How Anti-ESG Pressure Affects Investment: Evidence from Retirement Savings (single-authored)
Reject and Resubmit, Journal of Finance
Media coverage: UCLA Anderson Review, Morningstar, Inc. Magazine
Awards: UCLA Xavier Drèze Prize for Best Ph.D. Student Research Paper, FMA Semifinalist in Asset Pricing & Investments
Presentations: SFS Cavalcade, NBER Pension Finance Conference, New York Fed and NYU Summer Climate Finance Conference Poster Session, UChicago Booth Stigler Center-CEPR Political Economy of Finance Conference 2024: Corporate Democracy, 16th Annual Alliance for Research on Corporate Sustainability (ARCS) Research Conference, Financial Market Solutions for Funding Green Transition and Climate Resilience—UCSC’s Center for Analytical Finance (CAFIN), the Center for Coastal Climate Resilience (CCCR) and UC Investments (invited), Wellington Finance Summit, SIF, Adam Smith Sustainability Conference, NFA, FMA, Pacific-Northwest Conference, CEAR-RSI Household Finance Conference, SFA, AFA AFFECT
This paper studies how the political environment impacts the availability of ESG options to individuals. I identify a judicial channel: because fiduciary duty is adjudicated by politically-oriented judges, litigation risk discourages some retirement plans from offering ESG. ESG availability is significantly lower in conservative than in liberal judicial circuits, beyond what demographics, firm characteristics and local politics explain. Reductions in judicial discretion close this gap substantially and increase ESG investment especially in conservative circuits. The effects are mostly driven by green firms, non-mega firms, and firms in liberal counties within conservative circuits. ESG inclusion also increases total retirement contributions.
The ESG Menu Puzzle: Lifecycle Theory versus Retirement Plan Practice (with Michael Gropper and Paul Yoo)
Presentations: University of Oregon Finance Brown Bag, 2026 2nd Annual Multidisciplinary Corporate Sustainability Conference at Santa Clara University, 2026 2nd UNC Kenan-Flagler Finance PhD Alumni Conference
This paper quantifies the welfare gains from including ESG assets in defined-contribution plans using a lifecycle portfolio-choice model with strictly risk-and-return factors. We find substantial heterogeneity across industries in the benefits of including an ESG asset. However, these model-implied welfare gains fail to explain cross-sectional patterns in the availability of ESG funds across retirement plans. Instead, we provide suggestive evidence that political and judicial environments, ESG preferences, and financial intermediaries have significant explanatory power. Our findings suggest that canonical risk-return optimization plays a marginal role in the menu-setting decisions governing the inclusion of ESG options in retirement plans.
Artificial Intelligence, Human Capital Risk and Household Portfolio Choice (with Kristoffer Berg, Luigi Dante Gaviano, and Constantine Yannelis)
For most households, human capital is the largest asset they own, and rapid advances in artificial intelligence (AI) may change its value. This paper studies whether workers whose occupations are more exposed to AI use financial and labor markets to hedge this risk, by investing in firms that gain from the new technology. We develop a portfolio-choice model with nontradable human capital in which AI-related equity pays off in states where exposed workers' labor income falls through technological unemployment. The model predicts that more exposed workers should hold more equity, especially when human capital is large relative to financial wealth. We test these predictions using linked Norwegian administrative data on workers' occupations, employers, income, wealth, and equity holdings. Workers in more AI-exposed occupations are more likely to participate in equity markets and, conditional on participation, hold more equity, especially from firms located in countries with firms more exposed to the AI boom. The exposure-equity relationship is stronger for younger workers, consistent with life-cycle hedging. Following the release of ChatGPT, workers with greater AI exposure also become more likely to move into lower-exposure industries and senior management roles. Our results highlight a channel through which financial markets may partially insure workers against technological unemployment.
Strategic Blindness: Optimal Inattention and Momentum Profitability (with Denis Mokanov and Gabriel Cuevas Rodriguez)
Presentations: Young Scholars Nordic Finance Workshop, FMA
We develop a model in which agents optimally choose their information acquisition rate. We show that our model provides an explanation for a number of empirical regularities documented in the literature: the unconditional profitability of momentum, the occurrence of momentum crashes, the enhanced profitability of volatility-managed momentum, and the attenuation of momentum. Next, we explore the implications of our model regarding the relative profitability of short-run and long-run momentum strategies, and show that the predictions of our model are supported by the data. Finally, we examine the implications of the model for sell-side analysts' earnings forecasts and find that earnings forecasts display conditional patterns consistent with the predictions of our model.