Research

Working Papers:

ESG Incidents and Fundraising in Private Equity
(with Chhavi Rastogi and Tianhao Yao)

Main Presentations: FIRS (scheduled), Law and Finance of Private Equity and Venture Capital (scheduled), EeasternFA , MFA, Singapore Private Equity Research Symposium, Inquire Europe Fall Seminar , 3th Oxford Sustainable Private Market Conference , HEC-HKUST Sustainable Finance Seminar Series , GRASFI, 7th Annual Private Markets Research Conference, International Risk Forum.

Abstract: We present novel evidence on how environmental and social (E&S) incidents affect the capital-raising ability of Private Equity (PE) firms. PE firms with E&S incidents in portfolio companies are less likely to fundraise and raise smaller subsequent funds. The decrease in capital commitment does not seem related to fund performance; instead, it is driven by E&S concerns of relationship limited partners (LPs). LPs trade off E&S concerns with financial cost of breaking relationships, implying a weaker impact on large, top-performing PE firms. The threat of “exit” by E&S-concerned investors incentivizes PE firms to exert “voice” and mitigate negative E&S externalities.

Capital Allocation Concentration Measurement in Venture Capital
(with Viacheslav Bazaliy)

Abstract: We revisit the measurement of capital allocation concentration in the venture capital (VC) industry and highlight the shortcomings of the widely used Herfindahl-Hirschman Index (HHI). We show that HHI-based concentration measures are sensitive to discrepancies in VC database coverage, industry taxonomies, and classification granularity, yielding divergent trends even when applied to identical VC portfolios. To overcome these limitations, we develop a novel concentration metric using large language model (LLM) text embeddings that capture the semantic similarity among financed startups beyond predefined industry classifications. Using matched PitchBook and Crunchbase data, we validate our approach and show that OpenAI embeddings outperform alternative models on signal-to-noise and retrieval tasks. Applying this methodology, we document that aggregate VC capital allocation concentration has increased more sharply than suggested by HHI measures. A novel decomposition shows that 40% of the growth in capital allocation concentration stems from an increase in within-sector similarity among founded startups—an effect that industry-based measures do not capture.

Exploration, Exploitation and Agency Issues in Venture Capital

(solo-authored, second year paper)

Main Presentations: Finance Theory Group Summer School, Rice - LEMMA Annual Conference, Aalto University, Entrepreneurship PhD Workshop, HEC Paris Brown Bag Seminar.

Abstract: I study the determinants of portfolio allocation decisions by venture capital (VC) firms. I construct a dynamic agency model with an exploration versus exploitation trade off of a VC firm raising capital for subsequent funds. The VC firm raises capital from a limited partner (LP) and can allocate this capital to a known market (exploitation) or explore a new market (exploration). The model features moral hazard between the general and limited partners and learning from past investments by the VC firm. I endogenize the portfolio allocation of the VC firm and the capital allocation of the limited partners. In the first best, firms with high opportunity cost of exploration do not explore; firms that choose to explore, base their allocation decision on the cost of managing the funds and their skill to learn from past investments. The threat of divestment by limited partners alleviates the moral hazard problem and can encourage exploration. Using Pitchbook data, I find evidence consistent with the model. Based on newly created VC firm’s partners’ past experience, I construct a novel opportunity cost of exploration measure and show that VC firms where the opportunity cost of exploration is high are more specialized and perform better at their first fund’s investments. Conditional on raising a follow up fund however, they grow less.

Work in Progress:

Human Capital Breadth, Portfolio Choice and Performance in Venture Capital

Main Presentations: Harvard Business School Lunch Seminar, HEC Paris Entrepreneurship Workshop (Early Ideas Session), Chicago Booth Finance PhD Brownbag, HEC Paris Brownbag

Product Market Competition and Intangible Investment

Contributions to Research:

Nonstandard Errors
(Journal of Finance 79, 2339-2390. 2024)
(with 342 co-authors as a research team member)

Abstract: In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty—nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.

Pre-PhD Publications:

Understanding detrimental and beneficial grain boundary effects in halide perovskites
(Advanced Materials 30.52, 2018)

Abstract: Grain boundaries play a key role in the performance of thin-film optoelectronic devices and yet their effect in halide perovskite materials is still not understood. The biggest factor limiting progress is the inability to identify grain boundaries. Noncrystallographic techniques can misidentify grain boundaries, leading to conflicting literature reports about their influence; however, the gold standard – electron backscatter diffraction (EBSD) – destroys halide perovskite thin films. Here, this problem is solved by using a solid-state EBSD detector with 6000 times higher sensitivity than the traditional phosphor screen and camera. Correlating true grain size with photoluminescence lifetime, carrier diffusion length, and mobility shows that grain boundaries are not benign but have a recombination velocity of 1670 cm s−1, comparable to that of crystalline silicon. Amorphous grain boundaries are also observed that give rise to locally brighter photoluminescence intensity and longer lifetimes. This anomalous grain boundary character offers a possible explanation for the mysteriously long lifetime and record efficiency achieved in small grain halide perovskite thin films. It also suggests a new approach for passivating grain boundaries, independent of surface passivation, to lead to even better performance in optoelectronic devices.