Bias in Fact Checking?: An Analysis of Partisan Trends Using PolitiFact Data
by Thomas A. Colicchio
Abstract
Fact checking is one of many tools that journalists use to combat the spread of fake news in American politics. Like much of the mainstream media, fact checkers have been criticized as having a left-wing bias. The efficacy of fact checking as a tool for promoting honesty in public discourse is dependent upon the American public’s belief that fact checkers are in fact objective arbiters. In this way, discovering whether this partisan bias is real or simply perceived is essential to directing how fact checkers, and perhaps the mainstream media at large, can work to regain the trust of many on the right. This paper uses data from PolitiFact, one of the most prominent fact checking websites, to analyze whether or not this bias exists. Prior research has shown that there is a selection bias toward fact checking Republicans more often and that they on average receive worse ratings. However, few have examined whether this differential treatment can be attributed to partisan bias. While it is not readily apparent how partisan bias can be objectively measured, this paper develops and tests some novel strategies that seek to answer this question. I find that among PolitiFact’s most prolific fact checkers there is a heterogeneity in their relative ratings of Democrats and Republicans that may suggest the presence of partisanship.
Peter Arcidiacono, Faculty Advisor
Michelle Connolly, Faculty Advisor
JEL codes: D83, D84, L82
Shades of Green: An Examination Into Second Party ESG Ratings In The Municipal Green Bond Market
by Harrison Zane Cole
Abstract
Since the end of the pandemic the market capitalization of green bonds and investor interest in sustainable investments has grown massively. The tidal wave of ESG funds has accompanied many claims of greenwashing and extreme variation in investment quality. While many investors focus on doing their own due diligence, second party ratings are an important source of information for capturing overall risk and characteristics of a security. This paper aims to take a deeper look at how HIP Investor’s (a popular ESG rating firm) ratings correlate to real-world yield and bond characteristics. Yield refers to the annualized return that investors receive from a bond, and lower yields at issuance reduce borrowing costs for the issuer. It is generally established in popular and academic literature that green bond designation does not directly lead to a benefit for issuers in terms of their cost of capital expressed through interest rates. This paper examines the yield at issuance effects for degrees of “actual greenness” and other inputs that may lead to a security to fit well in an ESG focused or impact fund. Within a sample of green bonds, the estimated yield to worst spread premium for a best-in-class (environmentally) ESG issuer is -23.9 basis points compared to a worst-in-class issuer holding all else equal. When considering non-environmental factors such as human health, the effect is larger at -71.4 basis points. For social wealth considerations, the directionality is reversed at 17.9 basis points. More research is needed to better understand and apply these results. This decrease in interest rates can result in millions of dollars of savings for larger issuances.
Lawrence Kreicher, Faculty Advisor
Michelle Connolly, Faculty Advisor
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
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
Withdrawal: The Difficulty of Transitioning to a Cashless Economy
By Praneeth Kandula
Abstract
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
