Affective forecasters often exhibit an impact bias, overestimating the intensity and duration of their emotional reaction to future events. Researchers have long wondered whether the impact bias might confer some benefit. We suggest that affective forecasters may strategically overestimate the hedonic impact of events to motivate their production. We report the results of four experiments providing the first support for this hypothesis. The impact bias was greater for forecasters who had chosen which of two events to attempt to produce than for forecasters who had yet to choose (Experiment 1). The impact bias was greater when forecasts were made while forecasters could (or perceived they could) influence whether an event was produced than when its production had been determined but was unknown (Experiments 2A and 2B). Finally, experimentally manipulating the extremity of affective forecasts for an event influenced the amount of effort that forecasters expended to produce it (Experiment 3). The results suggest that the impact bias may not be solely cognitive in origin, but may also have motivated underpinnings.

Gables, FL 33124. The authors thank Ben Borenstein, Vamsi Kanuri, and the behavioral labs at the University of Miami and the Moore School of Business for their help with data collection. They thank Chris Janiszewski, Anastasiya Pocheptsova Gosh, the editor, the associate editor, and the three reviewers for their helpful comments on previous versions of the manuscript.

Affective forecasts are used to anticipate the hedonic impact of future events and decide which events to pursue or avoid. We propose that because affective forecasters are more sensitive to outcome specifications of events than experiencers, the outcome specification values of an event, such as its duration, magnitude, probability, and psychological distance, can be used to predict the direction of affective forecasting errors: whether affective forecasters will overestimate or underestimate its hedonic impact. When specifications are positively correlated with the hedonic impact of an event, forecasters will overestimate the extent to which high specification values will intensify and low specification values will discount its impact. When outcome specifications are negatively correlated with its hedonic impact, forecasters will overestimate the extent to which low specification values will intensify and high specification values will discount its impact. These affective forecasting errors compound additively when multiple specifications are aligned in their impact: In Experiment 1, affective forecasters underestimated the hedonic impact of winning a smaller prize that they expected to win, and they overestimated the hedonic impact of winning a larger prize that they did not expect to win. In Experiment 2, affective forecasters underestimated the hedonic impact of a short unpleasant video about a temporally distant event, and they overestimated the hedonic impact of a long unpleasant video about a temporally near event. Experiments 3A and 3B showed that differences in the affect-richness of forecasted and experienced events underlie these differences in sensitivity to outcome specifications, therefore accounting for both the impact bias and its reversal. (PsycINFO Database Record

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We propose that affective forecasters overestimate the extent to which experienced hedonic responses to an outcome are influenced by the probability of its occurrence. The experience of an outcome (e.g., winning a gamble) is typically more affectively intense than the simulation of that outcome (e.g., imagining winning a gamble) upon which the affective forecast for it is based. We suggest that, as a result, experiencers allocate a larger share of their attention toward the outcome (e.g., winning the gamble) and less to its probability specifications than do affective forecasters. Consequently, hedonic responses to an outcome are less sensitive to its probability specifications than are affective forecasts for that outcome. The results of 6 experiments provide support for our theory. Affective forecasters overestimated how sensitive experiencers would be to the probability of positive and negative outcomes (Experiments 1 and 2). Consistent with our attentional account, differences in sensitivity to probability specifications disappeared when the attention of forecasters was diverted from probability specifications (Experiment 3) or when the attention of experiencers was drawn toward probability specifications (Experiment 4). Finally, differences in sensitivity to probability specifications between forecasters and experiencers were diminished when the forecasted outcome was more affectively intense (Experiments 5 and 6).