Knowledge that Transforms

We derive bounds on the rational variation in option‐implied beliefs about market returns. While risk preferences distort option‐implied (or risk‐neutral ) beliefs away from subjective beliefs, one can nonetheless bound risk‐neutral belief movement under a general assumption on the stochastic discount factor. The resulting test requires no knowledge of the objective distribution and allows significantly more flexibility in discount rates than standard volatility tests. Implementing our test empirically using index options, we find that there is so much movement in risk‐neutral beliefs that the bounds are routinely violated. Our results imply significant excess index‐price volatility.

Online experiments have surged in popularity, but how credible are their published results? We examine the universe of hypotheses tested on Amazon Mechanical Turk and reported in leading journals between 2010 and 2021. We find evidence of widespread p-hacking, publication bias, and under-powered studies. The extent of the problems varies substantially across fields, with marketing particularly badly afflicted and little evidence of distortion in economics. We explore correlates of increased credibility and compare the online results to laboratory results from the same outlets, finding similar distortions in both, with bunching just above the significance threshold more pronounced on MTurk.

Using online job postings data, we explore whether auditors adjust their human capital in response to clients' cyber breach incidents. We find that audit offices increase their demand for cybersecurity specialists after their clients' cyber breaches, implying that cyber breaches change not only client risk but also their auditor's production function. Consistent with expectations, we document that this impact is larger when breaches involve their own clients (rather than those of peer offices within the same audit firm) and when breaches directly involve financial information. Our evidence holds for both cyber‐focused and non‐cyber‐focused offices, highlighting the broad impact of cybersecurity risks on audit practices. Additionally, we find that audit offices with relatively high investment in cybersecurity human capital are better able to preserve their market share among clients in high‐cyber‐risk industries after a client's cyber breach.

Decisions are typically made by drawing on multiple sources of information, yet the correlation among these sources is often hard to assess. We study robustly optimal strategies—those that maximize the worst-case payoff guarantee across all correlation structures. With two states and two actions, the robustly optimal strategy is strikingly simple: use only the best information source and ignore the rest. With more actions, a robustly optimal strategy decomposes the problem into local comparisons and assigns each comparison to the source that is best at that comparison. With more states, the same specialization logic survives through a concavification characterization: the decision problem is decomposed into payoff-relevant components, and each component is assigned to its best source. These results offer a new rationale for why ignoring information can be optimal and highlight the benefit of using specialized information sources when correlations are ambiguous.

We demonstrate how private equity (PE) promotes nonbank lending by substituting for bank monitoring. Relative to non-PE-backed loans, PE-backed loans exhibit lower bank monitoring, smaller loan shares retained by lead banks, and larger shares held by nonbanks. The substitution is strongest when sponsors have greater incentives to engage with portfolio firms, is not associated with weaker loan performance, and persists during borrower distress. Our findings suggest that PE sponsors’ active engagement—through monitoring and support in distress—reduces banks’ need for monitoring and information production, enabling them to retain less skin in the game and sell loans to nonbanks.

Using US Supreme Court’s narrow-decision on Shelby v. Holder as a shock that diluted voting rights of Black Americans in covered counties, we document the relationship between political voice and economic decision-making. We show fewer Black Americans buy homes after their de-facto disenfranchisement, reflected through lower mortgage applications. Among those who apply for mortgages, there is a flight to Black lenders. Leveraging individual-level survey data, we show confidence in government and financial institutions plays a significant role in driving these effects. Our findings demonstrate that the effects of disenfranchisement extend beyond the ballot box to fundamental economic decisions like homeownership.

Organizational learning (OL) is a critical organizational capability. Yet designing management control (MC) that effectively supports OL is challenging, as learning outcomes are often intangible and unfold over extended time horizons. Employing situational strength theory, we examine combinations of MC practices that affect OL contingent on environmental uncertainty. Drawing on a survey of 210 senior business unit controllers, we use fuzzy-set Qualitative Comparative Analysis (fsQCA) to identify multiple combinations of MC practices that achieve high OL in different uncertainty contexts. In a subsequent step, we examine whether the situational strength of certain combinations of MC practices is associated with OL. Results show that in a low-uncertainty environment, the combined use of diverse performance measures and social controls, as well as performance pay and a mechanistic administrative structure, have a synergetic effect on OL. In a high-uncertainty context, the combined use of measure diversity and deliberate formal strategic planning is beneficial for achieving OL. Our results suggest that the effectiveness of MC practices for OL depends on aligning MC practices with the internal as well as the external context.

We show that leading investor disagreement proxies have near-zero cross-correlation – making disagreement pricing inferences challenging. We develop a frictionless model that generates overpricing from latent disagreement, jointly rationalizes major proxies, and generates new testable predictions. Equilibrium interrelationships motivate a new disagreement measure, DIS, which is more predictive of returns cross-sectionally than major proxies and more consistently predictive across macroeconomic regimes. We provide evidence that the friction-based channel of Miller (1977) and a frictionless mechanism coexist and are empirically separable. DIS also provides a micro-founded, disagreement-based account of the IVOL puzzle, absorbing IVOL’s predictability while revealing its regime and friction dependence.

We develop a model to study the efficiency of socially responsible investing (SRI) as a mechanism to control firms' externalities. When SRI is not too popular, responsible investors favor strategies that lead to a concentration of SRI in a subset of firms in the economy. This concentration can mitigate coordination issues in adopting green technologies, but it can also crowd out the green investments of excluded firms and increase the price of green products. In equilibrium, responsible investors continue to favor concentration even as SRI becomes more popular, and concentrate the most when concentration is least desirable.