Social influence has been shown to create significant unpredictability in cultural markets, providing one potential explanation why experts routinely fail at predicting commercial success of cultural products. As a result, social influence is often presented in a negative light. Here, we show the benefits of social influence for cultural markets. We present a policy that uses product quality, appeal, position bias and social influence to maximize expected profits in the market. Our computational experiments show that our profit-maximizing policy leverages social influence to produce significant performance benefits for the market, while our theoretical analysis proves that our policy outperforms in expectation any policy not displaying social signals. Our results contrast with earlier work which focused on showing the unpredictability and inequalities created by social influence. Not only do we show for the first time that, under our policy, dynamically showing consumers positive social signals increases the expected profit of the seller in cultural markets. We also show that, in reasonable settings, our profit-maximizing policy does not introduce significant unpredictability and identifies "blockbusters". Overall, these results shed new light on the nature of social influence and how it can be leveraged for the benefits of the market.

A privately informed seller seeks to liquidate a portfolio to raise cash. Each asset’s liquidity thus depends on the impact of its sale on the value of the entire portfolio. We demonstrate the importance of cross-signaling and derive sufficient conditions for a liquidity “pecking order” that determines the order of sale. For assets backed by a common pool, liquidity naturally aligns with seniority. Finally, we extend the portfolio liquidation game to consider security design and demonstrate the optimality of pooling securities and selling senior tranches or debt secured by the pool, with retention increasing in asset quality or informational asymmetry.

A Bayesian technique with analyses of within-person processes at the level of the individual is presented. The approach is used to examine whether the patterns of within-person responses on a 12-trial simulation task are consistent with the predictions of ITA theory (Dweck, 1999). ITA theory states that the performance of an individual with an entity theory of ability is more likely to spiral down following a failure experience than the performance of an individual with an incremental theory of ability. This is because entity theorists interpret failure experiences as evidence of a lack of ability which they believe is largely innate and therefore relatively fixed; whilst incremental theorists believe in the malleability of abilities and interpret failure experiences as evidence of more controllable factors such as poor strategy or lack of effort. The results of our analyses support ITA theory at both the within- and between-person levels of analyses and demonstrate the benefits of Bayesian techniques for the analysis of within-person processes. These include more formal specification of the theory and the ability to draw inferences about each individual, which allows for more nuanced interpretations of individuals within a personality category, such as differences in the individual probabilities of spiraling. While Bayesian techniques have many potential advantages for the analyses of processes at the level of the individual, ease of use is not one of them for psychologists trained in traditional frequentist statistical techniques.

This paper considers the estimation and inference procedures for the case of a logistic panel regression model with interactive fixed effects, where multiple individual effects are allowed and the model is capable of capturing high-dimensional cross-section dependence. The proposed model also allows for heterogeneous regression coefficients. New Bayesian and non-Bayesian approaches are introduced to estimate the model parameters. We investigate the asymptotic behaviors of the estimated parameters. We show the consistency and asymptotic normality of the estimated regression coefficients and the estimated interactive fixed effects when both the cross-section and time-series dimensions of the panel go to infinity. We prove that the dimensionality of the interactive effects can be consistently estimated by the proposed information criterion. Monte Carlo simulations demonstrate the satisfactory performance of the proposed method. Finally, the method is applied to study the performance of New York City medallion drivers in terms of efficiency.

We develop a new technique to estimate vector autoregressions with a common factor error structure by quantile regression. We apply our technique to study credit risk spillovers among a group of 17 sovereigns and their respective financial sectors between January 2006 and December 2017. We show that idiosyncratic credit risk shocks propagate much more strongly in both tails than at the conditional mean or median. Furthermore, we develop a measure of the relative spillover intensity in the right and left tails of the conditional distribution that provides a timely aggregate measure of systemic financial fragility and that can be used for risk management and monitoring purposes.

This article introduces a new procedure for analyzing the quantile co-movement of a large number of financial time series based on a large-scale panel data model with factor structures. The proposed method attempts to capture the unobservable heterogeneity of each of the financial time series based on sensitivity to explanatory variables and to the unobservable factor structure. In our model, the dimension of the common factor structure varies across quantiles, and the explanatory variables is allowed to depend on the factor structure. The proposed method allows for both cross-sectional and serial dependence, and heteroscedasticity, which are common in financial markets. We propose new estimation procedures for both frequentist and Bayesian frameworks. Consistency and asymptotic normality of the proposed estimator are established. We also propose a new model selection criterion for determining the number of common factors together with theoretical support. We apply the method to analyze the returns for over 6000 international stocks from over 60 countries during the subprime crisis, European sovereign debt crisis, and subsequent period. The empirical analysis indicates that the common factor structure varies across quantiles. We find that the common factors for the quantiles and the common factors for the mean are different. Supplementary materials for this article are available online.

A country's total fertility rate (TFR) depends on many factors. Attributing changes in TFR to changes of policy is difficult, as they could easily be correlated with changes in the unmeasured drivers of TFR. A case in point is Australia where both pronatalist effort and TFR increased in lock step from 2001 to 2008 and then decreased. The global financial crisis or other unobserved confounders might explain both the reducing TFR and pronatalist incentives after 2008. Therefore, it is difficult to estimate causal effects of policy using econometric techniques. The aim of this study is to instead look at the structure of the population to identify which subgroups most influence TFR. Specifically, we build a stochastic model relating TFR to the fertility rates of various subgroups and calculate elasticity of TFR with respect to each rate. For each subgroup, the ratio of its elasticity to its group size is used to evaluate the subgroup's potential cost effectiveness as a pronatalist target. In addition, we measure the historical stability of group fertility rates, which measures propensity to change. Groups with a high effectiveness ratio and also high propensity to change are natural policy targets. We applied this new method to Australian data on fertility rates broken down by parity, age and marital status. The results show that targeting parity 3+ is more cost-effective than lower parities. This study contributes to the literature on pronatalist policies by investigating the targeting of policies, and generates important implications for formulating cost-effective policies.

CEO incentives have been the subject of great interest for human resource scholars. We explore the institutional context within which the CEO makes sense of their incentives. Our theory suggests that CEO equity incentives interact with institutional norms to influence foreign market entry choices. Specifically, we argue that CEOs will weigh the risk bearing created by equity incentives, along with the consequences of legitimacy loss, when deciding whether to deviate from institutional norms when internationalizing. In doing so, we advance human resource literature by demonstrating that CEO responses to incentives are influenced by institutional norms and that CEOs' decisions to deviate from institutional norms are shaped by their incentives. We find support for our framework in the analysis of the stake taken by acquirers in 4,184 cross‐border acquisitions.

As colleagues and collaborators, we reflect on the work and legacy of Peter Carnevale, currently professor at the University of Southern California, and recipient of the 2002 Jeffrey Z. Rubin Theory-to-Practice Award of the International Association for Conflict Management (IACM). We review Carnevale’s main contributions, including his work on time pressure and surveillance, strategies for mediation, emotions in negotiation, and the use and integration of distinct methods for studying conflict and negotiation. We share personal anecdotes from our time as PhD students and collaborators with Peter Carnevale, and we touch on lessons learned for doing science and mentoring the next generation.

A growing body of research on moral markets—sectors whose raison d’être is to create social value by offering market solutions to social and environmental issues—has offered critical insights into the emergence and growth of these sectors. Less is known, however, about why some firms enter moral markets while others do not. Drawing from research on market entry, organizational identity, and social movements, we develop a theory that highlights the potential of organizational identity to explain variation in entry into moral markets. We then expand our framework by theorizing about contingencies that alter the shape of the relationship between organizational identity and market entry: the flexibility of the organizations’ identity, the type, and orientation of the social movement supporting the moral market, and the mode of market entry (de novo vs de alio). Finally, we discuss the contributions of our framework and opportunities for its extension.

Relatively little is known about how the composition of individual conflict management styles affects group functioning. This is unfortunate because, specifically in short-term project groups, this conflict management style composition may be pivotal given the strong task focus rather than establishing norms to guide or manage conflict. Therefore, we examined whether conflict style asymmetry within short-term project groups affects the link between intragroup conflict and the performance of groups. Data were collected among short-term project groups and the results suggest that asymmetry in both forcing and the problem-solving conflict management styles moderates the negative effect of task, relationship, and process conflicts on the performance of groups. We offer a discussion of the implications of these findings.