Research
(Please note: I don't disclose early-stage projects)
(Please note: I don't disclose early-stage projects)
Abstract: This paper investigates how political divergence between IPO issuers and lead underwriters affects matching and pricing outcomes in the U.S. IPO market. Using U.S. IPOs from 1990 to 2024 matched with BoardEx executive data and Federal Election Commission donation records, I document three main findings. First, political divergence significantly reduces issuer–underwriter match formation: a one-unit increase in divergence lowers the likelihood of selection by 8%, or 35% relative to the sample mean. Second, this effect is stronger when trust is more valuable and information asymmetry is more severe, including politically polarized periods, high-tech deals, non-VC-backed deals, and hot IPO markets. Exploiting Sinclair Broadcast Group’s staggered geographic expansion as a plausibly exogenous shock to underwriter executives’ political attitude, I provide causal evidence that widening partisan gaps reduce matching likelihood. Lastly, political divergence has pricing implications: greater deal-level divergence predicts more IPO underpricing. Overall, the results show that partisanship shapes relationship formation and pricing in the primary equity market.
Presentations: Iowa Finance Brown Bag Seminar; 2026 SouthWestern Finance Association; 2026 European Financial Management Association (Scheduled)
with Amrita Nain and Yi Hao
Abstract: We study the impact of political polarization on analysts' earnings forecast dispersion. Using continuous, time-varying measures of ideological leanings of U.S. state legislators on the liberal-conservative scale, we show that greater political polarization in a state leads to greater dispersion in earnings forecasts of analysts located in that state. This effect is stronger for firms in politically sensitive industries and firms that commit significant resources to social and environmental issues. We develop a continuous, firm-level measure of analysts' ideological disagreement and document the importance of our finding for both asset pricing and corporate investments. Looking at the cross-section of returns, we show that stocks covered by more politically polarized analysts earn lower future returns. In an M&A setting, we show that acquirers covered by more polarized analysts earn significantly lower announcement returns for equity offers but not for all-cash offers.
Presentations: 2025 SFS Cavalcade North America 2025*; 2025 Eastern Finance Association Annual Meeting; 2025 FMA Annual Meeting; 2025 Silicon Prairie Finance Conference; 2024 Spring & Fall Iowa Finance Brown Bag Seminar*; University of Texas at San Antonio*;
Awards: 2025 FMA Best Paper Semi-finalist in Asset Pricing & Investment
Under Review
with Jiajie Xu
Abstract: We study how political distance between places affects the mobility of skilled labor. Using a county-pair-by-year panel spanning over 20 years, we show that a one-standard-deviation increase in the difference in Republican presidential vote shares between origin and destination counties reduces bilateral inventor flows by 6.3%. The effect is concentrated among cross-party county pairs and longer-distance moves, and does not intensify during periods of heightened polarization. At the firm level, a one-standard-deviation increase in PAC-donation-based ideological distance implies a 42.1% decline in inter-firm inventor moves. A regression discontinuity design based on close presidential elections reveals a pull mechanism: destination counties narrowly electing Republicans attract fewer inventors, with no comparable origin-side effect. Political ideology is a friction in the reallocation of skilled human capital across both regions and firms.
with Yunxin Yi
Abstract: We examine whether the partisan composition of an analyst's workplace affects her earnings forecast accuracy. Matching sell-side analysts in IBES to voter registration records over 2000--2024, we find that analysts at more politically diverse brokerages produce significantly more accurate forecasts, even after absorbing firm-by-year, analyst, and brokerage fixed effects. Comparing theoretical extremes, the most diverse workplaces are associated with approximately 3.9% lower absolute forecast error than the most homogeneous. Restricting to analysts who switch brokerages yields larger estimates, consistent with a causal workplace effect. Event-study analyses around five U.S. presidential elections show that the accuracy advantage of diverse workplaces attenuates sharply in post-election months while homogeneous workplaces are unaffected, suggesting that diversity benefits forecast quality through informal information exchange that is disrupted when partisan identities become salient.
with Amrita Nain, Yasmine Nosair, and Jiajie Xu
Abstract: We study whether funding goes up for firms developing labor-saving automation patents facing COVID-induced labor supply shock. We look into different types of funding, including venture capital funding, corporate acquisitions, and government funding such as SBIR and SBA. Additionally, we examine whether VC experience matters in identifying the firms conducting labor-saving innovation as well as the value of such innovation. Employing a work-from-home suitability measure, we find that innovative firms that are shielded from the labor shock themselves and develop more labor-saving innovations attract more VC funding, particularly experienced VCs. We find no similar effects for corporate acquisitions and government funding.
Presentations: 2024 Spring Finance Brown Bag Seminar