Research

JOB MARKET PAPER

AI Regulation, Startup Financing, and Talent Allocation [SSRN]

Abstract: Governments are rapidly adopting artificial intelligence (AI) regulations to balance societal risks against potential productivity gains. Using a difference-in-differences design that exploits the staggered introduction of AI-related bills across 28 U.S. states, I find that proposed regulation reduces the annual probability that an AI startup secures funding and increases the likelihood of acquisition. The effects are concentrated in rules that restrict which AI systems can be built or deployed (“constraining” rules). By contrast, documentation, auditing, and disclosure requirements (“procedural” rules) dampen these effects, consistent with standardized disclosure reducing information frictions around opaque AI technologies. Hiring patterns show that constraining rules increase demand for AI governance roles and shift technical effort from frontier AI research toward deployment of existing systems, while procedural rules have the opposite effect. Startups also reallocate AI-related jobs to non-regulated states.

Awards: Oxford Saïd Foundation Research Award for the Best Doctoral Student Paper in Finance 

Seminar and Conference Presentations: Oxford Saïd FAME seminar

OTHER WORKING PAPERS

The Burden of University Equity Stakes for Spin-outs: Evidence from the UK  [SSRN]

(Co-authored with Thomas Hellmann and Mattias Qian)

Abstract: Universities generate breakthrough commercial technology, yet controversy persists regarding the optimal ownership stake they should retain in spin-outs commercializing these discoveries. This paper examines if higher university stakes inhibit spin-outs from raising venture capital funding. The analysis is based on a formal theory of spin-out fundraising, and draws on detailed administrative ownership data from spin-outs in the United Kingdom. Using an instrumental variable based on precedents set by prior spin-outs within a university, we find evidence that university stakes are a barrier to academic entrepreneurship, consistent with weakened founder incentives to raise venture capital. This effect is concentrated in universities that historically had higher university stakes.

Rejected with an invitation to resubmit at Management Science

Seminar and Conference presentations: Saïd Business School DPhil presentation (2023), NBER SI 2023 Entrepreneurship, Joint Workshop on Incentives, Management and Organization (IMO) & Entrepreneurship Economics (ENT) 

Featured In: Independent Review of University Spin-out Companies 

To name your venture after Oxbridge or not, that is the question!  [SSRN]

(Co-authored with Thomas Hellmann and Mattias Qian)

Abstract: This paper examines the significance of including a company’s location of origin in its name, a practice known as using an eponymous location name. Our theory demonstrates that signalling an origin from a prestigious location is an appealing strategy for relatively weaker companies, whereas stronger companies tend to avoid it. We empirically test this theory on a sample of UK university spin-outs from 2010-2021. Eponymous location names are particularly prevalent among spin-outs from Oxford and Cambridge. As predicted by our theory, eponymous location names are negatively related to measures of fundraising success after controlling for spin-out origin.

Forthcoming at the Canadian Journal of Economics 

WORK IN PROGRESS

The Diffusion of AI Capabilities Through Venture Capital Portfolios 

With Thomas Hellmann

AI Washing and the allocation of capital in AI startups 

With Jiaqi Zheng