Knowledge that Transforms

This study analyzes the wide dispersion in bid-ask spreads across clients in over-the-counter (OTC) markets. Our data detailed data comprise a dealing bank's complete trading record in a major OTC contract and include client IDs, seven client types, and precise markups. Average spreads are lowest for hedge funds (<1 basis point, bp) and highest for individuals and for small and medium enterprises (>50 bps). Regression results suggest that the primary source of variation is clients’ execution efficiency, meaning their ability to minimize execution costs. Efficient trading, which can require investments in knowledge and technology, has three dimensions: reliance on low-cost platforms; familiarity with market technologies, conventions, and negotiating strategies; and breadth of dealing relationships. Relations between proxies for client execution efficiency and client incentives to invest, such as trade frequency, are consistent with rational inattention.

Rapid growth of stablecoins has raised concerns about issuer default and spillover risks. To assess these risks, we model a stablecoin issuer facing persistent demand shocks. Absent regulation, the issuer holds little capital and favours interest-bearing but illiquid bonds over cash. This exposes coin-holders to default risk and poses spillovers via bond fire-sales. How can regulation mitigate these risks? Capital and liquidity thresholds can help, especially when introduced as usable buffers. The thresholds can be breached, providing flexibility. However, breaches trigger additional redemptions that discipline the issuer. The thresholds operate through asymmetric channels: the liquidity threshold raises only cash, whereas the capital threshold increases both capital and cash. Both thresholds mitigate default and spillover risks, making them substitutes when either risk is targeted separately but complements when both risks are targeted jointly. We provide a two-way mapping that helps derive capital-liquidity threshold combinations implied by chosen risk targets (and vice-versa).

We study the interaction of expansionary rate-based monetary policy and quantitative easing, despite their concurrent implementation, by exploiting heterogeneous banks and the introduction of negative monetary-policy rates in a fragmented euro area. Quantitative easing increases credit supply less when banks’ funding costs do not decrease simultaneously. Using administrative data from Germany, we uncover that among banks selling their securities, central-bank reserves remain disproportionately with high-deposit banks that are constrained due to sticky customer deposits at the zero lower bound. Affected German banks lend relatively less to firms while increasing their interbank exposure in the euro area.

Startups face a trade-off between short-term profitability and long-term growth. Their cash flows are said to follow a so-called J-curve. The shape of the curve depends on investors’ financing capacity: their ability to sustain prolonged periods of negative cash flow. US venture capitalists are often believed to have greater financing capacity. We examine a large Swedish dataset with detailed cash flow information. Swedish startups backed by US venture capitalists experience deeper J-curves, with larger short-term losses and higher long-term sales, relative to those backed by non-US venture capitalists. These results are consistent with US venture capitalists having greater financing capacity: they can provide more funding directly and have better access to later-stage investors.

In credit markets where borrower types are observable, is it welfare-maximizing for a rate-setting institution to offer different rates to different borrower types, or to pool them at a common rate? Moral hazard favours separation; deadweight default costs favour pooling, since compressing rates reduces aggregate defaults through hazard rate heterogeneity. We derive the condition determining which force dominates: the ratio of default cost intensity to moral hazard intensity. We show that there is a single threshold value of this ratio such that separation strictly dominates below it, complete pooling strictly dominates above it, and the two are welfare-equivalent exactly at it, for every possible value of the ratio. The result does not depend on information being scarce: even though borrower types are observable throughout, pooling can still dominate separation when default costs are sufficiently large, provided the maintained compression and effort conditions we state precisely continue to hold; we conjecture, but do not formally establish, that the same logic extends to imperfect information if the threshold, recomputed for that weaker information structure, continues to be exceeded. The welfare criterion is utilitarian surplus; the efficiency claim is surplus maximisation, not Pareto improvement.

Using transaction data from a U.S. account aggregator, I study how household balance-sheet conditions drive within-person variation in marginal propensities to consume, repay debt, and invest across three rounds of pandemic stimulus. Using a machine learning imputation estimator, I measure the sensitivity of responses to time-varying financial circumstances. Spending responses fall as liquid assets increase, while debt repayments crowd out consumption only for those with binding borrowing limits. Transfers also encourage retail investment in stocks and cryptocurrencies at both intensive and extensive margins. The findings show how liquidity constraints and debt overhang influence the allocation of transfers across spending, deleveraging, and financial assets.

We propose a new framework to explain the factor structure in the full cross section of Treasury bond returns. Our method unifies non-parametric curve estimation with cross-sectional factor modeling. We identify smoothness as a fundamental principle of the term structure of returns. Our approach implies investable factors, which correspond to the optimal spanning basis functions in decreasing order of smoothness. Our factors explain the slope and curvature shapes frequently encountered in PCA. In a comprehensive empirical study, we show that the first four factors explain the time-series variation and risk premia of the term structure of excess returns. Cash flows are covariances as the exposure of bonds to factors is fully explained by cash flow information. We identify a state-dependent complexity premium. The fourth factor, which captures complex shapes of the term structure premium, substantially reduces pricing errors and pays off during recessions.

We study how fatal and nonfatal health shocks affect households’ ability to meet their financial obligations. We find that fatal shocks substantially increase the likelihood of default and that housing wealth plays a key role as a self-insurance mechanism. Surviving spouses who experience the largest income losses are more likely to sell their homes, and those without housing wealth face a sharply higher risk of debt collection. In the most financially vulnerable families, these shocks even generate intergenerational spillovers. In contrast, nonfatal health shocks lead to only modest increases in default risk. Taken together, our findings suggest that strengthening survivors’ benefits for households with limited resources could improve welfare across generations.

The sensitivity of the external finance premium to firms’ net-worth-to-capital ratio is central to the strength of the financial accelerator, yet direct firm-level evidence remains scarce. We estimate this elasticity using balance sheet and income statement data for Swiss nonfinancial firms over 1998–2016. To address the endogeneity of net worth, we employ two complementary instrumental variable strategies: one based on firms’ non-operating income and the other a shift-share design that interacts predetermined exposure to financial income with aggregate dividend returns. Mapping the estimated elasticity into the costly state verification framework as implemented by Bernanke et al. (1999) yields structural monitoring costs of about one quarter of firms’ gross return on capital, with estimates ranging from 0.15 to 0.35 across specifications. Our results provide direct firm-level support for the financial accelerator mechanism and imply monitoring costs of the same order of magnitude as the benchmark calibration of Bernanke et al. (1999).

We examine how in-person and virtual interactions shape mutual fund investment decisions using a comprehensive dataset of corporate site visits. Before COVID-19, fund pairs jointly attending in-person visits trade more similarly (by 20% of a standard deviation) than matched controls. The effect holds for stocks unrelated to the hosting firm and appears in firm-level, industry, geographic, and asset allocation decisions; it is stronger among managers with prior familiarity, similar seniority, and mixed gender. Stocks purchased by jointly visiting funds earn higher subsequent returns, indicating that these exchanges convey valuable information. Exploiting the exogenous shift to virtual communication induced by COVID-19, we find that in-person visits remain associated with correlated trading during the pandemic, whereas virtual visits have substantially weaker effects. A survey of fund managers confirms that site visits prompt information exchange, follow-up research, and portfolio adjustments. In-person interactions appear central to information acquisition; and virtual interactions do not easily replicate this function.