More Like this

1. Measuring US Fiscal Capacity Using Discounted Cash Flow Analysis

   Jiang, Zhengyang; Lustig, Hanno; Van Nieuwerburgh, Stijn; Xiaolan, Mindy Z. (April 2023, Brookings papers on economic activity)

   We use discounted cash flow analysis to measure the projected fiscal capacity of the US federal government. We apply our valuation method to the Congressional Budget Office (CBO) projections for the US federal government’s primary deficits between 2022 and 2052 and projected debt outstanding in 2052. The discount rate for projected cash flows and future debt must include a GDP or market risk premium in recognition of the risk associated with future surpluses. Despite current low interest rates, we find that US fiscal capacity is more limited than commonly thought. Because of the back-loading of projected primary surpluses, the duration of the surplus claim far exceeds the duration of the outstanding Treasury portfolio. This duration mismatch exposes the government to the risk of rising interest rates, which would trigger the need for higher tax revenue or lower spending. Reducing this risk by front-loading primary surpluses requires a major fiscal adjustment. 

   more » « less
2. Using Possible Selves and Intersectionality Theory to Understand Why Students of Color Opt Out of Honors

   Ticknor, C.; Frazier, A.; Williams, J.; Thompson, M. (January 2020, Journal of the National Collegiate Honors Council)

   null (Ed.)

   Abstract: Honors education values diversity, not simply to enrich our classrooms but for equity and social justice. At Columbus State University, students of color were underrepresented in honors education, and we sought to determine if institutional structures hindered them from being able to access educational programming that was commensurate with their ability. We used focus group interviews with students of color who were academically eligible to enroll in honors education yet never participated. We combined focus group interviews with an analysis of our recruiting practices. Using a theoretical framework based on intersectionality and possible selves theory, we found that our participants valued diverse learning environments, balance, and co-curricular engagement that supported their professional, hoped-for selves. However, they perceived honors students as stressed, studious, and lacking leisure time, and they perceived honors education as disconnected from their future professional selves. Since their perceptions, which were informed by participation in advanced programs in middle school and high school, as well as our recruiting practices, were in conflict with their educational aims, our participants were unwilling to invest in honors education. While not generalizable, the results provide unique insights that may implicate institutional practices as barriers to participation because they fail to address the concerns of high-achieving students of color. 

   more » « less
3. Senior undergraduate students developing and envisioning possible selves after graduation

   https://doi.org/10.1119/perc.2021.pr.Khong  

   Khong, Hien; Lohman, B. C.; Foth, Nolan; Sayre, Eleanor C. (September 2021, PERC Proceedings)

   Bennett, Frank (Ed.)

   This study is situated within possible selves theory to explore how senior undergraduate students in STEM develop and envision their future possible selves after graduation. We interviewed students at an urban institution in the US and encouraged them to think about who they will be in the future associated with their future career choices. This study presents two case studies: Ricky and Francisco. These two students discuss a variety of academic contexts through which they negotiate and explore career-related possible selves: conferences, experiences from classes and research, maintained aspirations for science, and dissatisfaction with education from high school. However, we found that in some cases, academic contexts alone are not enough to help students develop future possible selves. Rather, they intersect with social contexts (social identity, out-of-school experiences) through which possible selves emerge. Our findings suggest that students might need more than just classroom-based lessons to explore their possible selves. Implications from this research can benefit the ongoing curriculum development aiming at increasing students’ interests in STEM-related careers and building a meaningful professional life after graduation. 

   more » « less
4. Why Do God and Humans Punish? Perceived Retributivist Punishment Motives Hinge on Views of the True Self

   https://doi.org/10.1177/01461672231160027  

   Lee, Young-eun; Dunlea, James_P; Heiphetz, Larisa (April 2023, Personality and Social Psychology Bulletin)

   Laypeople often believe that God punishes transgressions; however, their inferences about God’s punishment motives remain unclear. We addressed this topic by asking laypeople to indicate why God punishes. We also examined participants’ inferences about why humans punish to contribute to scholarly conversations regarding the extent to which people may anthropomorphize God’s mind. In Studies 1A to 1C, participants viewed God as less retributive than humans. In Study 2, participants expected God (vs. humans) to view humans’ true selves more positively; this difference mediated participants’ views of God as less retributive than humans. Study 3 manipulated agents’ views of humans’ true selves and examined how such information influenced each agent’s perceived motives. Participants viewed a given agent as less retributive when that agent regarded the true self as good (versus bad). These findings extend scholarship on lay theories of punishment motives and highlight links between religious and moral cognition. 

   more » « less
5. Thinking Fast and Slow: Data-Driven Adaptive DeFi Borrow-Lending Protocol

   https://doi.org/10.4230/LIPIcs.AFT.2024.27  

   Bastankhah, Mahsa; Nadkarni, Viraj; Jin, Chi; Kulkarni, Sanjeev; Viswanath, Pramod (January 2024, Schloss Dagstuhl – Leibniz-Zentrum für Informatik)

   Böhme, Rainer; Kiffer, Lucianna (Ed.)

   Decentralized finance (DeFi) borrowing and lending platforms are crucial to the decentralized economy, involving two main participants: lenders who provide assets for interest and borrowers who offer collateral exceeding their debt and pay interest. Collateral volatility necessitates over-collateralization to protect lenders and ensure competitive returns. Traditional DeFi platforms use a fixed interest rate curve based on the utilization rate (the fraction of available assets borrowed) and determine over-collateralization offline through simulations to manage risk. This method doesn't adapt well to dynamic market changes, such as price fluctuations and evolving user needs, often resulting in losses for lenders or borrowers. In this paper, we introduce an adaptive, data-driven protocol for DeFi borrowing and lending. Our approach includes a high-frequency controller that dynamically adjusts interest rates to maintain market stability and competitiveness with external markets. Unlike traditional protocols, which rely on user reactions and often adjust slowly, our controller uses a learning-based algorithm to quickly find optimal interest rates, reducing the opportunity cost for users during periods of misalignment with external rates. Additionally, we use a low-frequency planner that analyzes user behavior to set an optimal over-collateralization ratio, balancing risk reduction with profit maximization over the long term. This dual approach is essential for adaptive markets: the short-term component maintains market stability, preventing exploitation, while the long-term planner optimizes market parameters to enhance profitability and reduce risks. We provide theoretical guarantees on the convergence rates and adversarial robustness of the short-term component and the long-term effectiveness of our protocol. Empirical validation confirms our protocol’s theoretical benefits. 

   more » « less