This paper studies the impact that ethnic innovators have on the global activities of U.S. firms by analyzing detailed data on patent applications and on the operations of the foreign affiliates of U.S. multinational firms. The results indicate that increases in the share of a firm's innovation performed by inventors of a particular ethnicity are associated with increases in the share of that firm's affiliate activity in countries related to that ethnicity. Ethnic innovators also appear to facilitate the disintegration of innovative activity across borders and to allow U.S. multinationals to form new affiliates abroad without the support of local joint venture partners. This paper was accepted by Bruno Cassiman, business strategy.

We analyze a new auction format in which bidders pay a fee each time they increase the auction price. Bidding fees are the primary source of revenue for the seller but produce the same expected revenue as standard auctions (assuming risk-neutral bidders). If risk-loving preferences are incorporated in the model, expected revenue increases. Our model predicts a particular distribution of ending prices, which we test against observed auction data. The degree of fit depends on how unobserved parameters are chosen; in particular, a slight preference for risk has the biggest impact in explaining auction behavior, suggesting that pay-to-bid auctions are a mild form of gambling. This paper was accepted by Peter Wakker, decision analysis.

This paper is concerned with systemic risk in an interbank market, modelled as a directed graph of interbank obligations. This builds on the modelling paradigm of Eisenberg and Noe [Eisenberg L, Noe TH (2001) Systemic risk in financial systems. Management Sci. 47(2):236–249] by introducing costs of default if loans have to be called in by a failing bank. This immediately introduces novel and realistic effects. We find that, in general, many different clearing vectors can arise, among which there is a greatest clearing vector, arrived at by letting banks fail in succession until only solvent banks remain. Such a collapse should be prevented if at all possible. We then study situations in which consortia of banks may have the means and incentives to rescue failing banks. This again departs from the conclusions of the earlier work of Eisenberg and Noe, where in the absence of default losses there would be no incentive for solvent banks to rescue failing banks. We conclude with some remarks about how a rescue consortium might be constructed. This paper was accepted by Wei Xiong, finance.

We consider two ways to aggregate expert opinions using simple averages: averaging probabilities and averaging quantiles. We examine analytical properties of these forecasts and compare their ability to harness the wisdom of the crowd. In terms of location, the two average forecasts have the same mean. The average quantile forecast is always sharper: it has lower variance than the average probability forecast. Even when the average probability forecast is overconfident, the shape of the average quantile forecast still offers the possibility of a better forecast. Using probability forecasts for gross domestic product growth and inflation from the Survey of Professional Forecasters, we present evidence that both when the average probability forecast is overconfident and when it is underconfident, it is outperformed by the average quantile forecast. Our results show that averaging quantiles is a viable alternative and indicate some conditions under which it is likely to be more useful than averaging probabilities. This paper was accepted by Peter Wakker, decision analysis.

Systemic risk refers to the risk of collapse of an entire complex system as a result of the actions taken by the individual component entities or agents that comprise the system. Systemic risk is an issue of great concern in modern financial markets as well as, more broadly, in the management of complex business and engineering systems. We propose an axiomatic framework for the measurement and management of systemic risk based on the simultaneous analysis of outcomes across agents in the system and over scenarios of nature. Our framework defines a broad class of systemic risk measures that accomodate a rich set of regulatory preferences. This general class of systemic risk measures captures many specific measures of systemic risk that have recently been proposed as special cases and highlights their implicit assumptions. Moreover, the systemic risk measures that satisfy our conditions yield decentralized decompositions; i.e., the systemic risk can be decomposed into risk due to individual agents. Furthermore, one can associate a shadow price for systemic risk to each agent that correctly accounts for the externalities of the agent's individual decision making on the entire system. This paper was accepted by Gérard P. Cachon, stochastic models and simulation.

This paper shows that the effect of different distribution channel structures on product quality depends on the type of consumer heterogeneity and its distribution in a market. When consumer heterogeneity is uniformly distributed either vertically on willingness to pay or horizontally on transaction costs, a manufacturer may provide the same or lower product quality in a decentralized channel than in a centralized channel. In contrast, when consumer heterogeneity follows a more general distribution on willingness to pay, under certain conditions, the manufacturer may provide higher product quality in a decentralized channel than in a centralized channel. Decentralization also may lead to a higher product quality if consumer heterogeneity is uniformly distributed both vertically and horizontally, but not if consumer heterogeneity is uniformly distributed vertically on each of two product-quality attributes. Additionally, competition at the retail level may amplify these findings. This paper was accepted by J. Miguel Villas-Boas, marketing.

Some environments constrain the information that managers and decision makers can observe. We examine judgment in censored environments where a constraint, the censorship point, systematically distorts the observed sample. Random instances beyond the censorship point are observed at the censorship point, whereas uncensored instances are observed at their true value. Many important managerial decisions occur in censored environments, such as inventory, risk taking, and employee evaluation decisions. In this research, we demonstrate a censorship bias—individuals tend to rely too heavily on the observed censored sample, biasing their belief about the underlying population. We further show that the censorship bias is exacerbated for higher degrees of censorship, higher variance in the population, and higher variability in the censorship points. In four studies, we find evidence of the censorship bias across the domains of demand estimation and sequential risk taking. The bias causes individuals to make costly decisions and behave in an overly risk-averse manner. This paper was accepted by Teck Ho, judgment and decision making.