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Impact of Medicare Advantage Supplemental Benefit Expansion on Startup Funding

by Judy Tianhong Zhong


In 2018, the Center for Medicare and Medicaid Services (CMS) announced that they would expand the supplemental benefits that can be included in Medicare Advantage (MA) plans. The goal was to encourage insurers to innovate and test new benefit offerings that could improve health outcomes and reduce healthcare spending. A key player in this transformation is the MA vendor that provides supplemental benefit offerings to insurance plans, but this market is rather underdeveloped. To assess the implementation of this supplemental benefit expansion, this study examines the flow of funding into the emerging market of MA vendors. This paper uses a longitudinal approach and Crunchbase data on funding for 79,004 firms from 2014 to 2018 to determine whether there is a significant jump in funding toward MA vendors with supplemental benefit services following the policy change. The results show that both the average amount of funding per deal and the number of deals a MA vendor firm receives significantly increased following the expansion when compared with all other firms. This suggests that the policy may have been successful in promoting the development of the MA vendors market and the innovation of benefit offerings as more funding goes towards these companies.

Kate Bundorf, Faculty Advisor
David Ridley, Faculty Advisor
Michelle Connolly, Faculty Advisor

JEL classification: I1; I11; I18

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Technological Impacts on Return to Education in Brazil

by Yirui Zhao


The wage return to education has been studied for a long time. Acemoglu and Autor (2010) connect the decrease of medium-level job opportunities in the U.S. with technological advances. Their theoretical model predicts that if technology replaces routine jobs, workers with medium-level skills will experience decreases in wages relative to both high-skill workers (who become more productive with the improved technology) and low-skill workers (who can less easily be replaced since their work is not routine). Moreover, their theoretical model predicts that if medium-skill workers are closer substitutes for low-skill workers than they are for high-skill workers, the relative return of high-skill workers to low-skill workers should increase. Using education as proxy of skill (Acemoglu & Autor, 2012), this paper checks if these three predictions about relative wage returns to education also hold in Brazil. This paper finds that the impact of technological change on the Brazilian formal labor market between 1986 and 2010 is consistent with predicted changes in the return to education for medium-skill workers relative to both low and high skill workers. The impact is consistent with predicted changes in the return to education for high-skill workers relative to low-skill workers when Lula’s presidency is considered in the model.

Michelle Connolly, Faculty Advisor
Rafael Dix-Carneiro, Faculty Advisor
Daniel Xu, Faculty Advisor

JEL classification: J24; J31; O33

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The Cost of Delay: Evidence from the Ethereum Transaction Fee Market

by Yinhong “William” Zhao


Delaying a financial transaction can be costly, but the cost of delay is difficult to estimate in traditional
finance. I exploit the unique data offering and market design of the Ethereum blockchain to estimate the
cost of delaying financial transactions in decentralized finance (DeFi). I construct a dynamic auction
model for the Ethereum transaction fee market that relates users’ optimal transaction fee bids to their delay
cost functions and network conditions, and I structurally estimate the delay cost functions for different
users and transaction types. The average cost of delaying a transaction by one minute is 8.78 US dollars,
but the distribution of delay costs is highly skewed to the right. Delay costs are higher for complex
transactions and users who trade more frequently. I estimate that welfare loss due to network delay on
Ethereum was 14.03 million US dollars per day in July 2021, and I apply the delay cost estimates to
evaluate the welfare losses under alternative transaction fee mechanisms.

Campbell Harvey, Faculty Advisor
Michelle Connolly, Faculty Advisor

JEL Codes: D44; G10; L17;

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Determinants of Sustained Success in NFT Markets

by Emily Xu


Non-Fungible Tokens (NFTs) took headlines by storm in 2021 and have since established their own marketplace. As public interest in the space wanes in 2022-2023, I characterize this emerging space and investigate factors that distinguish top-performing NFT projects within their respective market segments while controlling for external market and cryptocurrency exposures. Literature in this emerging space remains sparse and I contribute in the following ways: 1) My cross-sectional time series panel synthesizes the most recent data from February 2022 to March 2023, utilizing information from five platforms (NonFungible.com, Twitter, OpenSea, ArtIndex, YahooFinance). To the best of my knowledge, this is the first holistic dataset that combines time-varying secondary sales data, Twitter, and market data. 2) My analysis categorizes data points by both NFT market segments and secondary sales performance, allowing for finer comparison between top and low performers within their respective categories. I find that a change in Twitter followers and tweets over time is a statistically significant and positive predictor of secondary sales, indicating that top-performing NFT projects must consistently add value and market to investors in order to generate sustained secondary sales. Additionally, top-performers saturate the space at incredibly high speeds and grand scales. For instance, the median top-performing collectible project has a collection of 10,000 items, attracted at least 60,000 Twitter followers, and achieved over $42 million in total sales, all within 1-2 years of the “NFT hype.” This concludes that royalties generated from NFTs are not passive, requiring creators to be reactive and consistent in their efforts.

Michelle Connolly, Faculty and Seminar Advisor
Professor Connel Fullenkamp, Faculty Advisor

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Illuminating the Economic Costs of Conflict: A Night Light Analysis of the Sri Lankan Civil War

by Nicholas Kiran Wijesekera


This paper investigates the economic consequences of the Sri Lankan Civil War (1983-2009) by using event-based data on civilian and combatant fatalities in addition to night light imagery as a proxy for economic activity. By looking at regional economic activity across the island of Sri Lanka, this paper
seeks to identify how violence led to declines or undershoots of economic activity in the areas in which it was most prevalent. The use of night light data gives a
hyper-localized proxy measurement of this activity for each year of the war. The investigation finds that government and rebel deaths have strong, negative effects on economic activity, and that these effects spill over across time and space. Additionally, the manner in which civilian deaths occur is an important determinant of their subsequent economic impact. The paper offers new findings on the economic legacy of the Sri Lankan Civil War and extends existing work on the use of night light data to measure economic activity during conflict.

Charles Becker, Faculty Advisor
Michelle Connolly, Faculty Advisor

JEL Codes: H56, N45, O53

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The True Cost: An Aggregate Analysis of the Advanced Clean Cars II Policy

by Lauren Mackenzie Sizemore


Global climate change, emphasis on the global, requires local solutions. Every entity plays a role, some more than others. Yet, when improvements in pollution or emissions in one region leads to more problems in another, how is the net cost or benefit to be deciphered for the environment, for the economy, and for humanity in general? Advanced Clean Cars II (ACC II), a proposed policy in California, United States, is a practical test of this question. For each model year beginning in 2026, the potential law gives a percentage of new vehicle sales that must be zero-emission vehicles (ZEVs) – cars that do not emit exhaust gas or other pollutants from the onboard source of power – or plug-in-hybrid electric vehicles (PHEVs). By 2035, ACC II would require all new vehicles purchased in California to be either a ZEV or a PHEV. With reduced tailpipe emissions, California expects to benefit from reduced smog, less carbon emissions, better air quality, a reduction in air-related health issues such as asthma, and increased sales from California-based electric vehicle companies such as Tesla and Rivian. Since air is a common resource, improving California’s quality also betters air globally. Yet emissions and pollution produced during the mining, production, and scrappage phases work in opposition to the decreased tailpipe emissions. By converting each type of pollutant into a per vehicle dollar cost, I paint a better picture of the global cost-benefit. The per vehicle cost is scaled based on the expected number of electric and conventional vehicles in California which is predicted under two scenarios: ACC II passes with full enforcement and the law is not passed. I forecast the number of electric vehicles likely bought in both instances using the Bass Model for New Product Growth of Consumer Durables (Bass 1969). I determine that a maximum of eighteen states, including California, could successfully implement ACC II and lower emissions given their 2021 electricity grid’s carbon intensity.

Connel Fullenkamp, Faculty Advisor
Michelle Connolly, Faculty Advisor

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Student Effort and Parent Attitude on Education Attainment: Evidence from Multi-year Survey in Gansu, China

by Ridge Zhong-yuan Ren


This paper explores whether student effort and parent attitudes have varying effects at different stages of a student’s life in terms of educational attainment and job outcomes. With survey data in Gansu, China, a largely rural province in Northwest China that lags behind the rest of China in education, this paper employs a multivariate regression model. This method allows me to measure the achievement or outcome of the child between each successive wave of surveys and estimate which factors held the strongest effect on the next wave. Student achievement in early waves is measured by the student’s score on assessments in math and Chinese, and the later outcome is measured by the student’s income and the highest level of education achieved. This paper finds that effort in Math and math achievement have a positive association with better education attainment and career outcomes later in life. In addition, I find that parental education levels also have a positive association with child outcomes.

Pengpeng Xiao, Faculty Advisor
Kent P. Kimbrough, Faculty Advisor

JEL Codes: I25, I26

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Short Term Effectiveness of Chinese Stock Connect Program — a Study of the Pricing Dynamics of Cross-listed Stocks

by Kaiyu Ren


This thesis examines the pricing dynamics of cross-listed stocks in the Chinese A-share and
Hong Kong H-share markets. By identifying an announcement-implementation window, I offer a
fresh perspective on the short-term price adjustment of cross-listed stocks around the launch of
the first Stock Connect program. My findings reveal a significant increase of the A-H price ratio,
but this price discrepancy appears to have been mitigated by the implementation of the Stock
Connect program.Additionally, my observations suggest the existence of market inefficiencies,
particularly among the groups of A-share stocks that are excluded from the Stock Connect

Ronald Leven, Faculty Advisor

JEL codes: G14; G18

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Price Determinants and Depreciation of Used Cars Post-COVID-19

by Ayaan Sundeep Patel


Throughout the COVID-19 pandemic, the price of used cars has fluctuated greatly due to
numerous factors. Inflation and supply chain issues have been at the forefront of the news and
have affected not only cars but most consumer goods. While the majority of society has
seemingly progressed past COVID-19, its effects still linger in the used car market, as prices rose
4.6% from January 2023 to February 2023. Therefore, in an effort to study this phenomenon, I
scraped data from autotrader.co.uk on February 23, 2023. This study aims to understand the
effect of various factors, including mileage, age, and engine size, on various classes of used cars.
The five classes being studied are compact cars, luxury sports sedans, luxury mid-size sedans,
luxury full-size sedans, and luxury SUVs. A log-linear model is used to model the price
determinants of the used cars. A linear model is incorporated to model the depreciation rate of
the cars in the dataset. Lastly, this model is used to predict the three-year depreciation rate for
each car model, which is then compared to the pre-COVID-19 three-year depreciation rate to see
the inflated prices in the UK used car market.

Michelle Connolly, Ph.D., Faculty Advisor
Andrea Lanteri, Ph.D., Faculty Advisor

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Improving Institutional Performance: Foreign Aid Evaluation and Determinants of Foreign Aid Project Success Ratings

by Susan Sawyer O’Keefe


In this paper, I use a regression model to predict project outcome ratings for international aid
projects by 12 multilateral and bilateral aid agencies taking place in 183 recipient countries. The
influential factors considered are project duration, project size, evaluation type, evaluation lag, donor
ratings, and country-level indicators of development. I find a significant relationship supporting
differences in project outcome ratings for projects evaluated by an independent evaluation agency, a
resource that some banks use to access project performance by an unbiased party. I also examine the
significance of other project-level factors and compare these to trends identified in past literature on
foreign aid project effectiveness.

Michelle Connolly, Faculty Advisor

JEL classification: H43, O22

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Undergraduate Program Assistant
Matthew Eggleston

Director of the Honors Program
Michelle P. Connolly