My research sits at the intersection of political economy, behavioral finance, and real estate markets. I am especially interested in how political identity, partisanship, and spatial dynamics shape economic decisions both for households and professionals in contexts where bias or identity-based expectations alter market outcomes. Through rigorous empirical work with voter registration, housing transaction, forecast, and policy data, I combine quantitative econometric methods and spatial analysis to uncover how beliefs and politics influence asset pricing, housing, and investment behavior.
Job Market Paper: Political Alignment and Housing Transactions
In this paper, I use voter registration data from North Carolina matched to housing transactions from 2009 to 2022 to show that households sharing party affiliation with the sitting president are more likely to buy or sell homes. This appears to be driven by lower perceived economic uncertainty and a greater willingness to undertake irreversible housing investments. I document equilibrium effects as neighborhoods with higher shares of aligned households experience greater housing supply, longer time on market, and lower prices. I use the entry of Sinclair Broadcast Group as an exogenous shift in local partisan alignment to provide causal evidence. This work contributes to the literature by demonstrating that partisan alignment influences one of the most important household financial decisions.
Published Work: When the Train Never Comes
In my published article in The Professional Geographer with Isabelle Nilsson and Elizabeth C. Delmelle, I study the Durham Orange Light Rail project. We examine whether property values responded to both the announcement and later cancellation of the project. Using matched treatment and control properties, we find no significant effect of either announcement or cancellation on station adjacent properties. Instead, appreciation was concentrated in denser and more centrally located neighborhoods. These findings suggest that what appears to be a transit premium is often the result of underlying growth and density rather than the transit investment itself.
Additional and Ongoing Projects
I am developing a paper on partisan identity in analyst forecasts. Early results show that analysts misaligned with the president issue more conservative forecasts, but that competitive pressures reduce this bias. Another developing project tests whether political identity influences institutional participation in green energy investment. Preliminary results suggest alignment may encourage participation in ESG and renewable energy opportunities.
Future Research Agenda
Over the next several years I plan to extend this agenda in three areas. First, I will study behavioral and identity based bias among financial professionals beyond analysts to include fund managers and portfolio decision makers. Second, I will investigate how local political alignment and policy heterogeneity influence real estate finance outcomes such as mortgage pricing, neighborhood investment, and valuation. Third, I will study how political beliefs influence ESG and sustainability related investments, including green bonds and corporate climate initiatives.
My work relies on careful identification strategies, large administrative and market datasets, and empirical asset pricing frameworks. These contributions broaden our understanding of how identity and belief systems affect economic behavior while providing evidence that is directly relevant for public policy and financial regulation.