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Working Paper
Navigating Higher Education Insurance: An Experimental Study on Demand and Adverse Selection
Balakrishnan, Sidhya; Bettinger, Eric; Kofoed, Michael S.; Ritter, Dubravka; Webber, Douglas A.; Aksu, Ege; Hartley, Jonathan S. (2024-04-19)
We conduct a survey-based experiment with 2,776 students at a non-profit university to analyze income insurance demand in education financing. We offered students a hypothetical choice: either a federal loan with income-driven repayment or an income-share agreement (ISA), with randomized framingof downside protections. Emphasizing income insurance increased ISA uptake by 43%. We observe that students are responsive to changes in contract terms and possible student loan cancellation, which is evidence of preference adjustment or adverse selection. Our results indicate that framing specific ...
Finance and Economics Discussion Series , Paper 2024-024

Working Paper
Place-Based Labor Market Inequality
Webber, Douglas A.; Agnes, Isabella; Liu, Jessica; Troland, Erin (2025-06-02)
This paper presents an overview of how various labor market indicators differ across geography. While many indicators are often discussed in terms of national aggregates, such discussions obscure the large degree of variation that exists across localities. We primarily use counties as a geographic unit, and document both structural differences that persist over time as well as differences in the past two business cycles. The racial composition of communities plays a large role in explaining geographic differences in labor market indicators, in some cases even more so than income. We ...
Finance and Economics Discussion Series , Paper 2025-040

Working Paper
Suitability of a County-Level Income Definition for Analysis of Lower-Income Communities
Troland, Erin; Agnes, Isabella; Dries, Ellie; Liu, Jessica; Merchant, Zofsha; Shaalan, Fatimah; Tran, Michelle; Tranfaglia, Anna; Webber, Douglas A. (2025-06-02)
This paper examines the costs and benefits of using a straightforward county-level income definition in the classification and study of lower-income communities. A definition based on population-weighted distribution of county-level median household incomes does a good job of identifying the most economically disadvantaged communities across a wide range of indicators. We show robustness to the use of different thresholds, levels of geography, and cost-of-living adjustments.
Finance and Economics Discussion Series , Paper 2025-039

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