Individual versus group spot price forecasting in the international petroleum market: A case study

This paper utilizes the conventional statistical tests associated with the rational expectations hypothesis so as to compare the relative accuracy of individual versus group forecasting within the organization. In order to maintain comparability between forecasting regimens the study employs like information sets for the two prediction methods. Using the rational expectations tests as criteria, the statistical results show group forecasts inferior to individually produced predictions These findings imply that group-produced forecasting accuracy may be hampered by the psychological interaction associated with consensus behavior. Conversely, we find forecasting accuracy improves when predictions are elicited from individuals in an isolated laboratory-like setting.     

An empirical comparison of neural network and logistic regression models

The purpose of this paper is to critically compare a neural network technique with the established statistical technique of logistic regression for modeling decisions for several marketing situations. In our study, these two modeling techniques were compared using data collected on the decisions by supermarket buyers whether to add a new product to their shelves or not. Our analysis shows that although neural networks offer a possible alternative approach, they have both strengths and weaknesses that must be clearly understood.     

Testing alone is insufficient

Review of Economic Design - The fear of contracting a serious illness caused by a contagious disease limits economic activity even after reopening. Widespread testing alone will not alleviate this...