An empirical investigation of preferences over sequences of outcomes and applications in the monetary, environmental and health domains: A decision analysis approach

Three anomalies revealed in previous research (Gain/Loss Asymmetry, Short/Long Asymmetry, and the Absolute Magnitude Effect) using a pairwise matching elicitation procedure were investigated using a relative valuation of sequences task. It appears that the participants of this study used additional factors other than discounting to rank the monetary sequences. The strongest factor was a Gain/Loss effect. In addition, participants preferred to spread the outcomes over time if they were losses, and consolidate them if they were gains. This preference for spreading was stronger with a larger magnitude of money. There was also a Gain/Loss effect in the pairwise matching task, in which losses were discounted at a higher rate than gains. This asymmetry is in the opposite direction than expected and not consistent with the responses given in their other task. The participants were more consistent between the two tasks when the outcome was a gain than when it was a loss.;In addition, experimental results on individuals' preferences for temporal sequences of environmental outcomes related to air quality and near-shore ocean water quality were compared with preferences for sequences of health and monetary outcomes. Generally, the participants gave significantly lower ratings to environmental and health sequences (with equal means) that worsened over time, relative to the ratings they gave to sequences that either remained the same or improved over time. This pattern was reversed when they faced sequences of monetary payments. This preference structure held for both short (5-year) and long (50-year) time horizons, and was confirmed with choice data. A positive relationship between an expectation that the most likely sequence would be decreasing and a choice of a decreasing sequence as ideal was also found in all domains but monetary. A model proposed by Loewenstein and Prelec was applied to the current data and compared to the traditional discounting model. In all cases, the model that incorporated "Gestalt" features of the sequence (slope and uniformity) performed better than the discounting model at predicting the mean ratings for the different sequences.