Fact or Fluff: Does Wording Used by Gene Editing Companies Affect Investor Behaviors?
by Thomas Freireich
Abstract
The writing style a startup uses to portray itself has an impact on investors’ perceptions of them, subsequently affecting their venture capital decisions. This funding is particularly important given the prominence of venture capital as a primary financial source for growing early-stage biotechnology companies. Currently, due to recent scientific advances, many of these startup companies are utilizing novel gene editing based approaches to cure a variety of previously untreated diseases. For the sake of those affected, it is essential that this sector of the biotechnology industry is managed properly early on so that developed treatments can eventually reach FDA approval. This paper is in part inspired by recent happenings revolving around the fraudulent biotech startup, Theranos. Elizabeth Holmes, Theranos’ founder, was renowned for making comments lauding the company’s product. It seemed to many that investors were lulled by the idea of what Holmes made Theranos to be, invested in the company based on false verbal promises instead of the reality of the scientific product. Occurrences like the demise of Theranos are detrimental to both investors and competing companies in need of venture funds in order to develop their treatments. Thus, this paper explores the impact of word-usage and writing style on venture capital investment in various gene editing based startups,hoping to elucidate whether investors are being swayed by word choice.
Professor Michelle Connolly, Faculty Advisor
JEL Codes: M1, M13, O3, O32
The Effect of Sustainability Reporting on ESG Ratings
by Arthur Luetkemeyer
Abstract
Over the past decade the concept of Environmental, Social, and Governance (ESG) investing has
emerged to aid investors to maximize return on investments while simultaneously supporting
environmentally and socially friendly methods of production and operation. In this paper I
investigate the effect of the quality of sustainability reporting on ESG ratings. I utilize a sample
of 100 chemical companies with ESG ratings and sustainability disclosure indexes over a 14-
year time period (2007-2020) to analyze the short- and long run effects of sustainability reporting
on ESG ratings. Using OLS my regression results suggest that better overall ESG disclosure as
well as individual E, S, and G disclosure leads to worse ESG ratings in both the short run and the
long run.
Professor Christopher Timmins, Faculty Advisor
Professor Grace Kim, Faculty Advisor
JEL Codes: M14, M40
Bang for Your (Green) Buck: The Effects of ESG Risk on US M&A Performance
by Richard Chen
Abstract
Mergers & Acquisitions (M&A) is a fundamental corporate activity that has not received much attention from an environmental, social, and governance (ESG) perspective. In this paper, I analyze how buyer and target ESG risks affect US M&A performance in both the short and long run as measured by deal valuations and changes in buyer operating metrics, respectively. I utilize a sample of 341 transactions from 2007-2020 with a cumulative value over $3 trillion from Capital IQ where both the buyer and target have available ESG data provided by RepRisk. Utilizing OLS, my results suggest that higher ESG risk causes buyers to pay more and targets to receive less. In the long run, buyer ESG risk is an important determinant of performance. When examining the components of ESG, governance is the most consistently significant, followed by social, then environmental – though it becomes more significant in the long run. Additionally, all three components appear to have some non-linear impacts on M&A performance.
Professor Connel Fullenkamp, Faculty Advisor
Professor Grace Kim, Faculty Advisor
JEL Codes: G34, G14, M14
Incentives to Quit in Men’s Professional Tennis: An Empirical Test of Tournament Theory
By Will Walker
This paper studies the influence of incentives on quitting behaviors in professional men’s tennis tournaments and offers broader implications to pay structures in the labor market. Precedent literature established that prize incentives and skill heterogeneity can impact player effort exertion. Prize incentives include prize money and indirect financial rewards (ranking points). Players may also exert less effort when there is a significant difference in skill between the match favorite and the match underdog. Results warrant three important conclusions. First, prize incentives (particularly prize money) do influence a player’s likelihood of quitting. Results on skill heterogeneity are less conclusive, though being the “match favorite” could reduce the odds of quitting. Finally, match underdogs and “unseeded” players may be especially susceptible to the influence of prize incentives when considering whether to quit.
Advisors: Peter Arcidiacono and Grace Kim | JEL Codes: J41, J31, J32, J33, M12, M51, M52
The Comprehensive Optimal Business Location Model
By Mitchel Gorecki
In order to ensure long run viability, a firm must understand the idea of optimal business location. In the designing of a strategy, it is important to not only evaluate the present market environment but to also account for possible future change. This paper will demonstrate the core ideas behind a comprehensive location model that will predict the optimal location for a business. The effectiveness of the model will be evaluated by using past data from Durham, North Carolina to predict current retail development. The model is determined to be successful by seeing if the trend recognized would be able to correctly identify the present location choices of firms. The model will be further used to predict the future development plans for businesses locating in the Durham area.
Advisor: Charles Becker | JEL Codes: E3, M1, M2,
Measuring the Likelihood of Small Business Loan Default: Community Development Financial Institutions (CDFIs) and the use of Credit-Scoring to Minimize Default Risk1
By Andrea Coravos
Community development financial institutions (CDFIs) provide financial services to underserved markets and populations. Using small business loan portfolio data from a national CDFI, this paper identifies the specific borrower, lender, and loan characteristics and changes in economic conditions that increase the likelihood of default. These results lay the foundation for an in-house credit-scoring model, which could decrease the CDFI’s underwriting costs while maintaining their social mission. Credit-scoring models help CDFIs quantify their risk, which often allows them to extend more credit in the small business community.*
Advisor: Charles Becker | JEL Codes: K22, M1,
