The regulation of large interconnected financial institutions has become a key policy issue. To improve financial stability, regulators have proposed limiting banks’ size and interconnectedness. I estimate a network-based model of the over-the-counter interbank lending market in the US and quantify the efficiency-stability implications of this policy. Trading efficiency decreases with limits on interconnectedness because the intermediation chains become longer. While restricting the interconnectedness of banks improves stability, the effect is non-monotonic. Stability also improves with higher liquidity requirements, when banks have access to liquidity during the crisis, and when failed banks’ depositors maintain confidence in the banking system.

We construct a sample of over 200,000 supply chains between 2003 and 2018 to conduct a chain-based analysis of trade credit. Our study uncovers novel stylized facts about trade credit both within and across supply chains. More upstream firms borrow more from suppliers, lend more to customers, and hold more net trade credit. This upstreamness effect in trade credit is weaker for more profitable firms and for longer chains. Firms in more central or more profitable chains provide more net trade credit. Our results are generally consistent with the recursive moral hazard theory of trade credit. Evidence for the financing advantage theory is mixed.

We document an unprecedented brain drain of Artificial Intelligence (AI) professors from universities from 2004 to 2018. We find that students from the affected universities establish fewer AI startups and raise less funding. The brain‐drain effect is significant for tenured professors, professors from top universities, and deep‐learning professors. Additional evidence suggests that unobserved city‐ and university‐level shocks are unlikely to drive our results. We consider several economic channels for the findings. The most consistent explanation is that professors' departures reduce startup founders' AI knowledge, which we find is an important factor for successful startup formation and fundraising.

We examine empirically and theoretically the relation between firms’ risk and distance to consumers in a production network. We document two novel facts: firms farther away from consumers have higher risk premiums and higher exposure to aggregate productivity. We quantitatively explain these findings using a general equilibrium model featuring a multilayer production process. The economic force is “vertical creative destruction,” that is, positive productivity shocks to suppliers devalue customers’ assets-in-place, thereby lowering the cyclicality of downstream firms’ values. We show that vertical creative destruction varies with competition and firm characteristics and generates sizable cross-sectional differences in risk premiums.