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Affective forecasting (also known as hedonic forecasting or the hedonic forecasting mechanism) is the prediction of one's affect (emotional state) in the future. As a process that influences preferences, decisions, and behavior, affective forecasting is studied by both psychologists and economists, with broad applications.

Economists Daniel Kahneman and Snell began research on hedonic forecasts in the early nineties, examining its impact on decision-making. The term affective forecasting was later coined by psychologists Timothy Wilson and Daniel Gilbert. While early research tended to focus solely on measuring emotional forecasts, subsequent studies also began to examine the accuracy of forecasts, revealing that people are surprisingly poor judges of their future emotional states. For example, in predicting how events like winning the lottery might affect their happiness, people are likely to overestimate future positive feelings, ignoring the numerous other factors that might contribute to their emotional state outside of the single lottery event. Some of the cognitive biases related to systematic errors in affective forecasts are focalism, empathy gap, and impact bias.

While affective forecasting has traditionally drawn the most attention from economists and psychologists, their findings have in turn generated interest from a variety of other fields, including happiness research, law, and healthcare. Its effect on decision-making and well-being is of particular concern to policy-makers and analysts in these fields, although it also has applications in ethics. For example, the tendency to underestimate our ability to adapt to life-changing events has led to legal theorists questioning the assumptions behind tort damage compensation. Behavioral economists have incorporated discrepancies between forecasts and actual emotional outcomes into their models of different types of utility and welfare. This discrepancy also concerns healthcare analysts, in that many important health decisions depend upon patients' perceptions of their future quality-of-life.

Overview
Affective forecasting can be divided into four components: predictions about emotional valence (ie. positive or negative), the specific emotions experienced, their duration, and their intensity. . While errors may occur in all four components, research overwhelmingly indicates that the two areas most prone to bias, usually in the form of overestimation, are duration and intensity. On average, people are fairly accurate about predicting which emotions they will feel in response to future events. This tendency is found in contexts as diverse as predicting responses to photographs or winning dates in a dating-game. However, some studies indicate that predicting specific emotions in response to more complex social events leads to greater inaccuracy. For example, one study found that while many women who imagine encountering gender harassment predict feelings of anger, in reality, a much higher proportion report feelings of fear. Other research suggests that accuracy in affective forecasting is greater for positive affect than negative affect, suggesting an overall tendency to overreact to perceived negative events. Gilbert and Wilson posit that this is a result of our psychological immune system.

Affective forecasting is often measured as a two-stage process in psychological and economic literature. The first stage takes place in the present moment when the prediction is made, and the second takes place in the future, during the actual experience and outcome of the event. More specifically, the present stage involves bringing to mind a representation of the future event and inferring a hypothetical emotional response to it. Researchers often define the future stage as spanning both the initial affective reaction, as well as the aftermath, or subsequent fading of emotions. This allows them to capture measurements of intensity as well as duration.

Major Sources of Errors
Because forecasting errors commonly arise from literature on cognitive processes, many affective forecasting errors derive from and are often framed as cognitive biases, some of which are closely related or overlap themselves (eg. projection bias and empathy gap). Below is a list of commonly cited cognitive processes that contribute to forecasting errors.

Impact Bias
One of the most common sources of error in affective forecasting across various populations and situations is the impact bias, which is the tendency to overestimate the emotional impact of a future event, whether in terms of intensity or duration. For example, studies have found that college students overestimated how happy or unhappy they would be after being assigned to a desirable or undesirable dormitory. Impact bias has also been found in retroactive assessments of the past events.

Proposed causes of impact bias include mechanisms like immune bias and focalism, as well as misconstruals. For example, using highly available, but unrepresentative past memories, increases the impact bias. The pervasiveness of impact bias in affective forecasts is of particular concern to healthcare specialists, in that it affects both patients' expectations of future medical events as well as patient-provider relationships. (See health.)

Some studies specifically address "durability bias", the overestimation of the length of emotional responses to future events.

Focalism
Focalism (or the "focusing illusion") occurs when people focus too much on certain details of an event, ignoring other factors. Research suggests that people have a tendency to exaggerate aspects of life when focusing their attention on it. A well-known example originates from a paper by Kahneman and Schkade, who coined the term "focusing illusion" in 1998. They found that although people tended to believe that someone from the Midwest would be more satisfied if they lived in California, results showed equal levels of life satisfaction in residents of both regions. In this case, concentrating on the easily observed difference in weather bore more weight in predicting satisfaction than other factors. Various studies have attempted to "defocus" participants, with mixed results depending on methods used. One successful study asked people to imagine how happy a winner of the lottery and a recently-diagnosed HIV patient would be. The researchers were able to attenuate focalism by exposing participants to detailed and mundane descriptions of each person's life. These participants subsequently estimated similar levels of happiness for the HIV patient as well as the lottery-winner, as opposed to control participants, who made unrealistically disparate predictions of happiness.

Immune Neglect
Gilbert et al. originally coined the term "immune neglect" (or "immune bias") to describe a function of the psychological immune system. Immune neglect refers to forecasters' unawareness of their tendency to adapt to and cope with negative events. Subsequent research has indicated that having more effective coping strategies is correlated with greater biases in forecasting negative events, while having ineffective coping strategies is correlated with greater biases in forecasting positive events.

Projection Bias
Projection bias is the tendency to falsely project current preferences onto a future event. Within economics, projection bias relates to utility, habit formation, and consumptive behavior. For example, when deciding whether or not to smoke cigarettes, people may predict how their current consumption will affect their future preferences. Projection bias, then, could help to enable habit-forming behavior like smoking by leading people to systematically underestimate future drawbacks. Projection bias can arise from empathy gaps (or hot/cold empathy gaps), which occur when the present and future phases of affective forecasting are characterized by different states of physiological arousal, which the forecaster fails to take into account. For example, a forecaster in a state of hunger is likely to overestimate how much they will want to eat later, overlooking the effect of satiation on future preferences. As with projection bias, economists use the visceral motivations that produce empathy gaps to help explain impulsive or self-destructive behaviors, such as smoking.

Miscontruals
"Construal level theory" theorizes that distant events are conceptualized more abstractly than immediate ones. Thus, psychologists suggest that a lack of concrete details prompts forecasters to rely on more general or idealized representations of events, which subsequently leads to simplistic and inaccurate predictions. For example, when asked to imagine what a 'good day' would be like for them in the near future, people often describe both positive and negative events. When asked to imagine what a 'good day' would be like for them in a year, however, people resort to more uniformly positive descriptions. Gilbert and Wilson call bringing to mind a flawed representation of a forecasted event the misconstrual problem. Framing effects, environmental context, and cognitive heuristics (such as schemas) can all affect how a forecaster conceptualizes a future event.

Expectation Effects
Previously formed expectations can alter emotional responses to the event itself, motivating forecasters to confirm or debunk their initial forecasts. In this way, self-fulfilling prophecy can lead to the perception that forecasters have made accurate predictions. Inaccurate forecasts can also become amplified by expectation effects. For example, a forecaster who expects a movie to be enjoyable will, upon finding it dull, like it significantly less than a forecaster who had no expectations.

Memory
Affective forecasters often rely on memories of past events. However, predictions hinge on the accuracy of remembering past experiences. Various studies indicate that retroactive assessments of past experiences are prone to various errors, such as duration neglect or decay bias. People tend to overemphasize the peaks and ends of their experiences when assessing them (peak/end bias), instead of analyzing the event as a whole. Retroactive reports often conflict with present-moment reports of events, further pointing to contradictions between the actual emotions experienced during an event and the memory of them. In addition to producing errors in forecasts about the future, this discrepancy has incited economists to redefine different types of utility and happiness (see section on economics).

In Psychology
Psychologists have traditionally focused on identifying how and why errors in affective forecasting arise, contributing significantly to the understanding of how different biases influence the process.

Psychological Immune System
Gilbert and Wilson coined the term "psychological immune system" to encompass a number of biases and mechanisms that protect people from experiencing extreme negative emotions. This label draws on an analogy with the biological immune system. These processes affect how the people process, transform or construct information, making the existing state of affairs more bearable and the alternatives more appealing. The mechanisms of the psychological immune system act without conscious awareness, so people usually fail to anticipate its effects. This is one reason why people are poor at affective forecasting: they typically underestimate the extent to which these processes will shield them from a negative event. .

Improving Forecasts
Preliminary studies have incorporate findings on cognitive bias]es and affective forecasting to investigate ways of "debiasing" forecasts. Approaches vary depending on which bias is targeted. For example, one study successfully "defocused" (i.e. reduced the impact of focalism) participants . Researchers asked participants to imagine how happy a winner of the lottery and a recently-diagnosed HIV patient would be. The researchers were able to attenuate focalism by exposing participants to detailed and mundane descriptions of each person's life. These participants subsequently estimated similar levels of happiness for the HIV patient as well as the lottery-winner, as opposed to control participants, who made unrealistically disparate predictions of happiness. A study focusing on decreasing [[impact bias employed mindfulness techniques, finding that mindfulness leads to more moderate forecasts and decreased susceptibility to impact bias.

Mediating Factors
Psychologists are interested in what types of factors mediate affective forecasting. Research suggests links between forecasting processes and extraversion and neuroticism, possibly because these personality traits affect baseline moods and both experienced and anticipated emotional reactions. Other research has found that working memory and the perceived importance of a future event increase impact bias, but only for some individuals. Other individual traits that lead to differences in forecasting accuracy are levels of attachment anxiety and emotional intelligence. Culture may also mediate affective forecasting. People from east Asian cultures exhibit less susceptibility to both impact bias and focalism.

Other directions
Research has also investigated motivational components of affective forecasting. Consumer psychologists are interested in how marketers can influence consumers' affective forecasts to influence consumer decision, specifically in regards to the durability bias.

In Economics
Behavioral economists share psychologists' interests in affective forecasting insomuch as it affects utility constructs, decision making    , and happiness research that combines psychological and economic approaches.

Time Discounting
Time discounting (or time preference) is the tendency to weigh present events over future ones. Applied to affective forecasting, this helps explain why people underestimate the intensity of future events, a phenomenon called "future anhedonia". Forecasts of the duration of feelings often capture the tendency for emotions to fade over time, but underestimate the speed in which this happens.

Utility
Research in affective forecasting errors complicate conventional interpretations of utility maximization, which presuppose that to make rational decisions, people must be able to make accurate forecasts about future experiences or utility. In incorporating affective forecasting into their model of expected utility or predicted utility, Kahneman and Thaler foreground errors in hedonic projections. Affective forecasting has also been used to understand loss aversion, an implicit component of prospect theory, which states that decision makers weigh losses more than gains.

Decision-making
Affective forecasting is an important component of studying human decision making. Research in affective forecasts and economic decision making include investigations of durability bias in consumers, predictions of public transit satisfaction , and environmentally-friendly decisions.

Happiness and Well-being
Economic research on happiness and well-being incorporate research on affective forecasting errors and biases, which are often framed in terms of utility. Findings in affective forecasting have also influenced theories of hedonic adaptation.

In Law
In addition to influencing legal discourse on emotions, tort damages  , and welfare, Jeremy Blumenthal cites additional implications of affective forecasting in civil jury compensation, contract law, sexual harassment, health law, and capital sentencing.

In Health
Affective forecasting has implications in health decision-making and medical ethics and policy-making.

Notable Contributors

 * Daniel Kahneman
 * George Loewenstein
 * Timothy Wilson
 * Daniel Gilbert