Research

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.

When do temporary cash flow shocks leave permanent scars on firms? I study this question using weather-driven suspensions of Italian public construction contracts, which generate sharp, exogenous and well-defined cash flow shocks: all payments to the firm are legally halted, while her cost obligations persist. Using a staggered difference-in-differences design matching treated firms to not-yet-treated controls on size, location and public sector reliance, I find that contract suspensions reduce firm sales by 30%, employment by 15% and total assets by 19%. These effects are not transitory - they deepen over four years following the initial shock. The scarring is driven by a within-firm amplification mechanism: the cash flow shock propagates from suspended to unsuspended contracts, as working capital constraints prevent firms from financing the upfront expenditures their other projects require. Payment delays on unsuspended contracts rise by 15%, and inventories are depleted as firms exhaust their buffer stocks. Crucially, contract suspensions disrupt cash flows without necessarily damaging the firm's physical assets, allowing me to isolate the effects of a pure earnings shock from any impairment of collateral values. Cross-firm heterogeneity confirms this reading: more pledgeable collateral does not insulate firms, while higher leverage and thinner working-capital buffers sharpen the scarring. The results point to two complementary frictions: a working capital constraint that generates the within-firm propagation, and an earnings-based borrowing constraint that prevents firms from accessing external finance to arrest the cycle.