Processing of Negative Numbers and its Impact on Economic Judgement
Mon-B16-Talk I-01
Presented by: Hannah Seidler
The perception and integration of numeric information is a prerequisite for many decisions in our daily life, such as when assessing risks. Research in numeric cognition indicates, that positive numbers are mentally represented on a compressed mental number line (CMNL), i.e., the same difference between two numerosities is perceived as smaller for greater numerosities than for smaller ones (e.g., Izard & Dehaene, 2008). The CMNL predicts an underestimation of the mean for sequences of positive numbers. This suggests that for a risky lottery, a subjective certainty equivalent below the expected value may not only be due to preferences, such as risk aversion, but also due to perceptual biases in the mental representation of numbers (Khaw et al., 2021; Olschewski et al., 2021). We tested whether the assumption of a CMNL also applies to negative numbers and thus partially explains risk-seeking behavior in the loss domain. Using a fixed-sampling paradigm, participants sequentially sampled 20 numbers drawn from an underlying distribution and estimated the sequence’s mean. The sequences either contained only positive numbers, only negative numbers, or both (i.e. mixed sequences) and varied in mean and standard deviation. In line with a CMNL for absolute magnitudes, we found an underestimation for positive and an overestimation for negative sequences, indicating that both, risk seeking and risk aversion could partly be explained by biases in number perception. However, the pattern reversed for mixed sequences. We discuss the impact on economic judgments when both, gains and losses are involved.
Keywords: decision-making, Decision-from-Experience, number perception, risk preferences