Knowledge that Transforms

A majority of small U.S. businesses attempting to reorganize in bankruptcy fail to successfully do so. Subchapter V of Chapter 11 was introduced in 2020 for firms with less than $7.5 million in liabilities to streamline the process by reducing bankruptcy costs and negotiation frictions, and enabling entrepreneurs to retain their ownership. Employing regression-discontinuity and difference-in-differences designs, we show that many small businesses reorganize under the new procedures that otherwise would have been liquidated. Further, expected creditor recoveries and post-bankruptcy survival rates are at least as high in Subchapter V as in similar traditional small business reorganizations. Our results show that the increased ability to preserve small businesses is not associated with a bias toward continuing unviable firms, and that creditors are not harmed by a shift in bargaining power toward small business owners.

We examine how U.S.-China geopolitical tensions affect the informational role of activist short sellers. Using hand-collected data on 183 reports targeting U.S.-listed Chinese firms from 2010 to 2020, we find that campaign activity increases during high-tension periods, driven by follow-up reports on already-targeted firms rather than new investigations. Reports released during these periods contain more negative language, are associated with larger but reversing price declines, and include fraud allegations less likely to be verified. These patterns suggest that geopolitical tensions shift activist short selling from price discovery toward bear-raid-type activity.

We study principals’ use of performance information to allocate human capital development resources to underperforming agents. We use proprietary data from a retail firm that sets uniform, noncalibrated performance targets to ensure consistent quality and customer experience across all stores. Unlike calibrated targets, uniform, noncalibrated targets do not account for heterogeneity in local conditions. Given that human capital development is costly, we predict and find that principals do not support all agents who underperform on noncalibrated targets. Instead, they use relative performance information and concentrate support on underperforming agents who outperform their geographical peers. In contrast, for calibrated targets, we find no evidence that principals rely on relative performance; agents who underperform calibrated targets are generally eligible for human capital support. Consistent with our assumption that relative performance is informative about returns to human capital investment, we find that support for underperforming agents who outperform their peers improves performance.

Prior studies predominantly examine fundamental performance‐driven explanations of loan renegotiations. We contrast with this work by investigating the improvement in secondary loan market trading conditions as a non‐fundamental driver of loan renegotiation. Exploiting a regression discontinuity design around the LSTA 100 Index reconstitution, we find that index‐included loans are around five times more likely to receive interest‐rate–reducing amendments than comparable loans just below the index inclusion threshold. Within‐loan‐package tests confirm that these renegotiations are not driven by changes in the borrower's fundamental performance. The threat of refinancing likely drives this effect, as the results are more pronounced when such threats are more credible.

Consider a setting where N players, partitioned into K observable types, form a directed network. Agents’ preferences over the form of the network consist of an arbitrary network benefit function (e.g., agents may have preferences over their network centrality) and a private, or dyadic, component which is additively separable in own links. This latter component allows for unobserved heterogeneity in the costs of sending and receiving links across agents (respectively out- and in- degree heterogeneity) as well as homophily/heterophily across the K types of agents. In contrast, the network benefit function allows agents’ preferences over links to vary with the presence or absence of links elsewhere in the network (and hence with the link formation behavior of their peers). In the null model, which excludes the network benefit function, links form independently across dyads in the manner described by Charbonneau (2017) among others. Under the alternative, there is interdependence across linking decisions (i.e., strategic interaction). We show how to test the null with power optimized in specific directions. These alternative directions include many common models of strategic network formation (e.g., “connections” models, “structural hole” models etc.). Our random utility specification induces an exponential family structure under the null which we exploit to construct a similar test which exactly controls size (despite the the null being a composite one with many nuisance parameters). We further show how to construct locally best tests for specific alternatives without making any assumptions about equilibrium selection. To make our tests feasible, we introduce a new MCMC algorithm for simulating the null distributions of our test statistics.

Deviations from covered interest rate parity (CIP) are often linked to limits to arbitrage, yet trading volumes surge during periods of apparent no-arbitrage violations. We show that these distortions stem from constraints on non-U.S. agents’ access to wholesale U.S. dollar markets and reflect a premium for unencumbered synthetic dollar funding: non-U.S. banks substitute secured USD borrowing with FX swaps to meet regulatory requirements. A shadow cost-augmented CIP condition holds, implying no riskless arbitrage. U.S. dealers extract rents on dollar provision while non-U.S. customers bear $10.4 billion in additional annual hedging costs. Our results illustrate how intermediary constraints segment global dollar funding.