I am a PhD candidate in the Economics Department at the University of Texas at Austin. In Fall 2025, I will be joining the University of Oregon as an Assistant Professor of Economics.
My research focuses on industrial organization, labor economics, and market design in healthcare and higher education.
View my CV here
Email: joribarash@utexas.edu
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Experts can leverage asymmetric information to induce demand for their services, complicating the design of payment contracts. In healthcare, physicians are widely believed to induce excessive treatment under a piece rate contract ("fee-for-service”) and inadequate treatment under a flat-fee contract ("capitation"). A single contract that mixes fee-for-service and capitation payments may balance these forces for an average physician, but heterogeneous physicians plausibly have different socially optimal contracts. I study whether offering physicians a menu of contracts can improve welfare relative to a single contract. I first develop a model of treatment decisions, showing that welfare impacts are theoretically ambiguous and depend on the correlation between physicians’ altruism, cost of effort, and patient needs. I then estimate the model using administrative data on Norwegian primary care physicians and their patients. In this population, the status quo single contract is inefficient. Physicians prefer a menu and respond by spending more time treating patients without increasing aggregate expenditure. The increase in patient health is equivalent to 5 percent of expenditure, with the largest gains for older, chronically ill, and rural patients.
This paper estimates the effect of a physician’s number of registered patients ("enrollment”) on short-run treatment intensity in the context of Norwegian primary care. I instrument for enrollment with quasi-random administrative patient assignments. The estimated effect of enrollment is negative but small for several measures of treatment intensity. For example, with one new patient registration, the average physician spends 3 fewer minutes per month across incumbent patients. Descriptive evidence suggests that crowd-out exacerbates under-treatment. Crowd-out is larger among physicians who reach their stated capacity or initially work part-time. Drawing on a model of physician decision-making, this heterogeneity implies that capacity constraints dominate income effects in explaining crowd-out. With capacity constraints, increasing the number of physicians may more effectively reduce crowd-out than incentives for greater treatment per physician. Fixing physician supply, an alternative patient assignment rule could reduce crowd-out from administrative assignment by 86 percent.
Recent policy changes limit the scope for university admission decisions to equitably ration spots. I investigate whether selective universities can instead use graduation-contingent loan forgiveness to allocate spots to the students who most benefit from attendance. Identifying variation comes from an existing loan forgiveness program that incentivized greater on-time graduation. Exploiting a discontinuity from Pell Grant eligibility, I find no detectable effect of loan take-up on course load, course completion, part-time work, on-time graduation, or earnings, so participation primarily reflects selection on unobserved ability. I incorporate selection into a structural model of students' college choice, loan forgiveness take-up, and graduation. Using model estimates, I show how counterfactual loan forgiveness could target advantageous selection rather than moral hazard, leading to greater welfare, statewide graduation, and demographic equity.
From Passive Promises to Proactive Guarantees: The Efficacy of Financial Certainty Interventions Among Automatically (In-)Admissible Students with Matt S. Giani, Richard Murphy, Stella M. Flores, Brian Dixon, and Julio Mena Bernal
Low-income high-achieving students are less likely than high-income peers to enroll in selective colleges. Financial certainty interventions can address administrative burdens that stifle their enrollment, even when colleges are tuition-free for them. However, we do not know whether these interventions are effective when students enjoy admissions certainty (e.g., with percent plans) or how financial certainty interventions interact with automatic admissions. We tested the efficacy of a direct-to-student intervention that proactively guaranteed low-income students free tuition, on-campus housing, and a housing scholarship at the University of Texas at Austin. The intervention increased application rates for the full sample, but only increased enrollment at the university among students eligible for automatic admission, for whom the intervention nearly doubled enrollment (43% vs. 24%).
Targeting Aid During a Crisis: Speed, Selection, and Subsidy Design with Lauri Kytömaa
In times of crisis, means-tested government programs sometimes relax eligibility standards to deliver aid faster. With adverse selection and less time to screen beneficiaries, relaxed eligibility may increase expenditure on non-targeted populations and decrease pass-through to households from private intermediaries, with both mechanisms lowering efficacy. The tradeoff between speed and eligibility standards is motivated by the relatively untested premise that faster delivery meaningfully improves outcomes. This paper shows that timely subsidized modification of distressed mortgages could have further reduced U.S. foreclosures in the aftermath of the 2008 financial crisis. We exploit a simulated instrument based on the spatial distribution of financial shocks. Using a dynamic structural model of servicers' modification and foreclosure choices, we characterize how the optimal modification subsidy varies with time from delinquency, servicer volume, and market conditions.
Experience Learning and Externalities: Plant-Based Substitutes
Environmental policy frequently subsidizes low-pollution products, but this approach can be relatively expensive given information frictions and ineffective given consumer heterogeneity. For example, plant-based meat has a lower carbon footprint than most animal products, but it is unclear ex-ante whether economies of scale are sufficient to spur widespread adoption. Motivated by reduced-form evidence of large changes in behavior after first purchase, I estimate demand for these products with a 10-year nationwide household panel, allowing for imperfect information about quality and rich consumer heterogeneity. I evaluate the effect of counterfactual vouchers and marginal costs on consumer surplus and CO2 emissions. Contrary to conventional wisdom, lower prices are unlikely to induce large-scale substitution, but offering vouchers to inexperienced households accelerates the pace of adoption. The averted social cost of carbon is twice as large as direct voucher costs.
Heuristic to Bayesian: The evolution of reasoning from childhood to adulthood with Isabelle Brocas, Juan D. Carrillo, and Niree Kodaverdian. Journal of Economic Behavior & Organization, 159, March 2019.
ECO 358R Supervised Research: Spring 2024 and Spring 2025 (originating instructor)
This course introduces undergraduate students to research methods with an emphasis on applied microeconomics, preparing students to write an excellent honors thesis and make an informed decision about economics graduate education. Biweekly 75-minute meetings mix short methods lectures (e.g., DiD, IV), collaborative work, and student presentations. Assignments include two replications of published articles and two original research proposals.