Political Alignment and Housing Transactions
with Yongqiang Chu and Cong (Roman) Wang
Abstract: By matching voter registration records with housing transaction data, we find that voters who share the same political affiliation as the current U.S. president are 0.214 percentage points (10% of the unconditional probability) more likely to engage in housing transactions. Both buying and selling transactions increase, suggesting that reduced perceived economic uncertainty drives this effect. We develop a spatial equilibrium model predicting that these politically motivated transactions lead to lower house prices in aligned neighborhoods due to increased supply without corresponding demand increases. Empirically, house prices in aligned census blocks are 2.0% lower than in misaligned blocks, consistent with our theoretical predictions.
Presentations: UNC Charlotte (2024, 2025, 2026), FMA Semi-Finalist Best Paper (2025), 2026 ARES Annual Conference (2026)
Press: Featured in The Wall Street Journal article, "What Puts Republicans in the Mood to Shop."
When the Train Never Comes: Property Value Impacts from the Announcement and Cancellation of a Light Rail Project.
The Professional Geographer (2025)
with Isabelle Nilsson and Elizabeth C. Delmelle
Abstract: Academics and practitioners have long been interested in the potential property value increases associated with new transit investments. The placement of transit stations is not random, however, and often they are placed in locations most likely to experience growth. Therefore, isolating the impacts of the new infrastructure from these confounding factors has been a challenge. In this study, we examine the effect of the announcement and subsequent cancellation of a transit project on sales prices, taking advantage of a unique natural experiment, the Durham Orange Light Rail Transit project. Using a set of closely matched treatment and control properties, we find no evidence of an announcement or cancellation effect on station-adjacent property sales prices. We find evidence, however, that prices in denser areas, closer to the city center tended to appreciate at a higher rate. These findings suggest a shift in demand for living in dense, urban environments, which is often where rail transit stations are located. The results are essential for urban planning as they show that rail transit is planned in growing cities with tight housing markets where properties, including those located in neighborhoods with planned stations, are already on an upward growth trajectory in terms of price.
Presentations: UNC Charlotte (2023, 2026)
The Mere Exposure Effect in Architecture
Humanizing Digital Reality (pp 589–602, 2018)
with Christopher Beorkrem and Jefferson Ellinger
Abstract: Per Schelling’s model of Segregation, the population will innately segregate itself based on preferences, often leading to organization by race and class. This subdividing of communities through segregation increases social tension, discourages communication, and isolates those who are different. In 1968, Robert Zajonc proved that subjects rated a familiar stimulus more positively than similar yet unfamiliar stimuli. The mere exposure effect is a phenomenon by which people develop a preference for things solely because they are familiar with them. Architecture can diminish the impact of social segregation through mere exposure by examining the effects of architectural interventions and programs. Through mere exposure designers can create new connections between members of society by rethinking circulation paths, carefully considering the geolocation of program, and creating more effective public space. By incorporating modern social behavioral analytics into design logics, social spaces can facilitate more productive engagements between occupants. Examining the effect of unit location on circulation and noting the most effective locations for public goods, developers and city planners will increase communication between community members. Increasing communication as a primary goal of design will facilitate the development of stronger communities. Although the tool specifically targets residential complexes, the concept is scalable. Providing a designer an automated method for evaluation and data collection based on the mere exposure effect in urban design and architecture can create more informed design of public space. The goal is to create a more diverse and sustainable community through an informed understanding of how space and program influence behavior.
Presentations: Design Modelling Symposium 2017, UNC Charlotte (2016, 2017)
Competition, Visibility, and Partisan Bias in Sell-Side Equity Research
Solo Authored
Abstract: Partisan bias in professional economic judgment is well documented in private settings, where accuracy is difficult to observe, and peer competition is limited. Whether that bias survives in a public, competitive setting is less clear. I examine this question using voter registration data matched to sell-side equity analyst earnings forecasts for S&P 500 firms from 1992 to 2020. Consistent with prior work, misaligned analysts issue more pessimistic forecasts. But the bias attenuates along every margin I measure. Analysts in battleground states show no measurable bias: misaligned pessimism and aligned optimism compress symmetrically toward zero. Long-run political diversity among analysts covering a firm reduces individual bias, while persistent unanimous coverage amplifies it. Within brokerages, contemporaneous cross-partisan exposure limits bias amplification, and persistent homogeneity strengthens it. Elevated aggregate political conflict attenuates the bias rather than amplifying it, the reverse of what prior work finds in private credit markets. The results suggest that partisan bias in expert judgment depends on whether the institutional setting exposes it to correction through peer competition, public attribution, or cross-partisan information saturation.
Presentations: UNC Charlotte (2023, 2024, 2026), Research in Behavioral Finance Conference at Vrije Universiteit Amsterdam (2026), 37th Annual Meeting of the Academy of Behavioral Finance & Economics (2026)