Knowledge that Transforms

We document that the increasing polarization in Tobin’s Q within industries is closely connected to the growing divergence in rents and the emergence of superstar firms over the past four decades, while discount rates and growth rates did not exhibit the same increasing dispersion. We explain these industry polarization trends in an estimated general equilibrium model where each industry consists of large superstar oligopolists and small monopolistically competitive firms with endogenous transitions between them. Small firms make investments in speculative innovation to increase their probability of becoming superstars. Our model estimation finds that rising entry barriers in both small and superstar firms contribute to rising polarization in markups, but the rising barriers to creating small firms and increasing tastes for goods produced by superstars account for most of the divergence in Q. Stunting the creation of small firms generates greater incentives for speculative innovation, magnifying the impact of market power dispersion on industry polarization in Q.

Classical asset pricing models predict that optimizing investors exhibit extremely high demand elasticities, while empirical estimates are significantly lower—by three orders of magnitude. To reconcile this disparity, we introduce a novel decomposition of investor demand elasticity into two key components: “price pass-through”, which captures how price movements forecast returns, and “unspanned returns”, reflecting a stock’s lack of perfect substitutes. In a factor model framework, we show that unspanned returns become significant when models include “weak factors”. Classical models overestimate demand elasticity by assuming both very low unspanned returns and high price pass-throughs, assumptions that are inconsistent with empirical evidence.

We explore whether Quantitative Easing (QE) negatively affected the functioning of the treasury market. Focusing on the arbitrage between European sovereign bonds and their futures contracts, we show that the scarcity of treasuries created by QE led to a disconnect between the prices of identical assets. We identify three channels: reduced bond market liquidity, increased funding costs in the repo market, and a higher cost of carry. A change in a policy instrument allows us to identify scarcity as the main driver and rule out alternatives, such as balance sheet costs. Our results extend to other arbitrage relations involving treasuries.

A nationwide panic forced President Roosevelt to declare a banking holiday in March 1933. The government reopened banks sequentially using a process that sent noisy signals about banks’ health. New microdata reveals that the public responded to these signals. Deposits at rapidly reopened banks rebounded quicker than at comparable or stronger banks that reopened even a few days later. The stigma of late reopening shifted funds from stigmatized to lauded banks and among communities that they served. Despite persisting over a decade, the shift had no measurable impact on the rate at which localities recovered from the Great Depression.

We examine the survival prospects, employment profiles, and patient outcomes at private equity (PE)-acquired hospitals. Target hospitals maintain their survival rates while significantly reducing employment and wage expenditures. The number of core medical workers drops temporarily, but returns to its pre-acquisition level in the long run. However, administrative job and wage cuts persist over the long term, particularly at previously nonprofit hospitals. Using proprietary insurance claims data, we find no significant changes in patient demographics or inpatient prices at PE-acquired hospitals. While patient satisfaction declines, there is no evidence of increased patient mortality or readmission rates at PE-acquired hospitals.

Using daily banking and credit card data for thousands of households linked to U.S. publicly listed employers, we find novel evidence that firm-specific uncertainty persistently reduces future spending and spurs precautionary savings. A one-standard-deviation rise in option-implied firm volatility—akin to the S&P 500 VIX—predicts a $106 monthly spending drop (8 hours of wages) and a $193 increase in bank balances, reflecting notable cutbacks in typical non-durable goods and services. The mechanism operates through heightened household risks: firm uncertainty expands both income and consumption risk over the next year, with the largest effects among lower and top earners (notably the top 1%). Employers only partly shield earnings, while households only partly self-insulate consumption risk via smoothing channels. Detrimental uncertainty effects on households are stronger than firm stock price declines.

Using 2015–2019 intraday short sale data from CBOE, we show that shorting flows near the open, middle, and close all negatively predict future returns, but the shorting flows near the open and middle have stronger predictive power than shorting flows near the close. We relate our findings to three informed trading models with different predictions on the timing of the trades. The long term predictive power of shorting flows near the open and midday is consistent with Kyle’s (1985) model of steady trading; the intraday variation in shorting flows’ predictive power is more consistent with Holden and Subrahmanyam’s (1992) aggressive trading model, in the sense that predictive power of shorting flows is stronger when there is greater urgency to trade at open and when the securities lending market is more competitive; and the liquidity timing hypothesis from Collin-Dufresne and Fos (2016) is also supported by the finding that opening shorting flows increase for firms with better liquidity conditions.

We introduce in the theory of Gabaix and Maggiori (2015) a network structure to capture the complexity of the balance sheets of financial intermediaries, using the Leontief inverse-based centrality. We use this framework in a multi-country world with imperfect financial markets to study how currency risk premia are connected to financiers’ risk bearing capacity. Guided by the theory, we construct a Centrality Based Characteristic (CBC), based on the centrality of the trade imbalance network and variance–covariance matrix of currency returns. Sorting currencies on CBC generates a high Sharpe ratio, and the resulting excess returns reflect a novel source of predictability.

Trade credit is an important source of firm financing, yet its rich informational content pertaining to payment timeliness is under-explored in asset pricing. Using an extensive data set from a leading private information exchange on business payment performance, we study the effects of trade credit payment timeliness on stock returns. We document two distinct channels through which trade credit payment behavior impacts future stock returns — slow diffusion of information and risk stemming from a customer firm’s vertical bargaining power position in the supply chain. Consistent with our first channel, a sudden delay in a firm’s payment to its suppliers predicts significantly lower future returns for its stock. Consistent with our second channel, firms that pay their bills moderately late on a consistent basis relative to terms earn significantly higher stock returns.

Unlike labor income, human capital is inseparable from individuals and does not completely accrue to creditors. Therefore, human capital investment is more resilient to “debt overhang” than labor supply. We develop a dynamic model displaying this difference. We find that while both labor supply and human capital investment are hump-shaped in household indebtedness, human capital investment declines less aggressively as indebtedness builds up. Importantly, because human capital is only valuable when households expect to supply labor, the greater reduction in labor supply due to debt overhang back-propagates into ex-ante human capital investment. We provide empirical support for the model.