Yifan (Freda) Fang

Research

Green Demand vs. Brown Assets: Can Market Forces Discipline Polluting Divestitures?

Presentations: Inaugural HKU Governance and Sustainability PhD Workshop (2025),  EsFA (2025), Rotman Sustainable Finance Research Roundtable (2025), NFA PhD Session (2024), MFA Regular Session (2024),  Rotman School of Management (2023)

Abstract: I examine whether market forces can mitigate environmental externalities in the context of U.S. fossil-fuel power plant divestitures. Using plant-level data from 2004 to 2022, I find that divested plants increase carbon emissions by 18% on average after the transaction, but this increase is almost entirely offset in fully deregulated electricity markets, where firms face stronger incentives to cater to green preferences. Consistent with a demand-side mechanism, the offset is strongest in regions and periods with greater corporate demand for clean energy. The findings suggest a demand-side channel through which competitive electricity markets can mitigate environmental costs and support decarbonization.

Venture Fraud, with Alexander Dyck, Camille Hebert, and Ting Xu

Presentations: EFA (2026, Scheduled), FIRS (2026), UT Austin Forensic Finance Conference (2026), University of Kentucky Finance Conference (2026), IPC Spring Research Symposium (2026), Bretton Woods Accounting and Finance Ski Conference (2026), UD Weinberg-ECGI Symposium (2026), ASU Sonoran Winter Finance Conference (2026), HEC Paris Entrepreneurship Workshop (2025), Rotman School of Management (2025)

Media Coverage: Financial Times, Bloomberg Money Stuff by Matt Levine, The Globe and Mail, ECGI, Boardroom Governance Newsletter, Nominal News 

Award: 2026 John L. Weinberg/IRRCi Research Paper Award  

Abstract: We assemble the first dataset of venture fraud cases involving 654 U.S. VC-backed startups. Venture fraud has increased over the past two decades. Among newly public firms, VC-backed companies are more likely to face fraud charges than comparable non-VC-backed firms. Governance characteristics, rather than founder traits, are the strongest predictors of fraud: fraud is more prevalent in startups with founder-friendly contracts, complex cap tables, and initial rounds raised in hot market conditions. Fraudulent entrepreneurs continue to found new VC-backed startups unharmed, suggesting weak market discipline. These findings highlight growing agency costs in private markets.

Silicon Valley Everywhere? Startup Accelerators and the Geography of Entrepreneurship, with Mohaddeseh Heydari Nejad 

Presentations: NFA (2026, Scheduled), EARIE (2026, Scheduled), RCFS Winter Conference (2026),  Rotman School of Management (2026),  Kelley School of Business (2025)

Abstract: Entrepreneurial entry reflects a fundamental tradeoff between strategic complementarities within local ecosystems and competition for scarce resources. This paper examines how this tradeoff shapes regional entrepreneurs’ entry decisions. We exploit the staggered rollout of the Creative Destruction Lab (CDL), a global mentoring-based accelerator that introduced 27 streams across 10 cities between 2012 and 2022. To address endogenous program placement, we construct a novel instrument based on academic collaboration networks between business schools and the CDL’s founding institution, the University of Toronto. We show that sector-specific launches reshape the composition of local entrepreneurship by reallocating startup formation toward treated sectors. Entry responses are weakened when local spillover potential is low, consistent with a complementarity-driven mechanism. Investor capital does not respond, resulting in intensified competition for financing. Motivated by these patterns, we develop a structural model that organizes the underlying mechanisms and provides suggestive policy counterfactuals. We document substantial heterogeneity in responses across sectors, with some targeted sectors experiencing costly crowding. Overall, the model suggests that generic policies may coordinate a broader base of participants more effectively than narrow targeting.