Splitting Hairs or Splitting Regions: The Differential Democratic Impacts of Splitting ZIP Codes vs. Counties During Redistricting
by Jacob Hervey
Abstract
In light of the Supreme Court’s holding in Gill v. Whitford, judicially-enforceable gerrymandering
metrics must focus on democratic harms to individual citizens, instead
of state-wide measures of proportionality. Previous literature has suggested that gerrymandering
metrics should focus on the extent to which congressional districts split preexisting
geographic boundaries (namely, ZIP codes and counties). This work compares
the differential democratic harms caused by ZIP code versus county splitting during
redistricting across two domains. First, we exploit the changes during the 2010 redistricting
process to construct a difference-in-difference model that captures changes in
voters’ political knowledge as a function of their exposure to geographic splitting. Second,
we predict district-level electoral outcomes from 2002-2018 based upon the extent
of ZIP code and county splitting. Our results indicate that ZIP code and county splitting
cause more significant democratic harms for different outcomes of interest. While
county splitting has more negative consequences for constituents’ political knowledge,
ZIP code splitting is more detrimental with regards to voter turnout.
Dr. Patrick Bayer, Faculty Advisor
Dr. Michelle Connolly, Faculty Advisor
JEL Codes: D72, K16, H11
Intergenerational Economic Transfers and Wealth Inequality in the United States
by Parinay Gupta
Abstract
Using longitudinal data from Panel Study of Income Dynamics (PSID) from 2007-2021, this
paper investigates the role of economic transfers (inheritances and gifts) in asset
accumulation processes of US households, in both short-term and long-term. Analysis is
done through dimensions of race, wealth quartile, and age. Examining quartiles reveals
significant wealth disparities, mirrored in income and education levels. Racially, White
households consistently hold higher wealth, income, and educational levels compared to
Black households, indicating systematic racial disparities. Multivariate analysis uncovers
relationships between socio-economic factors and wealth. Past wealth positively influences
future accumulation, except for the lowest quartile. Labor income negatively impacts wealth,
particularly in lowest quartile, potentially indicating poverty traps and dissaving, while asset
income positively affects quartiles except the lowest, in both short-term and long-term. Total
expenditure initially reduces wealth but reverses in quartiles except the lowest in both time
frames. Race is significantly associated with wealth, with young Black households
consistently disadvantaged, though this reverses for the wealthiest quartile and in longerterm.
Age correlates positively with wealth. Transfers’ (inheritances and gifts) impact varies
across quartiles, showing diminishing returns and switching signs as wealth quartile
increases, indicating differential returns for upper quartiles. Noteworthy is the positive
association between transfers received 8-10 years ago and current wealth, irrespective of age
and wealth quartile, highlighting their significant long-term role in wealth accumulation.
Prof. William Darity, Faculty Advisor
Prof. Michelle Connolly, Faculty Advisor
JEL Classification Numbers: D14, D31, J15
The Sub-proportionality of Subjective Probability Weighting in Poker
by William Clark
Abstract
This study uses Texas Hold’em poker to investigate decision-making under
uncertainty and the concept of probability weighting, where individuals may
overvalue or undervalue uncertain outcomes. I conduct an experiment to assess
Cumulative Prospect Theory’s relevance to subjective probabilities in poker by
simplifying the game to compare complex and simple gamble evaluations. The
research aims to understand how risk preferences and probability estimation
without complete information are influenced by individuals’ poker experience
and framing effects. We find that deviations from what theory predicts in the
subjective-probability Poker frame can be explained well by the framing effects
made in the decision maker’s editing phase. By examining the difference in the
predictive power of decision making models in explicit vs subjective probability
gambles, the study seeks to improve comprehension of cognitive processes in
navigating uncertainty.
Professor Philipp Sadowski, Faculty Advisor
Professor Grace Kim, Faculty Advisor
JEL Classification: C91, D80, D91
The Cost of Delay: Evidence from the Ethereum Transaction Fee Market
by Yinhong “William” Zhao
Abstract
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;
Reconstruction following Destruction: Entrepreneurship in the Aftermath of a Natural Disaster
by Richard Lombardo
Abstract
Entrepreneurship is thought to be the engine of growth in many developing countries. There is, however,
a paucity of evidence on the role that entrepreneurship plays in rebuilding economic livelihoods both in
the short and longer-term in the aftermath of a large-scale shock. This is an important gap in the literature
given the increasing frequency and severity of shocks across the globe. This paper contributes to filling that
gap by investigating the evolution of entrepreneurial success following the 2004 Indian Ocean tsunami, a
large-scale and unexpected shock. Using longitudinal survey data, the Study of the Tsunami Aftermath and
Recovery (STAR), I find large declines in business ownership, profits, and capital for those most exposed
to the tsunami that persisted through 10 years following the tsunami. These estimates can be given a causal
interpretation under the plausible assumption that exposure to the tsunami can be treated as exogenous after
taking into account individual-specific unobserved heterogeneity with fixed effects, including pre-tsunami
geographical features that drove exposure. Individuals living in rural areas and individuals with the least
resources pre-tsunami fared the worst in terms of developing new businesses. However, the massive Build
Back Better reconstruction program promoted entrepreneurship. Receipt of housing aid as part of that
program is linked to an increase in the development of non-agricultural businesses that spurred gains in real
profits.
Duncan Thomas, Faculty Advisor
Michelle Connolly, Faculty Advisor
JEL classification: D1; H84; L26; Q54
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
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
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
Economic Situations and Social Distance: Taxation and Donation
By Alexander Brandt
Abstract:
This experimental study evaluated the effects of two common economic situations –
taxation and donation – on the social distance between participants in the situations, an original
effect of interest that is the opposite of prior research. This study employed a novel survey
framework, in which subjects gave money to others in the economic situations and socially
judged recipients of their money. Findings mostly did not support predictions that the economic
situations would differently affect social distance, but the novel framework enabled an effective
test of the effect of economic situations on social distance and is a major contribution to the field.
Professor Rachel E. Kranton, Faculty Advisor
Professor Scott A. Huettel, Faculty Advisor
Professor Grace Kim, Seminar Advisor
JEL classification: C91; D64; D89; D90
Nonprofit Location, Survival, and Success: A Case Study of El Sistema USA
By Andie Carroll
As nonprofits work to serve their communities, they must choose a place to locate that best suits their needs and the needs of the population they aim to serve. Locational characteristics such as median income and population density have been shown to impact how many nonprofits choose to locate in a given area. However, few studies have examined the impact of locational characteristics on how nonprofits survive and thrive. This study examines the impact of geographic and demographic factors on nonprofit survival and success through a case study of El Sistema USA (ESUSA), a nationwide network of music education programs with the goal of helping underserved youth. The study analyzes panel survey data from 131 El Sistema-inspired programs in the U.S. from 2005 to 2018 along with demographic data from the American Community Survey, charitable giving data from the IRS, and GIS data compiled through a review of ESUSA program websites. By using regression models of ESUSA program survival and success (defined by more students served and higher program budgets), this study found that ESUSA programs in areas of more need are more likely to survive and thrive.
Advisors: Professor Lorrie Schmid, Professor Michelle Connolly | JEL Codes: L3, L31, D23
