Low-income households with proximate access to payday loans exhibit greater economic distress, higher take-up of food assistance benefits, and greater delinquency on child support payments than peers without proximate loan access. These findings suggest that borrowing can exacerbate distress, leading borrowers to use transfer programs and to prioritize payday loan payments over other liabilities like child support. In that way, payday lending produces negative externalities—costs imposed on taxpayers that fund transfer programs and nonresident family members that fail to receive child support. Received August 13, 2014; editorial decision December 5, 2016 by Editor Alexander Ljungqvist.

I study asset price amplification in an asymmetric information model. Entrepreneurs issue debt to finance investments in a physical asset. They have private information about their success probabilities. For a given debt level, higher asset prices require entrepreneurs to invest more of their own funds. This makes bad entrepreneurs more reluctant to mimic good ones; as a result, good entrepreneurs increase their equilibrium leverage and invest more, and this amplifies the initial asset price increase. This model generates predictions about the credit market that are qualitatively consistent with existing evidence. Received April 24, 2015; editorial decision June 15, 2016 by Editor Itay Goldstein.

We examine the accuracy and contribution of the Merton distance to default (DD) model, which is based on Merton's (1974) bond pricing model. We compare the model to a “naïve” alternative, which uses the functional form suggested by the Merton model but does not solve the model for an implied probability of default. We find that the naïve predictor performs slightly better in hazard models and in out-of-sample forecasts than both the Merton DD model and a reduced-form model that uses the same inputs. Several other forecasting variables are also important predictors, and fitted values from an expanded hazard model outperform Merton DD default probabilities out of sample. Implied default probabilities from credit default swaps and corporate bond yield spreads are only weakly correlated with Merton DD probabilities after adjusting for agency ratings and bond characteristics. We conclude that while the Merton DD model does not produce a sufficient statistic for the probability of default, its functional form is useful for forecasting defaults.

When agents can learn about their abilities as active investors, they rationally “trade to learn ” even if they expect to lose from active investing. The model used to develop this insight draws conclusions that are consistent with empirical study of household trading behavior: Households ’ portfolios underperform passive investments; their trading inten-sity depends on past performance; and they begin by trading small sums of money. Using household data from Finland, the article estimates a structural model of learning and trad-ing. The estimated model shows that investors trade to learn even if they are pessimistic about their abilities as traders. It also demonstrates that realized returns are significantly downward-biased measures of investors ’ true abilities. (JEL D10, G11) While most households adjust their stock portfolios only infrequently, some trade very actively and underperform passive investments.1 I ask whether a model in which investors rationally learn from experience can explain this be-havior, and, if so, what the model tells us about households ’ beliefs. In my model, investors are uncertain about their abilities and learn as they trade. If the value of observing another signal is high, then an investor trades even if she expects to lose money, thus apparently trading “too much. ” If a trade is successful, the investor infers skill and subsequently trades more. If an investor loses money, she will infer less skill and subsequently trade less. After enough losses, she stops trading altogether. Investors who are especially uncertain about their abilities trade small amounts early in their careers until

This paper examines how external governance pressure affects the type of debt that firms issue. Consistent with a governance mechanism substitution effect, we find that an exogenous increase (decrease) in governance pressure from the product (takeover) market has a significant negative (positive) impact on the use of bank (public debt) financing over public debt (bank loan) issuance. Tests using changes in the strictness of loan covenants provide corroborative evidence. These findings are consistent with the notion that firms endogenously substitute governance mechanisms and that demand for creditor governance depends on the relative strength of alternative external governance mechanisms. Received May 18, 2016; editorial decision November 11, 2017 by Editor David Denis.

We study dividend payouts when banks face coordination-based rollover crises. Banks in the model can use dividends to both risk shift and signal their available liquidity to short-term lenders, thus, influencing the lenders’ actions. In the unique equilibrium both channels induce banks to pay higher dividends than in the absence of a rollover crisis. In our model banks exert an informational externality on other banks via the inferences and actions of lenders. Optimal dividend regulation that corrects this externality and promote financial stability includes a binding cap on dividends. We also discuss testable implications of our theory.

Using data spanning the twentieth century, we show that the majority of accounting-based return anomalies, including investment, are most likely an artifact of data snooping. When examined out-of-sample by moving either backward or forward in time, the average returns and Sharpe ratios of most anomalies decrease, whereas their volatilities and correlations with other anomalies increase. The few anomalies that do persist out-of-sample correlate with the shift from investment in physical capital to intangible capital and the increasing reliance on debt financing over the twentieth century. Received November 25, 2016; editorial decision September 23, 2017 by Editor Andrew Karolyi.

We propose a statistical model of heterogeneous beliefs wherein investors are represented as different machine learning model specifications. Investors form return forecasts from their individual models using common data inputs. We measure disagreement as forecast dispersion across investor-models (MFD). Our measure aligns with analyst forecast disagreement but more powerfully predicts returns. We document a large and robust association between belief disagreement and future returns. A decile spread portfolio that sells stocks with high disagreement and buys stocks with low disagreement earns a value-weighted return of 13% per year. Further analyses suggest MFD-alpha is mispricing induced by short-sale costs and limits-to-arbitrage.

We study how Institutional Shareholder Services (ISS) affect firms’ engagement with shareholders. Our analyses exploit a quasi-natural experiment using say-on-pay voting outcomes near a threshold that triggers ISS to review engagement activities. Firms receiving ISS treatment exhibit swift and substantive increases in extensive and intensive margins of engagement, especially when their boards have higher agency conflicts and directors are more likely to lose voting support from ISS. Increases in engagement persist over time, and shareholders appear to value the increased engagement. Collectively, we shed light on an unexplored channel through which ISS positively influences firms’ governance and information environments.

Initial coin offerings (ICOs) have emerged as a new mechanism for entrepreneurial finance, with parallels to initial public offerings, venture capital, and presale crowdfunding. In a sample of more than 1,500 ICOs that collectively raise $12.9 billion, we examine which issuer and ICO characteristics predict successful real outcomes (increasing issuer employment and avoiding enterprise failure). Success is associated with disclosure, credible commitment to the project, and quality signals. An instrumental variables analysis finds that ICO token exchange listing causes higher future employment, indicating that access to token liquidity has important real consequences for the enterprise.