manner that reflects student preferences and school priorities. Many of these assignment schemes use lotteries to ration seats when schools are oversubscribed. The resulting random assignment opens the door to credible quasi-experimental research designs for the evaluation of school effectiveness. Yet the question of how best to separate the lottery-generated randomization integral to such designs from non-random preferences and priorities remains open. This paper develops easily-implemented empirical strategies that fully exploit the random assignment embedded in a wide class of mechanisms, while also revealing why seats are randomized at one school but not another. We use these methods to evaluate charter schools in Denver, one of a growing number of districts that combine charter and traditional public schools in a unified assignment system. The resulting estimates show large achievement gains from charter school attendance. Our approach generates efficiency gains over ad hoc methods, such as those that focus on schools ranked first, while also identifying a more representative average causal effect. We also show how to use centralized assignment mechanisms to identify causal effects in models with multiple school sectors.