Research
(Please note: I don't disclose early-stage projects)
(Please note: I don't disclose early-stage projects)
Abstract: This study investigates the impact of political belief disagreement in the IPO setting. By matching IPO deal data with BoardEx executives, institutional holdings data, and political donation records from the FEC, I show that political alignment systematically relates to IPO pricing and allocations. Using a shift-share instrument, I provide causal evidence that executive–president misalignment reduces underpricing. A within-underwriter design further shows that issuer–underwriter misalignment causally increases underpricing. For the underwriter–investor margin, I document that lower disagreement is associated with greater underpricing and that higher disagreement predicts smaller allocations at the fund–deal level, consistent with favoritism in book-building. These results indicate that political homophily operates through distinct channels—optimism/signaling, agency frictions, and favoritism—affecting both prices and allocations in primary equity markets.
Presentations: 2025 Fall Finance Brown Bag Seminar (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: 2024 Spring Finance Brown Bag Seminar*; 2024 Fall Finance Brown Bag Seminar; University of Texas at San Antonio*; 2025 Eastern Finance Association Annual Meeting; 2025 SFS Cavalcade North America 2025*; 2025 Silicon Prairie Finance Conference; 2025 FMA Annual Meeting (Scheduled) (FMA 2025 Best Paper Semi-finalist in Asset Pricing & Investment)
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
with Yunxin Yi
Abstract: We study the effect of workplace partisan matching on performance in the setting of sell-side equity analysts. Looking at the granular forecast-level estimates, we find that the workplace partisan matching is positively associated with the forecast accuracy of analysts employed in the same brokerage house in that quarter. With firm-by-analyst fixed effect, we strengthen the identification that this positive impact is persistent over time and is unlikely to be confounded by time-invariant analyst or firm characteristics. This effect is stronger for firms in politically sensitive industries, but weaker for firms with high social and environmental scores. Overall, this paper documents a direct, positive, and time-persistent effect of partisan assortative matching within the analyst workplace on forecast performance.