Economic Perception and Cable News: Evidence from Panel Data, 2016–2020
by Audrey S. Wang
Abstract
This paper employs a panel approach to investigate the role of partisan cable news in shaping economic perceptions using the VOTER Survey dataset (2016–2020) and sentiment-scored transcripts from Fox News, CNN and MSNBC, examining how sentiment and coverage intensity interact with individuals’ viewership patterns to affect macroeconomic assessments. Findings suggest changes in exposure to cable news affects viewers’ economic perceptions, with effects varying by network, viewership patterns, time horizon and primetime exposure. Fox News exhibits particularly polarizing influence, with positive shifts in exposure improving economic outlooks among its viewers while worsening perceptions among non-viewers. Effects are moderated when individuals do not exclusively watch Fox News, suggesting a countervailing effect to watching multiple, ideologically diverse channels. Strikingly, non-primetime exposure to Fox’s coverage is more consistently associated with shifts in sentiment than primetime exposure, even among non-viewers — indicating that lower-profile programming may diffuse more broadly into the ambient media environment. In contrast, CNN’s economic coverage shows limited or short-lived influence, and MSNBC’s effects are more time-sensitive and contingent on viewership. These findings underscore the persistent influence of cable news in shaping public economic perceptions and suggest that media effects are not uniform across formats or audiences.
Professor Michelle Connolly, Faculty Advisor
Professor Bocar Ba, Faculty Advisor
JEL Codes: L8, L82
Keywords: Cable news; Consumer sentiment; Sentiment analysis
Reel Representation: The Economic Impact of Gender on Bollywood Box Office Revenue
by Sidharth Ravi
Abstract
The Hindi Film Industry, known as Bollywood, is seen as a gatekeeper of Indian culture.
Annually thousands of films are produced, half a million workers across India are
employed and millions in revenue is created. Although Bollywood has ensured increased
employment and wage opportunities for women on and off screen, the overall
representation of women remains severely low. Little is known about their impact on
Bollywood’s film revenue. This study uses a novel dataset to estimate the impact of
female representation on Bollywood revenue from 2009-2019. We apply a traditional
linear regression and use a ratio of female to male characters in a film’s cast as a proxy
for female representation. Results indicate there is not a significant relationship between
an increased female cast composition on box office performance. To check for the diverse
impact of star power, I analyzed the gender makeup of the movie star in a film, finding
this to have a significant impact on box office revenue. In addition, there is a significant
effect of production budgets and genre on box office performance.
Professor Genna Miller, Faculty Advisor
Professor Grace Kim, Seminar Advisor
JEL Codes: L820, F63, J16, Z11
Keywords: Film Economics, Bollywood, Gender, Female Representation
Externalities of Overhead Power Lines on Residential Housing Values
by Jake Park-Walters
Abstract
Overhead electricity transmission lines (OHLs) create negative externalities on nearby housing values largely from perceived factors including aesthetics, safety, and health. Studies have been performed outside of the US to determine the specific value impact of power lines by proximity. It is not, however, well researched within the United States–specifically in suburban and urban areas. To assess the value loss from overhead power lines, this study examines housing transactions in North Carolina from 1997 to 2020 with a particular emphasis upon cities and townships. With GIS software, proximity variables are calculated such that a difference-indifference regression can estimate the impact of distance to OHL on transaction values. This is important for local policy regarding whether municipalities may want to invest into burying power lines as a means of improving local property values. The results attempt to illustrate how burying high impact lines (HILs) can generate high public benefit relative to cost through marginal value of public funds (MVPF) calculations. These HILs may be chosen based on a variety of factors including proximity to dense, high value housing to maximize value improvement by burial.
Professor David Berger, Faculty Advisor
Professor Michelle Connolly, Faculty Advisor
JEL Codes: L94, H76, D04
Keywords: Electric Utilities, Policy Evaluation, Local Government Expenditure
Email for Access to Data
The Impact of Quiet Zone Implementation on Accident Incidence at Highway-rail Grade Crossings
by Jack Duhon
Abstract
In the last five years, (2019-2023) there have been 10,704 accidents
at highway-rail grade crossings (HRGCs) in the United States, resulting
in 3,859 injuries and 1,233 fatalities. This paper seeks to address impact
of quiet zones, where trains are not allowed to blow their horns before
going through a crossing, on HRGC safety in the United States. Using
a two-way fixed effects model, we find evidence of quiet zones increasing
accident incidence and accident severity, in some instances at a level far
higher than believed by the Federal Railroad Administration.
Professor Jeff DeSimone, Faculty Advisor
Professor Grace Kim, Faculty Advisor
JEL Codes: L92; L98; R41
Keywords: Accident, Railroad, Quiet Zone
Email for Access to Data
RadioWaves and Ballot Boxes: How Conservative Broadcasting Influenced Southern Electoral Behavior
by Ian Carlson Bailey
Abstract
This study examines how conservative talk radio influenced electoral behavior in the American South during the postwar era. Focusing on Carl McIntire’s “Twentieth Century Reformation Hour” program, I exploit exogenous variation in radio signal strength driven by topographical differences to identify causal effects on voting patterns. Using a novel dataset combining archival records with technical broadcasting data, I find that exposure to McIntire’s broadcasts significantly reduced support for Democratic presidential candidate John F. Kennedy in the 1960 election by 1.4 percentage points while increasing Republican candidate Richard Nixon’s vote share by 0.9 percentage points, with negligible effects on voter turnout. These effects were strongest in counties with the lowest proportions of Protestant residents, suggesting a ceiling effect in areas already predisposed toward conservatism. Furthermore, exposure to McIntire’s program increased the probability Democratic congressmen would vote against Kennedy’s 1962 Trade Expansion Act, demonstrating that partisan media influence extended beyond electoral outcomes to shape legislative behavior.
Professor Grace Kim, Faculty Advisor
JEL Codes: D72; L82; N42
Keywords: Media Effects; Political Economy; Electoral Behavior; Conservative Radio; Partisan
Realignment
A Comparison of the HHI and the Procurement-Based Framework in Merger Review
by Kenneth Gong
Abstract
The Herfindahl-Hirschman Index (HHI), a measure of market concentration, plays a critical role in the U.S. Merger Guidelines. It is used as a threshold metric that marks certain mergers as potentially harmful to consumers. However, the microfoundations for the HHI are grounded in the Cournot oligopoly model, which may not be an appropriate foundation for certain markets, particularly those in which buyers purchase through competitive procurements. Recent developments in Incomplete Information Industrial Organization (IIIO) allow merger analysis to be tailored to such procurement-based markets. While IIIO methods allow one to calculate the probability of an increase in price (PIP) as a result of a horizontal merger, until now no work has been done to compare the HHI approach to merger review with the IIIO approach. In this paper, we find that the IIIO approach is largely consistent with the 2023 Merger Guidelines in that we agree that both the post-merger HHI and the change in HHI should be used in merger review, however our results place greater emphasis on the change in HHI in terms of predictive power of the PIP.
Professor Leslie Marx, Faculty Advisor
Professor Michelle Connolly, Faculty Advisor
JEL Codes: L4, L41, L44
The Press and Peace, Examining Iraq War Coverage in Newspapers using BERT LLMs
by Jakobe Bussey
Abstract
This study utilizes state-of-the-art BERT (Bidirectional Encoder Representations from Transformers) models to perform sentiment analysis on Wall Street Journal and New York Times articles about the Iraq War published between 2002 and 2012 and further categorize them using advanced unsupervised machine learning techniques. By utilizing statistical analysis and quartic regression models, this paper concludes that the two newspapers report on the Iraq War differently, with both exhibiting a predominantly negative-neutral tone overall. Additionally, the analysis reveals significant fluctuations in negativity from both outlets over time as the war progresses. Furthermore, this study examines the objectivity of reporting between editorial and non-editorial articles, finding that non-editorials tend to report more objectively, and the neutrality of editorials remains relatively constant while the objectivity of non-editorials fluctuates in response to war events. Finally, the paper investigates variations in sentiment across different topics, uncovering substantial variations in positive, neutral, and negative sentiments across topics and their evolution over time.
Professor Peter Arcidiacono, Faculty Advisor
JEL Codes: L8, L82, H56
Beyond the But-For World: Weak-necessity causal reasoning for model-based counterfactuals in law and economics
by Lilia Qian
Abstract
Under current standards for scientific evidence defined under Daubert, antitrust models are frequently excluded from legal consideration, but not always for reasons that make them genuinely unreliable. This paper clarifies why antitrust models face difficulties when subjected to methodological scrutiny: the employment of model-based counterfactual arguments under an epistemically defective ‘but-for’ structure of causation. Assessing the relevance and reliability of an antitrust model is a matter of assessing the validity and applicability of the causal claim it makes, not the degree to which the modeling methodology is considered scientific. A more flexible causal framework, the weak-necessity structure of causation, is suggested as a means of developing and evaluating model-based counterfactuals. This framework allows for modeling of overdetermined-causation situations, or situations in which the outcome of interest can be attributed to two or more causes. Since antitrust cases typically involve overdetermined causation, the weak-necessity framework allows them to be modeled in a more precise and intuitive way.
Professor Kevin Hoover, Faculty Advisor
JEL Codes: B41, K21, L41, L44
Airline Non-Price Competition Between FSC and LCC Carriers: Varying Airline Optimization Strategies
by Lucas Johnson
Abstract
The goal of this paper is to extend the discourse surrounding certain topics in terms of airline
optimization which is defined in this paper as the ability of an airline to efficiently transport
goods and passengers as well as accrue revenue from its airplanes relative to its total capacity to
transport goods and accrue revenue. Previous literature deals heavily with the differences
between LCC and FSC carriers as well as the importance of both customer satisfaction and
operational efficiency for the ability of an airline to compete. The analysis of this paper is in the
form of a panel-regression performed on a dataset obtained from the T1 Airline Summary
Statistics form maintained by the Bureau of Transportation Statistics. This data demonstrates the
relationship between dependent variables represented by certain metrics of airline success,
revenue passengers enplaned, revenue passenger miles and revenue ton miles, with independent
variables that reflect optimization in terms of both payload and passenger transport. These
variables are influenced by factors such as certain measures of timeliness competition defined in
this analysis as ramp inefficiency and departure efficiency.
Professor Grace Kim, Faculty Advisor
JEL Codes: L93; D22; R4; L13
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;
