Color me moral: White and black product colors influence prosocial behaviors

There are “moral meanings” that people ascribe to objects in white and black colors. Namely, it seems that people have been conditioned to see objects in white color as potentially “morally good” and those in black color as potentially “bad.” In the current inquiry, we would therefore hypothesize that consumers see buying a product in white color as an act that is morally good and buying a product in black color as an act that is morally bad. If so, then, in accordance with the moral regulation theory, those who buy white‐colored products should feel licensed to behave less prosocially afterward, while those who buy black‐colored products should be more prosocial as they feel a need to compensate for their initial misconduct. We investigate such a hypothesis in six studies, examining prosociality after buying white‐ or black‐colored products. The results are consistent with our hypothesizing and highlight a moral credentials framework in particular in explaining why the effect occurs. Consequently, product colors do not only satisfy the diversity of consumer tastes but they also impact consumers’ prosocial behavior well‐beyond product choice and outside of retail domains.     

Payments for Order Flow on Nasdaq

We present a model of Nasdaq that includes the two ways in which marketmakers compete for order flow: quotes and direct payments. Brokers in our model can execute small trades through a computerized system, preferencing arrangements with marketmakers, or vertical integration into market making. The comparative statics in our model differ from those of the traditional model of dealer markets, which does not capture important institutional features of Nasdaq. We also show that the empirical evidence is inconsistent with the traditional model, which suggests that preferencing and vertical integration are important components in understanding Nasdaq.     

Accuracy of management and security analysts' forecasts: Additional evidence

This paper provides further support for findings in studies by Basi, Carey, and Twark [2] and Ruland [5] which indicated no statistically significant superiority of management over analysts in forecasting earnings per share. These somewhat surprising findings are seen to flow from several possible sources. Lack of superior management forecasting performance may reflect (1) a considerable sharing of the forecast or forecast-related information by management with analysts, or (2) firm-specific data (to which management is more privy) may be less important in forecasting performance than data on economy-wide movements.     

Modelling and Estimation for Bivariate Financial Returns

Maximum likelihood estimates are obtained for long data sets of bivariate financial returns using mixing representation of the bivariate (skew) Variance Gamma (VG) and two (skew) t distributions. By analysing simulated and real data, issues such as asymptotic lower tail dependence and competitiveness of the three models are illustrated. A brief review of the properties of the models is included. The present paper is a companion to papers in this journal by Demarta & McNeil and Finlay & Seneta.