About my Research
My research is at the juncture of finance, innovation, and labor. I study the drivers of innovation, entrepreneurship and technological change and their economic impact on firms, workers, and broader society. In my prior work, I examined the impact of financial crises on innovation and entrepreneurship, as well as the drivers and economic impact of fintech entry. More recently, I have done research on measuring the economic impact of recent technological developments, particularly artificial intelligence (AI) technologies, examining AI’s impact on firm performance, labor composition, and changes in firm risk.
The AI in Finance Conference: Opportunities and Risks
I organize research conference on AI in Finance at at the University of Maryland's Smith School of Business. You can find programs for past conferences here: 2024, 2025, and 2006. If you are interested in receiving the call for papers, sign up here.
My research is at the juncture of finance, innovation, and labor. I study the drivers of innovation, entrepreneurship and technological change and their economic impact on firms, workers, and broader society. In my prior work, I examined the impact of financial crises on innovation and entrepreneurship, as well as the drivers and economic impact of fintech entry. More recently, I have done research on measuring the economic impact of recent technological developments, particularly artificial intelligence (AI) technologies, examining AI’s impact on firm performance, labor composition, and changes in firm risk.
The AI in Finance Conference: Opportunities and Risks
I organize research conference on AI in Finance at at the University of Maryland's Smith School of Business. You can find programs for past conferences here: 2024, 2025, and 2006. If you are interested in receiving the call for papers, sign up here.
Publications (including Forthcoming and Accepted)
13. Understanding Firms' AI Efforts and Their Economic Impact. Review of Corporate Finance Studies 2026
- Keynote speech at the Economic and Societal Impacts of AI Conference in Munich, Germany, organized by CESifo
- This paper reviews firm-level data on artificial intelligence (AI) and the emerging evidence on AI's economic effects. It argues that measurement is central: different AI datasets capture different objects-including invention versus use, internal capability building versus outsourcing, and realized activity versus investor perceptions-and can therefore lead to different conclusions. The paper develops a framework for choosing among these measures and surveys available data sources on firm AI efforts. It synthesizes evidence on AI's effects on firm growth, valuation, productivity, risk, labor, competition, financial markets and applications. The paper concludes by suggesting some ideas for future research.
12. Russian Oil Exports under International Sanctions. Energy Economics 2026, with Benjamin Hilgenstock, Oleg Itskhoki, Maxim Mironov, Elina Ribakova, Natalia Shapoval
- Based on Russian customs data, we develop a novel transaction-level data set for Russian oil and product export prices, volumes, and revenues, disaggregated by ports and trading partners. The data set shed light on the evolution of Russian oil trade between the full-scale invasion of Ukraine in February 2022 and the first months of the EU embargo and G7 price cap imposed in late 2022 on Russian oil and refined product exports. Russian crude oil and oil product exports, in value terms, fell by $15.6 billion in 2023Q1 vs. 2022Q4, accounting for 40 % of the total decline in Russian exports. We estimate contributions of 6.1 billion from smaller volumes, $4.2 billion from lower global prices, and $5.2 billion from larger price discounts. At the same time, 2023Q1 budget revenues from hydrocarbons fell 47 % below the previous quarter. Price discounts on Russian crude oil exports widened considerably in segments of the market where demand conditions changed due to the exit of European buyers. There is evidence of systematic violations of the price cap that underscore the need for more rigorous sanctions enforcement.
11. Customer Data Access and Fintech Entry: Early Evidence from Open Banking. Journal of Financial Economics 2025, with Saleem Bahaj, Greg Buchak, Filippo De Marco, Angus Foulis, Will Gornall, Francesco Mazzola, Tong Yu
- Open banking (OB) empowers bank customers to share transaction data with fintechs and other banks. 49 countries have adopted OB policies. Consumer trust in fintechs predicts OB policy adoption and adoption spurs investment in fintechs. UK microdata shows that OB enables: i) consumers to access both financial advice and credit; ii) SMEs to establish new fintech lending relationships. In a calibrated model, OB universally improves welfare through entry and product improvements when used for advice. When used for credit, OB promotes entry and competition by reducing adverse selection, but higher prices for costlier or privacy-conscious consumers partially offset these benefits.
10. Artificial Intelligence Makes Firm Operating Performance Less Volatile. American Economic Review: Papers and Proceedings 2025, with Anastassia Fedyk, Alex He, James Hodson
- We study the shifts in U.S. firms’ workforce composition and organization associated with the use of AI technologies. To do so, we leverage a unique combination of worker resume and job postings datasets to measure firm-level AI investments and workforce composition variables, such as educational attainment, specialization, and hierarchy. We document that firms with higher initial shares of highly-educated workers and STEM workers invest more in AI. As firms invest in AI, they tend to transition to more educated workforces, with higher shares of workers with undergraduate and graduate degrees, and more specialization in STEM fields and IT and analysis skills. Furthermore, AI investments are associated with a flattening of the firms’ hierarchical structure, with significant increases in the share of workers at the junior level and decreases in shares of workers in middle-management and senior roles. Overall, our results highlight that adoption of AI technologies is associated with significant reorganization of firms’ workforces.
9. IPOs, Human Capital, and Labor Reallocation. Journal of Financial and Quantitative Analysis 2025, with Paige Ouimet and Rebecca Zarutskie
- We examine the human capital of IPO-filing firms and how going public affects their labor force. IPO-filing firms have high average wages and limited industrial diversification. Moreover, we document that a successful IPO increases departures of high-skilled employees to startups and diversification though employment growth in non-core industries. While IPOs do not significantly affect earnings growth of pre-IPO workers, post-IPO hires receive larger earnings increases upon joining. These results are most consistent with agency mechanisms associated with the transition to public ownership. Overall, going public has significant implications for the firms’ overall labor force, the firm, and labor reallocation.
8. Friends during Hard Times: Evidence from the Great Depression. Journal of Financial and Quantitative Analysis 2024, with Diego Garcia and Geoff Tate
- Using a novel dataset of over 3500 public and private firms, we construct the network of firm connections through executives and directors on the eve of the 1929 financial market crash. We find that more connected firms have 17% higher 10-year survival rates on average. Consistent with a role in facilitating access to working capital, the results are particularly strong for small firms, private firms, cash-poor firms, and firms located in counties with high bank suspension rates during the crisis. Moreover, connections to cash-rich firms that increase their accounts receivable during the peak of the crisis are most important for survival. Our results suggest that network connections can play a stabilizing role during a financial crisis by easing the flow of capital to constrained firms.
7. Artificial Intelligence, Firm Growth, and Product Innovation. The Journal of Financial Economics 2024, with Anastassia Fedyk, Alex He, James Hodson
- The most cited paper published in 2024 in the top three finance journals: Journal of Financial Economics, Review of Financial Studies, and Journal of Finance
- We study the use and economic impact of artificial intelligence (AI) technologies among U.S. firms. We propose a new measure of firm-level AI investments, using a unique combination of detailed worker resume and job postings datasets. Our measure reveals a stark increase in AI investments across sectors in the last decade. AI-investing firms see higher growth in sales, employment, and market valuations. We use a novel identification strategy, instrumenting firm-level AI investments with firms' ex-ante exposure, based on alumni networks, to the supply of AI-skilled labor from universities historically strong in AI research. The positive growth effect of AI comes primarily through increased product innovation, reflected in trademarks, product patents, and updates to product portfolios. AI-powered growth concentrates among the ex-ante largest firms, leading to higher industry concentration and reinforcing winner-take-most dynamics. Our results highlight that new technologies can contribute to growth through product innovation.
6. Firm Investments in Artificial Intelligence Technologies and Changes in Workforce Composition. The NBER Volume on Technology, Productivity, and Economic Growth 2025, with Anastassia Fedyk, Alex He, James Hodson
- We study the shifts in U.S. firms’ workforce composition and organization associated with the use of AI technologies. To do so, we leverage a unique combination of worker resume and job postings datasets to measure firm-level AI investments and workforce composition variables, such as educational attainment, specialization, and hierarchy. We document that firms with higher initial shares of highly-educated workers and STEM workers invest more in AI. As firms invest in AI, they tend to transition to more educated workforces, with higher shares of workers with undergraduate and graduate degrees, and more specialization in STEM fields and IT and analysis skills. Furthermore, AI investments are associated with a flattening of the firms’ hierarchical structure, with significant increases in the share of workers at the junior level and decreases in shares of workers in middle-management and senior roles. Overall, our results highlight that adoption of AI technologies is associated with significant reorganization of firms’ workforces.
5. Entrepreneurial Spillovers from Corporate R&D. Journal of Labor Economics 2024, with Sabrina Howell
- Honorable Mention, Yuki Arai Faculty Research Prize for Finance, 2018
- This paper offers the first study of how changes in corporate R&D investment affect labor mobility. We document that increases in firm R&D have no measurable effect on employee mobility to other incumbent firms or on exit from employment, but do spur employee departures to join the founding teams of startups. These startups are more likely to be outside the R&D-investing employer’s industry, suggesting that the ideas moving via employees to startups would impose diversification costs on the parent. These startups also likely generate substantial spillover benefits, as they are more likely to be VC-backed, high-tech, and high-wage.
4. Cutting the Innovation Engine: How Federal Funding Shocks Affect University Patenting, Entrepreneurship, and Publications. Quarterly Journal of Economics 2023, with Alex Xi He, Sabrina Howell, Elisabeth Perlman, Joseph Staudt
- NYU Stern Yuki Arai Faculty Award for Best Paper in Finance 2020
- This paper studies how federal funding affects the innovation outputs of university researchers. We link person-level research grants from 22 universities to patents, publications, and career outcomes from the U.S. Census Bureau. We focus on the effects of large, idiosyncratic, and temporary cuts to federal funding in a researcher’s pre-existing narrow field of study. Using an event study design, we document that these negative federal funding shocks reduce high-tech entrepreneurship and publications, but increase patenting. The lost publications tend to be higher quality and more basic, while the additional patents tend to be lower quality, less general, and more often privately assigned. These federal funding cuts lead to an increase in private funding, which partially compensates for the decline in federal funding. Together with evidence from industry-university contracts, the results suggest that federal funding cuts shift university research funding from federal to private sources and lead to innovation outputs that are less openly accessible and more often appropriated by corporate funders.
3. Financial Disruptions and the Organization of Innovation: Evidence from the Great Depression.
Review of Financial Studies 2023, with Asaf Bernstein and Filippo Mezzanotti
- Lead Article & Editor's Choice. Earlier version of this project received the Best Paper Award from the China International Conference in Finance (CICF)
- This paper was previously titled "Crisis Innovation"; Online Appendix A; Online Appendix B
- We examine innovation after the Great Depression using data on a century’s worth of U.S. patents and a difference-in-differences design that exploits regional variation in the severity of the economic crisis. Harder-hit areas experienced large and persistent declines in independent patenting, which lasted for the next 70 years. This decline was larger for young and inexperienced inventors and lower-quality patents. In contrast, large firms had relative innovation increases, especially for inventors with the largest declines in independent patenting. Overall, the Great Depression contributed to the decline in technological entrepreneurship and accelerated the shift of innovation into larger firms.
2. Heterogeneous Taxes and Limited Risk Sharing: Evidence from Municipal Bonds. Review of Financial Studies 2021, with Pab Jotikasthira, Chris Lundblad, and Tarun Ramadorai
- James A. Lebenthal Memorial Prize for Best Paper at the Fourth Annual Municipal Finance Conference
- We evaluate the impacts of tax policy on asset returns using the U.S. municipal bond market. In theory, tax-induced ownership segmentation limits risk-sharing, creating downward-sloping regions of the aggregate demand curve for the asset. In the data, cross-state variation in tax privilege policies predicts differences in in-state ownership of local municipal bonds; the policies create incentives for concentrated local ownership. High tax privilege states have muni bond yields that are more sensitive to variations in supply and local idiosyncratic risk. The effects are stronger when local investors face correlated background risk and/or diminishing marginal non-pecuniary benefits from holding local assets.
1. Destructive Creation at Work: How Financial Distress Spurs Entrepreneurship (Online Appendix). Review of Financial Studies 2020
- Using U.S. Census firm-worker data, I document that firms' financial distress has an economically important effect on employee departures to entrepreneurship. The impact is amplified in the high-tech and service sectors, where employees are key assets. In states with enforceable noncompete contracts, the effect is mitigated. Compared to typical entrepreneurs, distress-driven entrepreneurs are high-wage workers who found better firms, as measured by jobs, pay, and survival. Startup jobs compensate for 33% of job losses at the constrained incumbents. Overall, the financial inability of incumbent firms to pursue productive opportunities increases the reallocation of economic activity into new firms.
Working Papers
5. Canaries in the Gold Mine: Early Productivity Gains from Artificial Intelligence Creating Organization Capital, with Alex He, Renhao Jiang
- Using a new firm-level measure of AI investment based on AI-skilled employment---spanning machine learning through generative and agentic AI---we show that AI investments are associated with productivity growth in recent years, but not over the previous decade. We trace the productivity gains to the accumulation of organization capital that AI helps create: durable firm-specific knowledge acquired through learning-by-doing that enables more efficient production. We build a novel measure of organization capital based on workers' job descriptions and document that productivity gains are driven by AI-skilled jobs that build organization capital. Overall, our findings suggest that AI investment generates productivity growth by creating organization capital.
4. Antitrust Enforcement Increases Economic Activity. Conditionally Accepted at AEJ: Applied, with Simcha Barkai, Jessica Jeffers, Ezra Karger, and Ekaterina Volkova
- FIRN Brattle Best Paper Award
- We hand-collect information describing all 3,055 antitrust lawsuits brought by the Department of Justice (DOJ) between 1971 and 2018. Using confidential U.S. Census microdata, we show that DOJ lawsuits targeting past anticompetitive conduct in local industries lead to a persistent 5.4% increase in employment and 4.1% increase in business formation compared to the same industries in other states. We further find (1) a sharp increase in payroll exceeding the increase in employment, (2) an economically and statistically insignificant increase in sales, and (3) a precise increase in the labor share. Our results show that government antitrust enforcement increases economic activity.
3. Artificial Intelligence and Firms' Systematic Risk, with Anastassia Fedyk, Alex He, James Hodson
- We leverage comprehensive data on firm-level AI investments to examine how firms' systematic risk changes with the advent of artificial intelligence (AI) during the 2010s. Firms that invest more in AI see increases in their systematic risk, measured by equity market beta. This result is unique to AI: robotics, IT, organizational capital, and general R&D investments do not display similar results during the sample period. We show that the increased market beta of AI-investing firms is not explained by financial or operating leverage, asynchronous trading, increased correlation with the tech sector, within industry concentration, or correlated investor flows. Instead, our results are consistent with AI investments creating new growth options for firms: AI-investing firms become more growth-like, and the effect on market betas is twice larger on the market upside than on the downside. Overall, our findings provide direct evidence that firms' investments in new technologies such as AI create growth options and affect the composition of the firms' risk profiles.
2. The Impact of Money in Politics on Labor and Capital: Evidence from Citizens United v. FEC, with Pat Akey, Greg Buchak, Ana-Maria Tenekedjieva
- We examine whether corporate money in politics benefits or hurts labor using the 2010 Supreme Court ruling Citizens United, which rendered bans on political election spending unconstitutional. In difference-in-difference analyses, affected states experience increases in both capital and labor income relative to unaffected states. We find evidence consistent with increased political spending spurring political competition and the adoption of pro-growth policies. These policies benefit a broader set of constituents as we find a broad-based increase in labor income. Affected states see increased political turnover and reduced regulatory burdens. The economic effects are stronger among ex-ante politically inactive and younger firms.
1. Pay, Employment, and Dynamics of Young Firms, with Wenting Ma, Chris Moser, Paige Ouimet, Rebecca Zarutskie
- Why do young firms pay less? Using confidential microdata from the US Census Bureau, we find lower earnings among workers at young firms. However, we argue that such measurement is likely subject to worker and firm selection. Exploiting the two-sided panel nature of the data to control for relevant dimensions of worker and firm heterogeneity, we uncover a positive and significant young-firm pay premium. Furthermore, we show that worker selection at firm birth is related to future firm dynamics, including survival and growth. We tie our empirical findings to a simple model of pay, employment, and dynamics of young firms.