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Heterogeneity in Mortgage Refinancing
By Julia Wu
Abstract
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
After The Mega-Buyout Era: Do Public-to-Private Transactions Still Outperform?
By Bryn Wilson
Abstract
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
Analysis of the Impact of Gender and Age of Protagonists in Top-Grossing Films from 2000-2019 on Film Success
By Daniella Welton
Abstract
The gender wage gap is prominent in many fields of work, but it is especially prevalent among actors in the film industry. According to the U.S. Department of Labor, as of 2019 female annual workers were earning about 82.3% of their male counterparts. In a study of feature films released from 1980 to 2015, females were making only 56% of their male counterparts on average; this gap also has been shown to increase as female actors get older (Blau & Kahn, 2017; De Pater et al., 2014; Izquierdo Sanchez & Navarro Paniagua, 2017). In this paper I investigate the relationship between the gender and age of protagonists in the film industry and film success through a series of three regressions with film success defined as film total gross, critic reviews, and audience reviews. My data set is composed of 100 top-grossing films from each year 2000-2019. Through my statistical analysis I did not find any evidence that the gender or age of the protagonist influences film success. Thus my results do not show any evidence that the gender wage gap could be related to differences in film success.
Professor Genna Miller, Faculty Advisor
Professor Kent Kimbrough, Seminar Advisor
JEL Codes: J16, J30, J70, J71
Impact of Utility-Scale Solar Farms on Property Values in North Carolina
By Megan Wang
Abstract
The aim of this paper is to investigate impacts of utility-scale solar farms on surrounding property values. Using data from CoreLogic, the Energy Information Administration (EIA), and the US Census Bureau, this study identifies a 12% statistically significant increase in sale values associated with high-income residential homes within three miles of a solar farm. However, low-income homes built near solar farms are associated with a -1.4% decrease in sale values.
As North Carolina continues to expand solar energy, specifically through photovoltaic utilities, understanding the impact of solar development on surrounding communities should be a priority and policies should aim to prevent property devaluations in low-income neighborhoods caused by solar farms.
Dr. Christopher Timmins, Faculty Advisor
JEL Classification: Q42, R11
The Effect of Workforce Participation and Household Income Contribution on Women’s Healthcare Empowerment in Rural Bangladesh
By Hannah Wang
Abstract
Women in Bangladesh have gained increased access to paid work in the past decade yet
still experience limited choices and access to resources, which threatens their ability to exercise
control over healthcare for themselves and their children. Several collective household
bargaining theories hypothesize a link between women’s workforce participation and
empowerment. This paper uses a cross-sectional approach and survey data collected at the end of
a randomized trial field experiment in rural Bangladesh from 2007 to 2017 to examine health
empowerment outcomes for 7,151 young women ages 14 to 32. The results show that women
who work for income are expected to be more health empowered, specifically due to an
increased ability to make their own health decisions. As a woman contributes more income to her
household, her health empowerment is expected to increase, through increased abilities to make
her own health decisions, purchase medicine for herself, and seek medical treatment
independently. Greater mobility and stronger female-positive attitudes towards gender norms are
potential mechanisms through which paid work and household income contribution can translate
into health empowerment. Furthermore, higher total household income, having children, and
being more educated than her husband are expected to increase a woman’s health empowerment.
These results are significant while controlling for the effects of various individual and household
characteristics.
Professor Erica M. Field, Faculty Advisor
Professor Michelle P. Connolly, Faculty Advisor
JEL classification: J1; J16; I15
Short and Long-Term Impacts of a Large-Scale Natural Disaster on Individual Labor Outcomes: Evidence from the 2004 Indian Ocean Tsunami
By Tony sun
Abstract
Natural disasters are often highly disruptive to the livelihoods of impacted populations. This paper investigates the effects of the 2004 Indian Ocean tsunami on male wages and labor supply from its immediate aftermath into the long run. Using fixed effects models that account for individual-specific heterogeneity, I find evidence of significant real wage declines for workers from heavily damaged areas that persist beyond the short-term. This long-term wage effect contrasts with previous literature, particularly in the context of relatively less severe disasters. Male workers also increased their hours-of-work following the tsunami, which suggests reliance on labor markets to smooth income losses and shifted their labor towards less disrupted industries. Additionally, I document the heterogeneity of tsunami impact on wages and hours-of-work by birth cohort and education, as well as by industry and sector of employment.
Professor Duncan Thomas, Faculty Advisor
Professor Michelle P. Connolly, Honors Seminar Instructor
JEL classification: J2; J21; J30; O10; Q54
Peer Effects & Differential Attrition: Evidence from Tennessee’s Project STAR
By Sanjay Satish
Abstract
This paper explores the effects of attrition on student development in early education.
It aims to provide evidence that student departure in elementary schools has educational
impacts on the students they leave behind. Utilizing data from Tennessee’s Project STAR
experiment, this paper aims to expand upon the literature of peer effects, as well as attrition,
in public elementary schools. It departs from previous papers by utilizing survival analysis to
determine which characteristics of students prolonged participation in the experiment. Clustering
analysis is subsequently employed to group departed students to better understand
the various channels of attrition present in STAR. It finds that students who left Project
STAR were more likely to be of lower income and lower ability than their peers. This paper
then uses these findings to estimate the peer effects of attrition on students who remained
in the experiment and undertakes a discussion of potential sources of bias in this estimation
and their effects on the explanatory power of peer effects estimates.
Professor Robert Garlick, Faculty Advisor
Professor Michelle Connolly, Faculty Advisor
JEL Classification: I, I21, I26, H4, J13
The Case for Clemency: Differential Impacts of Pretrial Detention on Case and Crime Outcomes
By George Rateb
Abstract
About half-million of individuals in US jails are detained pretrial while legally presumed
innocent. Using data on quasi-randomly assigned bail judges in the third-largest court system in
the U.S., we study the impact of pretrial detention on defendants’ court and crime outcomes
between 2008 and 2012. We supplement our primary analysis to document patterns on bail
amounts and how they differentially impact Black defendants relative to their white and Hispanic
counterparts. Instrumental variable estimates suggest that pretrial detention increases the
likelihood of being found guilty, mainly driven by the uptake of guilty pleas, especially for
minorities. By linking court and jail data, we provide mechanistic evidence that jail time is
positively correlated with the uptake of these guilty pleas. To the best of our knowledge, these
findings have not been empirically documented due to a lack of previous data availability.
Professor Bocar Ba, Faculty Advisor
Professor Michelle Connolly, Faculty Advisor
JEL classification: C26; J15; K14
A perfect storm: The effect of natural disasters on child health
By Cheyenne Danielle Quijano
Abstract
Typhoons and their accompanying flooding have destructive effects, including an
increase in the risk of waterborne disease in children. Using a spatial regression discontinuity
design, I explore the immediate to short-term effects of flooding as a result
of Typhoon Labuyo on the incidence of diarrhea and acute respiratory infection in the
Philippines by comparing children living in a flooded barangay (town) to children living
just outside of the flooded area. I build on the existing literature by accounting for
both incidence and intensity of the typhoon’s flooding in my model. I construct this
new flooding measure using programming techniques and ArcGIS by manipulating data
collected by the University of Maryland’s Global Flood Monitoring System. This data
as well as health data from the 2013 Philippines National Demographic Health Surveys
were collected the day after Typhoon Labuyo left the Philippines, providing a unique
opportunity to explore the immediate impact of the typhoon on child health. Most of
my results are insignificant, but subgroup analyses show that the effect of flooding on
waterborne disease incidence is less impactful in the immediate term following a flood
and more impactful in the medium-term. This is important, because understanding
the detrimental health effects of flooding is of utmost importance, especially because
climate change will only increase the frequency and intensity of natural disasters.
Professor Erica M. Field, Faculty Advisor
Professor Michelle P. Connolly, Faculty Advisor
JEL classification: I150, O120, O130, Q540
Tale of Two Cities An Econometric Analysis of East & West Coast Fine Art Galleries
By Daniella Victoria Paretti
Abstract
In a 2021 report published alongside Art Basel and UBS, renowned cultural economist Dr.
Clare McAndrew posited that the value of art sales in 2020 amounted to an impressive $50 billion
(although this actually marks an over 10-year low). It is no secret that the global art markets are
extremely lucrative, attracting the interest of industry magnates and business tycoons alike.
Though it is important to note that art markets are historically quite distinct from their normal good
counterparts — the sector is laden with issues regarding transparency, high barriers to entry, and
hiding of wealth. Amidst the COVID-19 pandemic, however, the tides began to turn; online
platforms for museums, auction houses, and galleries were employed more than ever before,
effectively modernizing the antiquated industry and expanding its reach to new consumers. How
has this trend of digitalization changed and improved art markets? More specifically, how can data
analytics and other technological resources serve the interests of private galleries? Using sales data
from a parent gallery with multiple locations across the United States (each displaying similar
works/artists), I have conducted a number of qualitative and statistical analyses to identify key
differences between the West and East coast locations. In short, the gallery on the West coast sold
more works and at a lower average cost than its counterpart, providing key insights into this local
market’s consumer base. Beyond this, factors like size, medium, and artist gender were found to
have statistically significant effects on the ultimate sale price and turnover rate of works. My
findings suggest that means of data analytics should be utilized by all actors in the art markets to
optimize their approach to business, as well as understand their consumers better than ever before.
Professor Michelle Connolly, Faculty Advisor
Professor Hans Van Miegroet, Faculty Advisor
JEL classification: Z11, C10, J11, O33
