Fine Distinctions within Cognitive Style Predict Forecasting Accuracy

Abstract

Leveraging data from over 1,000 users in the System for Prediction, Aggregation, Display and Elicitation (SPADE) research program, we present preliminary data on the factor structure of individual variation in decision making ability and the associations of this variance with errors in cognitive reasoning and accuracy in making socio-political forecasts. Generally, prior research has identified two factors, or styles—intuitive and analytic—that account for significant variance in how individuals reach solutions to complex numerical and logical problems. Though sometimes named differently across research programs, an intuitive style is a tendency to use instincts, experiential knowledge, and intuition to solve problems, where an analytic style is a tendency to apply formal logic, methods of inquiry and theory to confront problems. Within a large research sample, factor analytic techniques define finer distinctions among these styles. In particular, we find distinctions within the analytical style, such that certain measures of analytic style (REI; Norris, Pacini, & Epstein, 1998) capture variance related to tendencies to express a deep interest in complex problem solving and openness to new information. In contrast, other measures (CSI; Allinson et al., 1996) capture variance related to tendencies to solve problems that are driven by a need for closure and conscientiousness. Subsequent correlation analysis suggests that the latter tendency covaries with susceptibility to commit errors in logical reasoning and poor performance on socio-economic forecasts elicited through the iSPADE system. Future work will clarify the relationship between cognitive styles and errors in reasoning and forecasting behavior through multi-level modeling techniques.

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