Knowledge that Transforms

We examine voluntary disclosure decisions when firms are uncertain about audience preferences and are risk averse. In contrast to classic “unraveling” results, some firms remain silent in equilibrium. Silence is safer than disclosure; silence reduces the sensitivity of a firm’s payoff to audience preferences. Increases in firm (audience) risk-aversion reduce (increase) disclosure. Our model explains why some firms do not disclose earnings breakdowns, executive compensation, or Environmental, Social, and Governance (ESG) performance when they face diverse audiences, and why they disclose less under regulatory rules mandating that disclosure be entirely public.

We investigate equilibrium debt dynamics for a firm that cannot commit to a future debt policy and is subject to a fixed restructuring cost. We formally characterize equilibria when the firm is not required to repurchase outstanding debt prior to issuing additional debt. For realistic values of issuance costs and debt maturity, the no-commitment policy generates tax benefits that are similar to those obtained by a benchmark policy with commitment. For positive but arbitrarily small issuance costs, there are maturities for which shareholders extract essentially the entire claim to cash-flows.

This paper investigates whether multivariate crash risk (MCRASH), defined as exposure to extreme realizations of multiple systematic factors, is priced in the cross-section of expected stock returns. We derive an extended linear model with a positive premium for MCRASH, and we empirically confirm that stocks with high MCRASH earn significantly higher future returns than stocks with low MCRASH. The premium is not explained by linear factor exposures, alternative downside risk measures, or stock characteristics. Extending market-based definitions of crash risk to other well-established factors helps to determine the cross-section of expected stock returns without further expanding the factor zoo.

I present closed-form solutions for prices, portfolios, and beliefs in a model where four types of investors trade assets over time: naive investors who learn via a social network, “fanatics” possibly spreading fake news, and rational short- and long-term investors. I show that fanatic and rational views dominate over time, and their relative importance depends on their following by influencers. Securities markets exhibit social network spillovers, large effects of influencers and thought leaders, bubbles, bursts of high volume, price momentum, fundamental momentum, and reversal. The model sheds new light on the GameStop event, historical bubbles, and asset markets more generally.

We study how mutual fund managers gain an edge in selecting stocks in an era of globalization. We use textual analysis to construct a measure that captures a mutual fund's offshore exposure concentration through holding US multinational firms. We find that funds with a higher offshore concentration index (OCI) perform significantly better, with the difference in four-factor alpha between the top and bottom deciles amounting to 2.95% per annum. Fund managers’ overweighting of firms with operations in certain countries can be partly attributed to their foreign ethnicity. High OCI fund managers have an information advantage regarding firms’ fundamentals, such as earnings.

We show that reaching for yield—a tendency to take more risk when the real interest rate declines while the risk premium remains constant—results from imposing a sustainable spending constraint on an otherwise standard infinitely lived investor with power utility. When the interest rate is initially low, reaching for yield intensifies. The sustainable spending constraint also affects the response of risk-taking to a change in the risk premium, which can even change sign. In a variant of the model where the sustainable spending constraint is formulated in nominal terms, low inflation also encourages risk-taking.

We develop a dynamic model of a platform economy where tokens serve as a means of payment among platform users and are issued to finance investment in platform productivity. Tokens are optimally rewarded to platform owners when token supply (normalized by productivity) is low and burnt to boost franchise value when the normalized supply is high. Although token price is determined in a liquid market, the platform’s financial constraint generates an endogenous token issuance cost that causes underinvestment through the conflict of interest between insiders (owners) and outsiders (users). Blockchain technology mitigates underinvestment by addressing the owners’ time inconsistency problem.

We propose a “debt view” to explain the dominant international role of the dollar. Within a simple capital-structure model with debt-currency choice, we show that the “dominant currency” is the one that (1) depreciates in global downturns over horizons of typical debt maturity and (2) has the steepest nominal yield curve. Empirically, we show the dollar fits this description better than other major currencies. The debt view can explain dollar-debt-issuance patterns over the past two decades. It also offers insights into the future of the dominance of the dollar in the aftermath of the COVID-19 crisis.

In sharp contrast to most previous crisis episodes, the Treasury market experienced severe stress and illiquidity during the COVID-19 crisis, raising concerns that the safe-haven status of US Treasuries may be eroding. We document large shifts in Treasury ownership and temporary accumulation of Treasury and reverse repo positions on dealer balance sheets during this period. We build a dynamic equilibrium asset pricing model in which dealers subject to regulatory balance sheet constraints intermediate demand/supply shocks from habitat agents and provide repo financing to levered investors. The model predicts that Treasury inconvenience yields, measured as the spread between Treasuries and overnight-index swap rates (OIS), as well as spreads between dealers’ reverse repo and repo rates, should be highly positive during the COVID-19 crisis, as is confirmed in the data. The same model framework, adapted to the institutional setting in 2007–2009, can also explain the negative Treasury-OIS spread observed during the Great Recession.

This paper provides a comprehensive assessment of financial intermediation and the economic effects of the Paycheck Protection Program (PPP), a large and novel small business support program that was part of the initial policy response to the COVID-19 pandemic in the US. We use loan-level microdata for all PPP loans and high-frequency administrative employment data to present three main findings. First, banks played an important role in mediating program targeting, which helps explain why some funds initially flowed to regions that were less adversely affected by the pandemic. Second, we exploit regional heterogeneity in lending relationships and individual firm-loan matched data to study the role of banks in explaining the employment effects of the PPP. We find the short- and medium-term employment effects of the program were small compared to the program’s size. Third, many firms used the loans to make non-payroll fixed payments and build up savings buffers, which can account for small employment effects and likely reflects precautionary motives in the face of heightened uncertainty. Limited targeting in terms of who was eligible likely also led to many inframarginal firms receiving funds and to a low correlation between regional PPP funding and shock severity. Our findings illustrate how business liquidity support programs affect firm behavior and local economic activity, and how policy transmission depends on the agents delegated to deploy it.