Decisions from experience and statistical probabilities : why they trigger different choices than a priori probabilities

The distinction between risk and uncertainty is deeply entrenched in psychologists' and economists' thinking. Knight ([1921]), to whom it is frequently attributed, however, went beyond this dichotomy. Within the domain of risk, he set apart a priori and statistical probabilities, a distinction that maps onto that between decisions from description and experience, respectively. We argue this distinction is important because risky choices based on a priori (described) and statistical (experienced) probabilities can substantially diverge. To understand why, we examine various possible contributing factors to the description-experience gap. We find that payoff variability and memory limitations play only a small role in the emergence of the gap. In contrast, the presence of rare events and their representation as either natural frequencies in decisions from experience or single-event probabilities in decisions from description appear relevant for the gap.