Publications

Evaluating how factor premia vary over time and across asset classes is challenging due to limited time series data, especially outside of U.S. equities. We examine four prominent factors across six asset classes over a century. We find little evidence for arbitrage activity influencing returns, though some novel evidence of overfitting biases. We identify meaningful time variation in factor risk-adjusted returns that appears unrelated to macroeconomic risks, supporting other theories of dynamic return premia. Attempting to capture this variation, we evaluate various factor timing strategies, but find relatively modest predictability that likely fails to overcome implementation frictions.

Theories of authenticity usually try to explain what leads consumers to see something as authentic. Here, we address the inverse question instead: What makes a brand, individual, or product seem inauthentic? This shift in focus reveals a distinct psychology that is more than just the absence or inverse of responses to authenticity. Whereas authenticity typically confers meaning and value, invoking inauthenticity typically implies the detection of a moral violation. Specifically, consumers judge an entity to be inauthentic if they perceive a mismatch between what that entity claims to be (e.g., a socially responsible apparel brand, 100% orange juice) and what it really is upon closer scrutiny. Such judgments give rise to a powerful, non-compensatory reactance we term inauthenticity aversion. We segment inauthenticity violations into three principle types: deceptions, ulterior motives, and adulterations. This conceptualization allows us to capture a wide variety of inauthenticity cases and outline psychological commonalities across them. It also helps to explain the powerful outrage consumers display at perceived inauthenticity and illuminates potential hazards in common marketing approaches.

In this paper, we study a model of information consumption in which consumers sequentially interact with a platform that offers a menu of signals (posts) about an underlying state of the world (fact). At each time, incapable of consuming all posts, consumers screen the posts and only select (and consume) one from the offered menu. We show that, in the presence of uncertainty about the accuracy of these posts and as the number of posts increases, adverse effects, such as slow learning and polarization, arise. Specifically, we establish that, in this setting, bias emerges as a consequence of the consumer’s screening process. Namely, consumers, in their quest to choose the post that reduces their uncertainty about the state of the world, choose to consume the post that is closest to their own beliefs. We study the evolution of beliefs, and we show that such a screening bias slows down the learning process and that the speed of learning decreases with the menu size. Further, we show that the society becomes polarized during the prolonged learning process even in situations in which the society’s belief distribution was not a priori polarized.

In this article we argue addressing entry barriers created by network effects is critical to remedying a monopolization violation in a social network market (e.g. Facebook). For a social network, interoperability is likely a necessary, but not necessarily a sufficient, condition for an effective remedy. Mandatory interoperability based on robust and effective rules could overcome the network effects that protect the incumbent from entry, maximizing the potential for new entrants to enter at minimal cost, compete in the market, and take share from the incumbent. This remedy could be ordered in addition to other relief such as a divestiture, and indeed could be complementary to it, or stand on its own. In today’s internet-based network markets, interoperability carries no incremental costs such as dedicated wires and machines that were true of the telecom interoperability of past decades. Its main cost is the establishment of an open standard to exchange commonly used functionalities (e.g. text, images) of social networks. If this remedy were ordered by a court after a finding of antitrust liability, the standard should be overseen by an agency to ensure it serves to protect competition, lower entry barriers, and erode market power. Entrants who wish to interoperate with the incumbent could demonstrate adherence to privacy and security standards and receive royalty-free licenses.

This paper argues incumbent firms may acquire innovative targets solely to discontinue the target's innovation projects and preempt future competition. We call such acquisitions "killer acquisitions." We develop a model illustrating this phenomenon. Using pharmaceutical industry data, we show that acquired drug projects are less likely to be developed when they overlap with the acquirer's existing product portfolio, especially when the acquirer's market power is large due to weak competition or distant patent expiration. Conservative estimates indicate 5.3 percent to 7.4 percent of acquisitions in our sample are killer acquisitions. These acquisitions disproportionately occur just below thresholds for antitrust scrutiny.

Policy-makers are increasingly turning to behavioural science for insights about how to improve citizens’ decisions and outcomes1. Typically, different scientists test different intervention ideas in different samples using different outcomes over different time intervals2. The lack of comparability of such individual investigations limits their potential to inform policy. Here, to address this limitation and accelerate the pace of discovery, we introduce the megastudy—a massive field experiment in which the effects of many different interventions are compared in the same population on the same objectively measured outcome for the same duration. In a megastudy targeting physical exercise among 61,293 members of an American fitness chain, 30 scientists from 15 different US universities worked in small independent teams to design a total of 54 different four-week digital programmes (or interventions) encouraging exercise. We show that 45% of these interventions significantly increased weekly gym visits by 9% to 27%; the top-performing intervention offered microrewards for returning to the gym after a missed workout. Only 8% of interventions induced behaviour change that was significant and measurable after the four-week intervention. Conditioning on the 45% of interventions that increased exercise during the intervention, we detected carry-over effects that were proportionally similar to those measured in previous research3,4,5,6. Forecasts by impartial judges failed to predict which interventions would be most effective, underscoring the value of testing many ideas at once and, therefore, the potential for megastudies to improve the evidentiary value of behavioural science.

This paper proposes a framework for studying competitive mixed bundling with an arbitrary number of firms. We examine both a firm's incentive to introduce mixed bundling and equilibrium tariffs when all firms adopt the mixed-bundling strategy. In the duopoly case, relative to separate sales, mixed bundling has ambiguous impacts on prices, profit and consumer surplus; with many firms, however, mixed bundling typically lowers all prices, harms firms and benefits consumers.

This article presents an overview of methods developed for the modeling and control of local coronavirus outbreaks. The article reviews early transmission dynamics featuring exponential growth in infections, and links this to a renewal epidemic model where the current incidence of infection depends upon the expected value of incidence randomly lagged into the past. This leads directly to simple formulas for the fraction of the population infected in an unmitigated outbreak, and reveals herd immunity as the solution to an optimization problem. The model also leads to direct and easy-to-understand formulas for aligning observable epidemic indicators such as cases, hospitalizations and deaths with the unobservable incidence of infection, and as a byproduct leads to a simple first-order approach for estimating the effective reproduction number . The model also leads naturally to direct assessments of the effectiveness of isolation in preventing the spread of infection. This is illustrated with application to repeat asymptomatic screening programs of the sort utilized by universities, sports teams and businesses to prevent the spread of infection.