IRIS VRIONI
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Welcome to my page!
I am an Assistant Professor in the Department of Economics at the University of Rochester.
I am an applied microeconomist studying education, labor, and behavioral questions using tools from empirical industrial organization.
Email: ivrioni [at] ur.rochester.edu
You can view my CV here.
WORKING PAPERS
“Inequity in Centralized College Admissions with Public and Private Universities: Evidence from Albania” (Job Market Paper)
“Inequity in Centralized College Admissions with Public and Private Universities: Evidence from Albania” (Job Market Paper)
[Paper]
Centralized assignment systems are a popular policy tool to improve fairness and efficiency in allocating students to public college seats. In most implementations, however, private college admissions remain decentralized, which may give high socio-economic status (SES) students a strategic advantage in the centralized public match because high-SES students derive higher value from expensive private alternatives. I empirically study application behavior and the allocation of students in markets where only public college seats are centrally assigned with new data from the college match in Albania. Using a policy change that incorporated all private colleges in the centralized platform, which differentially shifted outside alternatives by SES, I find that when private colleges operate outside the match, high-SES students apply to more selective portfolios and enroll in more selective public programs, but the selectivity gap in applications shrinks after the policy change. I build and estimate a model of applications and matriculation that uses the unique institutional features of the Albanian college admissions to disentangle the effects of heterogeneous beliefs, preferences, and outside options on choice, and evaluate the distributional consequences of counterfactual admissions design. I find that removing outside options reverses the welfare gap in favor of lower-SES students, but at the expense of overall market efficiency. This is driven by the fact that outside options dampen the distortionary effects of list size restrictions and incorrect beliefs on choice.
“Gender, Early Signals, and the Career Outcomes of Top Mathematical Talent: Evidence from the Putnam Math Competition”
“Gender, Early Signals, and the Career Outcomes of Top Mathematical Talent: Evidence from the Putnam Math Competition”
[Awarded: NBER Dissertation Fellowship on Identifying and Developing Mathematical Talent Among Youth]
Top-talent labor and education markets are unique in the importance that skill ordering within top students has on the distribution of rewards (Stephan, 2012; Hill, 2020). How well talent ordering is observed by academic supervisors, in particular early in one’s career, may have important consequences for future opportunities, but little is known about the information quality that academic supervisors have about their students. I digitize archival records on all participants of the Putnam Mathematical Competition over three decades to make progress on the following questions: (1) Are supervisor perceptions of talent different for women and men of highest ability? (2) Do any such differences affect the education and career trajectories of top talent women? A unique feature of the Putnam offers insight. Anyone from each college can participate individually, but each college's team of three is pre-selected by a supervisor who ranks students ahead of the competition in order of expected score. I find that ex-ante, for women and men with the same ex-post competition scores, supervisors expect women to do worse than their male peers. Women are less likely than men to have been pre-selected in the top three, even when they obtain a score that places them in the top three performers of their college. Female supervisors are no less biased than male supervisors. I find evidence of supervisor learning about individual women, but not about the group over time. I then link individuals to their later outcomes to evaluate long-run effects of talent misperception for women.
“How Costs Limit Contraceptive Use among Low-Income Women in the U.S.: A Randomized Control Trial.” June 2023.
“How Costs Limit Contraceptive Use among Low-Income Women in the U.S.: A Randomized Control Trial.” June 2023.
with Martha J. Bailey, Vanessa Lang, Alexa Prettyman, Lea J. Bart, Daniel Eisenberg, Paula Fomby, Jennifer Barber. Vanessa Dalton
with Martha J. Bailey, Vanessa Lang, Alexa Prettyman, Lea J. Bart, Daniel Eisenberg, Paula Fomby, Jennifer Barber. Vanessa Dalton
The Affordable Care Act eliminated cost-sharing for contraception for Americans with health insurance, but substantial cost sharing remains for uninsured individuals who seek care through Title X—a national family planning program that provides patient-centered, subsidized contraception and reproductive health services in the U.S. This paper uses a randomized control trial (RCT) to examine how cost-sharing at Title X providers affects the choice of contraceptive method. The study randomizes vouchers that cover any contraceptive method up to the cost of 50% or 100% of a name-brand intra-uterine device (IUD). The results show that Title X clients are highly constrained by the out-of-pocket costs of contraception. The offer of free contraception is associated with a 40% increase in the use of any birth control method (ITT effect), a 94% increase in the value of birth control purchased, a 328-day (226%) increase in the period covered by contraceptives purchased, and a 324% increase in the likelihood of choosing a long-acting, reversible method (an IUD or implant). The results imply that eliminating the costs of contraception for Title X clients nationwide would reduce undesired pregnancies by 5.3%, birth rates by 3.9%, and abortions by 8.3%, and save $1.43 billion in the first year of the program.
WORK IN PROGRESS
“Price and Quality of Colleges in Systems with Centralized Admissions”
“Price and Quality of Colleges in Systems with Centralized Admissions”
“Educating International Mathematical Talent in the U.S.”
“Educating International Mathematical Talent in the U.S.”
TEACHING
Introduction to Statistics and Econometrics (Winter 2022), University of Michigan
Intermediate Microeconomics (Fall 2020, Fall 2021), University of Michigan
Intermediate Statistics and Econometrics (Fall 2019), University of Michigan
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