Research
(Please note: I don't disclose early-stage projects)
(Please note: I don't disclose early-stage projects)
Abstract: This paper documents partisan sorting between issuers and lead underwriters in U.S. initial public offerings. I link LSEG records for deals completed during 1990--2024 to BoardEx executives and their Federal Election Commission donations. Politically divergent issuer--underwriter pairs are systematically less likely to match. In the linear probability specification, a one-unit increase in political divergence lowers the probability of selection by approximately 8 percentage points, about 35% of the unconditional match rate. I identify the relationship using the staggered geographic expansion of the Sinclair Broadcast Group as a plausibly exogenous shock to underwriter executive ideology. The pattern operates through trust and information asymmetry channels: it intensifies during polarized periods and in deals with greater information asymmetry but attenuates when external certification substitutes for trust through political alignment. Partisan divergence also has pricing implications. A one-standard-deviation increase in deal-level political divergence is associated with 6.5 percentage points more first-day underpricing, or $14 million of additional money left on the table on average.
Presentations: 2026 Southern Finance Association (Scheduled); 2026 FMA (Scheduled); 2026 European Financial Management Association (Scheduled); Iowa Finance Brown Bag Seminar; 2026 SouthWestern Finance Association
Awards: 2026 FMA Best Paper Semi-finalist in Corporate Finance
with Amrita Nain and Yi Hao
Abstract: We show that ideological disagreement among sell-side analysts generates persistent earnings forecast dispersion. This effect is stronger in politically contentious industries and for firms with high ESG scores. An immigration-based shift-share instrument and a novel firm-level measure of analyst ideological disagreement confirm causality. Unlike information-based dispersion, ideology-induced dispersion does not decline over time. Consequently, ideological disagreement has significant implications for asset pricing and corporate finance. Stocks covered by more ideologically polarized analysts earn lower future returns, and acquirers with polarized analyst coverage use more equity and, in the subset of politically contentious industries, earn lower announcement returns.
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, the diffusion of ideas, and corporate innovation. In a county-pair panel of U.S. inventor mobility from 2001 to 2023, a one-standard-deviation increase in political distance between origin and destination counties reduces bilateral inventor flows by 20%, within as well as across party lines. Individual-level evidence identifies the mechanism. Matching inventors to their own political contribution records, Republican and Democratic inventors respond in opposite directions to the same destination's partisan lean. A conditional logit model of destination choice show that an inventor is 10% less likely to select a county one standard deviation further away from her own party. The friction is largest among within-state moves, where state institutions are held constant. At the firm level, a one-standard-deviation increase in PAC-donation-based ideological distance implies a 62.5% decline in inter-firm inventor moves. Political distance also dampens knowledge diffusion, reducing bilateral patent citations by 6.3%, slows entry into new technology classes, and lowers patenting output, both across counties and within firms' own footprints. Partisanship thus imposes a real cost on the allocation of inventive talent and the knowledge it carries.
Presentations: 2026 FMA (Scheduled); 2026 Silicon Prairie Finance Conference
with Amrita Nain, Tong Yao
Solo-authored, draft by request
Solo-authored, draft by request
Solo-authored, Data Preparation
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