Working Paper
Timothy J. Layton, Nicole Maestas, Daniel Prinz, and Boris Vabson. Working Paper. “Public vs. Private Provision of Social Insurance: Evidence from Medicaid.” Revisions Requested at American Economic Journal: Economic Policy.Abstract
Public health insurance benefits in the U.S. are increasingly provided by private firms. We assess the consequences of private provision by exploiting the staggered introduction of enrollment mandates across counties in Texas and New York, which required disabled Medicaid beneficiaries to shift to private health plans. In Texas, where the public program uses strict rationing to control costs, privatization led to higher Medicaid spending but also improvements in healthcare. In New York, where the public program is more generous, privatization did not affect Medicaid spending but resulted in a large decrease in inpatient admissions. We conclude that the consequences of private provision depend critically on the design of the public and private programs. 
Working Paper
Michael Geruso, Timothy Layton, Grace McCormack, and Mark Shepard. Working Paper. “The Two Margin Problem in Insurance Markets”. Working Paper Slides
In Preparation
Amanda Krieder, Timothy Layton, Mark Shepard, and Jacob Wallace. In Preparation. “Adverse Selection and Access to High Quality Specialty Care under Privatized Social Insurance Programs: Evidence from New York Medicaid”.
Keith Ericson, Timothy Layton, Adrianna McIntyre, and Adam Sacarny. In Preparation. “Frictions vs. Premiums Impeding Take-up of Subsidized Health Insurance Coverage: Evidence from a Field Experiment”.
Timothy Layton, Nicole Maestas, Daniel Prinz, Mark Shepard, and Boris Vabson. In Preparation. “Grading Medicaid: Fiscal Federalism and Social Insurance in the United States”.
Tal Gross, Timothy Layton, and Daniel Prinz. In Preparation. “Liquidity and Healthcare Consumption: Evidence from Social Security Payments”.Abstract
Cost-sharing mechanisms such as copayments and deductibles can distort the healthcare consumption of consumers with no cash. We test for that possibility by studying the distribution of monthly Social Security checks among Medicare recipients. On the day that low-income Medicare recipients receive their Social Security checks, they become 4–8 percent percent more likely to fill a prescription. That effect is concentrated in low-income areas, and is of a similar magnitude for a variety of therapeutic classes, including essential drugs that treat cardiovascular, respiratory, and mental health conditions, as well as diabetes. We observe no effect among Medicare recipients who qualify for generous copay subsidies. High-frequency prescription-refill data allow us to directly observe Medicare Part D recipients whose prescriptions need to be refilled and yet who do not refill them until their checks arrive. The results suggest that up to 6 percent of low-income Medicare recipients time their healthcare consumption based on their Social Security checks.
Timothy J. Layton, Michael Geruso, and Jacob Wallace. In Preparation. “Are All Managed Care Plans Created Equal? Evidence from Random Plan Assignment in New York Medicaid Managed Care”.
Zarek Brot-Goldberg, Timothy Layton, Boris Vabson, and Adelina Wang. In Preparation. “The Mechanisms behind Choice Passivity: Evidence from Medicare Part D”.
Brian McGarry, Timothy Layton, and David Grabowski. Forthcoming. “The Effects of Plan Payment Rates on the Market for Medicare Advantage Dual-Eligible Special Needs Plans.” Health Services Research.
Savannah Bergquist, Timothy Layton, Thomas McGuire, and Sherri Rose. Forthcoming. “Sample Selection for Medicare Risk Adjustment Due to Systematically Missing Data.” Health Services Research.
Timothy J. Layton, Thomas G. McGuire, and Richard van Kleef. Forthcoming. “Deriving Risk Adjustment Payment Weights to Maximize Efficiency of Health Insurance Markets.” Journal of Health Economics. NBER Working Paper
Savannah Berquist, Timothy Layton, Thomas McGuire, and Sherri Rose. Forthcoming. “Intervening on the Data to Improve the Performance of Health Plan Payment Models.” Journal of Health Economics.
Michael Geruso and Timothy J. Layton. Forthcoming. “Upcoding or Selection? Evidence from Medicare on Squishy Risk Adjustment.” Journal of Political Economy. NBER Working PaperAbstract

Upcoding—manipulation of patient diagnoses in order to game payment systems—has gained significant attention following the introduction of risk adjustment into US insurance markets. We provide new evidence that enrollees in private Medicare plans generate 6% to 16% higher diagnosis-based risk scores than they would generate under fee-for-service Medicare, where diagnoses do not affect payments. Our estimates imply upcoding generates billions of dollars in excess public spending annually and significant consumer choice distortions. We show that coding intensity increases with vertical integration, reflecting a principal-agent problem faced by insurers, who desire more intense coding from the physicians with whom they contract.

Michael Geruso, Timothy J. Layton, and Daniel Prinz. 2019. “Screening in Contract Design: Evidence from the ACA Marketplaces.” American Economic Journal: Economic Policy, 11, 2, Pp. 64-107. NBER Working PaperAbstract
We study insurers' use of prescription drug formularies to screen consumers in the ACA Health Insurance exchanges. We begin by showing that exchange risk adjustment and reinsurance succeed in neutralizing selection incentives for most, but not all, consumer types. A minority of consumers, identifiable by demand for particular classes of prescription drugs, are predictably unprofitable. We then show that contract features relating to these drugs are distorted in a manner consistent with multidimensional screening. The empirical findings support a long theoretical literature examining how insurance contracts offered in equilibrium can fail to optimally trade off risk protection and moral hazard. 
Timothy J. Layton, Michael Barnett, Tanner Hicks, and Anupam Jena. 2018. “Diagnosis of attention deficit hyperactivity disorder and time of school enrollment.” New England Journal of Medicine, 379, 22, Pp. 2122-2130. Publisher's Version
Keith Ericson, Jon Kingsdale, Timothy J. Layton, and Adam Sacarny. 2/7/2017. “Using 'Nudges' to Enhance Competition and Save Consumers Money on Health Insurance Exchanges/Marketplaces: Evidence from a Field Experiment.” Health Affairs, 36, 2, Pp. 311-319. Publisher's Version
Anna Sinaiko, Timothy Layton, Sherri Rose, and Thomas McGuire. 2017. “Family Risk Pooling in Individual Health Insurance Markets.” Health Services and Outcomes Research Methodology, 17, 3-4, Pp. 219-236.
Sherri Rose, Savannah Bergquist, and Timothy J. Layton. 2017. “Computational health economics for identification of unprofitable health care enrollees.” Biostatistics.
Timothy J. Layton. 2017. “Imperfect Risk Adjustment, Risk Preferences, and Sorting in Competitive Health Insurance Markets.” Journal of Health Economics, 56, Pp. 259-280. Publisher's VersionAbstract

Much of the risk adjustment literature focuses on its effects on insurers’ incentives to inefficiently manipulate insurance contracts to “cream-skim” the healthiest enrollees in the market (Glazer and McGuire 2000). However, when prices are set competitively as in the Exchanges established by the ACA, risk adjustment can also ameliorate another important type of selection problem, in the extreme case known as market unraveling or death spirals, where consumers inefficiently sort between plans due to the correlation between costs and demand. In this paper, I study how imperfect risk adjustment affects prices, sorting, and welfare in competitive health insurance markets. First, I build on the model of Einav et al. (2010) to show graphically and in a theoretical model that imperfect risk adjustment causes plan prices to be based on the portion of costs not predicted by the risk adjustment model (“residual costs”), rather than total costs. This adjusting of costs has the potential to substantially weaken the connection between demand and costs that is the source of the adverse selection problem, and the extent to which it will do so depends on the correlation between demand and the costs predicted by the risk adjustment model (“predicted costs”). In a setting where consumers are required to choose between two plans, and one plan is adversely selected, if predicted costs are positively (negatively) correlated with demand for that plan, risk adjustment will cause the prices of the two plans to converge (diverge), resulting in more (fewer) consumers choosing the adversely selected plan. I then use administrative health insurance claims data from a large employer to estimate the joint distribution of preferences, total costs, and predicted costs for a large sample of employees. I use the estimates to simulate competitive equilibria under several common forms of risk adjustment in a setting similar to the Exchanges. I find that in this setting when there is no risk adjustment, the market completely unravels and the entire market enrolls in the less comprehensive plan. However, when diagnosis-based risk adjustment similar to that being implemented in the Exchanges is implemented, a substantial portion of the market unraveling is undone, with over 80% of individuals enrolling in the more comprehensive plan. Estimates suggest that this implies a substantial welfare gain of over $700 per person, per year in this setting. 

Timothy J. Layton and Thomas G. McGuire. 2017. “Marketplace Plan Payment Options for Dealing with High-Cost Enrollees.” American Journal of Health Economics, 3, 2, Pp. 165-191. NBER Working Paper