By Julia Wu
Many households who would benefit from and are eligible to refinance their mortgages fail to do so. A recent literature has demonstrated a significant degree of heterogeneity in the propensity to refinance across various dimensions, yet much heterogeneity is left unexplained. In this paper, I use a clustering regression to characterize heterogeneity in mortgage refinancing by estimating the distribution of propensities to refinance. A key novelty to my approach is that I do so without relying on borrower characteristics, allowing me to recover the full degree of heterogeneity, rather than simply the extent to which the propensity to refinance varies with a given observable. I then explore the role of both observed and unobserved heterogeneity in group placement by regressing group estimates on a set of demographic characteristics. As a complement to my analysis, I provide evidence from a novel dataset of detailed information on borrower perspectives on mortgage refinancing to paint a more nuanced picture of how household characteristics and behavioral mechanisms play into the decision to refinance. I find a significant degree of heterogeneity in both the average and marginal propensity to refinance across households. While observables such as education, race and income do significantly correlate with group heterogeneity, it is clear that much heterogeneity may still be attributed to the presence of unobservable characteristics.
David Berger, Faculty Advisor
Michelle Connolly, Faculty Advisor
JEL codes: D9, E52, G21
By Bryn Wilson
This thesis contributes to existing knowledge of the private equity asset class by examining whether public-to-private leveraged buyouts outperform public peers before and after the mega-buyout era (2005 – 2007). This paper considers the impact of four groups of value drivers on both market- and peer-adjusted returns. These value drivers include operational improvements, leverage, multiple expansion and market timing, and management and corporate decision making. I analyze how these factors change over time, aiming to determine whether public-to-private target firms improve profitability, return on assets, and investment more than peers. I also examine how employment changes at target firms relative to peers. Multivariable regression analysis is used to quantify the impact of operating performance changes, leverage, multiple expansion, credit market conditions, GDP growth, and management and corporate decisions on market- and peer-adjusted returns. The paper constructs a sample of 227 public-to-private transactions from 1996 – 2013 and analyzes 74 transactions with post-buyout financial information available. Results suggest that private equity ownership post-buyout does not lead to significant operational improvements relative to peers, but that improving profitability and ROA are crucial to outperforming the market and peers.
Dr. Connel Fullenkamp, Faculty Advisor
JEL classification: G3; G34; G32; G11
By Praneeth Kandula
In 2021, modern payment methods such as mobile pay have increased nearly fivefold since their introduction in 2015. This shift to an increasingly cashless, digital economy has been marked by inequitable financial and technological divides. Historically, Black and Latino adults have had less access to financial systems and are less likely to own traditional computers and home broadband. Without rectifying these issues, a cashless, digital economy only serves to widen divides. Using data from the Diary of Consumer Payment, this study descriptively examines the use of cash and alternative payment methods by different racial and ethnic groups from 2015 through 2020. I also extend this effort to address the effects of COVID-19. I find that racial differences not only exist but also the gap between Black and Latino adults and White adults grows between 2015 and 2019. Still, this paper finds that in 2020 the likelihood to employ cash for a transaction falls for Black adults but not for Latino adults. COVID-19 has been a critical driver of change, forcing both consumers and corporations to shift to a more digital-centric economy. While there have been positive shifts for Black adults, policy ensuring that all racial groups have access to the necessary financial and digital networks will be critical in establishing an equitable economy moving forward.
Professor Lisa A. Gennetian, Faculty Advisor
Professor Michelle P. Connolly, Faculty Advisor
JEL Classification: D1 D31 G20 I24 J11
By Nehal Jain
On August 14th, 2014 India’s Prime Minister Narendra Modi implemented the largest ever
financial inclusion scheme to date known as Pradhan Mantri Jan Dhan Yojana (PMJDY). The
program aimed to bank all of India’s unbanked population. Prior to the program, India had one of
the highest rates of unbanked citizens. The program also included measures that prioritized women’s
access to these financial institutions given the gender gap in financial inclusivity. This paper aims
both to understand the effectiveness of PMJDY on granting women equal access as men to financial
institutions and whether financial inclusion results in increased economic empowerment, I find that
PMJDY was successful in increasing access to bank accounts and separately, that access to bank
accounts economically empowers women.
Pengpeng Xiao, Faculty Advisor
Michelle Connolly, Faculty Advisor
JEL classification: J1; G28; I31
By Jacob Epstein
This paper explores the relationship between active mutual fund performance and market dispersion from January 1990 to December 2018. I find a significant positive relationship between dispersion and 4-factor alpha overall, providing some evidence of managerial skill. There are large differences in this relationship by decade and fund selectivity. The results suggest active mutual funds were able to take advantage of stock-picking opportunities during the 1990s and 2000s, particularly the most active subset of funds. However, I find a significant negative relationship between dispersion and alpha for funds in the 2010s, indicating this relationship has changed over time. I discuss several possible explanations for this reversal, which could present interesting avenues for further research.
Advisors: Professor Emma Rasiel | JEL Codes: G1, G12, G23
By Nalini Gupta
This paper seeks to test the hypothesis that developing countries or informationally inefficient countries should see higher returns for active mutual funds on average than passive funds and the trend should be reversed in developed nations or informationally efficient economies. This analysis is done using a cross section of eight countries, four developed and four developing. Using a fund universe of 20 active and 20 passive funds per country and controls such as volatility, market return, financial market development and Human Development Index among others, we see that there is no clear systematically dominant strategy between active and passive investment universally. While developing countries are associated with lower returns, we do not find a significant difference between active and passive based on development classification. A key finding is that an increase in liquidity, acting as proxy for informational efficiency, leads to a co-movement of active and passive returns in each country. The paper also lends itself to further analysis regarding confounding factor such as noise trading and movement of foreign capital which impact the effect of increased liquidity on mutual fund returns.
Advisors: Professor Connel Fullenkamp, Professor Kent Kimbrough | JEL Codes: G1, G11, G14
Forecasting Corporate Bankruptcy: Applying Feature Selection Techniques to the Pre- and Post-Global Financial Crisis Environments
By Parker Levi
I investigate the use of feature selection techniques to forecast corporate bankruptcy in the years before, during and after the global financial crisis. Feature selection is the process of selecting a subset of relevant features for use in model construction. While other empirical bankruptcy studies apply similar techniques, I focus specifically on the effect of the 2007-2009 global financial crisis. I conclude that the set of bankruptcy predictors shifts from accounting variables before the financial crisis to market variables during and after the financial crisis for one-year-ahead forecasts. These findings provide insight into the development of stricter lending standards in the financial markets that occurred as a result of the crisis. My analysis applies the Least Absolute Shrinkage and Selection Operator (LASSO) method as a variable selection technique and Principal Components Analysis (PCA) as a dimensionality reduction technique. In comparing each of these methods, I conclude that LASSO outperforms PCA in terms of prediction accuracy and offers more interpretable results.
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Advisors: Professor Andrew Patton, Professor Michelle Connolly | JEL Codes: G1, G01, G33
Private Equity Buyouts and Strategic Acquisitions: An Analysis of Capital Investment and the Timing of Takeovers in the United States
By Anthony Melita
This paper investigates how motivational differences between agents who execute private equity buyouts and those who execute strategic (corporate) acquisitions may influence the timing of capital investment via takeovers. This paper synthesizes prominent merger theories to inform macroeconomic variables that may drive acquisitions. I find a significant negative expected effect of volatility on capital investment via takeover for each buyer type, a negative expected effect from valuation multiples on capital investment from PE buyouts, and a positive expected effect from debt capacity (EBITDA-CAPEX) on capital investment from PE buyouts.
Advisors: Professor Grace Kim | JEL Codes: G3, G34, G29
By Michael Nicholson
This paper analyzes loan pricing discrimination against predominantly black communities in U.S. mortgage markets. Building on previous literature, this paper posits that ceteris paribus predominantly black communities continue to face economically significant discrimination in mortgage pricing. Ultimately, this paper concludes that predominantly black communities face 10-14 basis points of pricing discrimination in mortgage loans which corresponds to 12.6-17.6% higher rate spreads. This estimation comes after accounting for geographic and lender effects, borrower quality, tract-level characteristics, and loan type. These results confirm past findings of pricing discrimination and illustrate yet another financial barrier for black households in this country.
Advisors: Professor Emma Rasiel, Professor Kent Kimbrough | JEL Codes: R2, J15, G21
By Peter Noonan
This thesis analyzes factors that determine acquisition premiums paid by private equity firms in public to private leveraged buyouts. Building off of established literature that models the acquisition premiums paid in corporate mergers and acquisitions (M&A), this paper considers factors that influence a private equity firm’s willingness to pay (referred to as reservation price) and the bargaining power dynamic between a target company and acquirer in leveraged buyouts. Specifically, multivariable regression analysis is used to quantify the impact of a target company’s trading multiple, profitability, stock price as a percentage of its annual high, and number of competitors, a private equity firm’s deal approach and payment method, and the financial market’s 10-year US Treasury yield and high-yield interest rates at the time a transaction was announced. A sample of 320 public to private leveraged buyout transactions completed from 2000 to 2020 is constructed to perform this paper’s regression analysis. Using 2008 as an inflection point, this thesis then applies the same regression model to the subperiods from 2000–2008 and from 2009–2020 to examine how these drivers have changed as a result of industry trends—increased competition, low interest rates, and new value creation investment strategies—as well as the 2008 financial crisis and US presidential election—two crucial events that caused tremendous change in the financial system and intense scrutiny of the private equity industry. From the same original transaction screen, a second sample of 659 transactions is used to perform a difference of acquisition premium means t-test to analyze how the absolute magnitude of leverage buyout acquisition premiums have changed across these two subperiods. The second sample consists of more transactions due the t-tests less data-demanding nature as a result of its fewer variables. Results of this paper’s baseline model suggest that acquisition premiums are driven by a target company’s…
Advisors: Professor Ronald Leven, Professor Michelle Connolly | JEL Codes: G3, G11, G34