Affective Forecasting

The Basic Idea

At one point or another, we’ve all likely experienced something that made us feel like the world was ending. Whether it be the end of a romantic relationship, losing a family member, not getting the dream job, or anything else subjectively devastating, we may sometimes feel like we’ll never recover. Affective forecasting, also known as hedonic forecasting, refers to predictions of how we will feel about future emotional events.1

If we know anything about human judgements and decision making, it’s that they can be erroneous, and affective forecasting is no different.2 Generally, people tend to overestimate both the strength and duration of their emotional reactions.1 This is because people engage in focalism, thinking about the impact of events in isolation, and immune neglect, ignoring the techniques we use to alleviate feelings. Impact bias — overestimating the impact of an event — makes us poor judges of the speed and strength of our coping mechanisms. We actually adapt more readily than we’d expect.

Whether people overestimate how good or bad they will feel, overestimate how quickly those feelings will arise, or underestimate how quickly they will dissipate, the important point is that they overestimate how powerfully the event will impact their emotional lives.

– Timothy Wilson and Daniel Gilbert in their seminal work,“Affective Forecasting”

Theory, meet practice

TDL is an applied research consultancy. In our work, we leverage the insights of diverse fields—from psychology and economics to machine learning and behavioral data science—to sculpt targeted solutions to nuanced problems.

Our consulting services

Key Terms

Affective forecasting: Predicting one’s affect (emotional state) in the future.

Focalism: Humans tend to think about the impact of an event in isolation, rather than other factors that could offset the emotion.

Immune neglect: Although humans can rationalize and engage in self-serving biases to undo negative feelings, we don’t consider these when predicting how we’ll feel.

Impact bias: Overestimating the enduring impact of emotion-causing events.


Israeli psychologist Daniel Kahneman is commonly cited in the field of behavioral economics and decision making research for his work on affective forecasting. Kahneman and fellow psychologist Jackie Snell came up with the concept of hedonic forecasting in their 1992 article, “Predicting a changing taste: Do people know what they will like?”3  In Kahneman and Snell’s article, hedonic forecasting referred to implicit or explicit forecasts of utility in the future, with utility defined as the quality and intensity of hedonic experiences associated with an outcome. Essentially, Kahneman and Snell focused on people’s predictions of how much pleasure they would experience from a certain decision.

However, humans are not always happy about the outcomes of their decision making.4 Recognizing this, social psychologists Timothy Wilson and Daniel Gilbert coined the term affective forecasting, referring to the expectations that we form about our future feelings. Their 2003 article entitled “Affective Forecasting” identified four components of future emotional experiences that humans may predict:

  1. Valence of the emotion: whether it will be positive or negative;
  2. Specific emotions like disgust, anger, fear, or a combination of all three;
  3. Intensity of the emotion; and
  4. Duration of the emotion.

Wilson and Gilbert suggested that people tend to accurately predict the valence of their future emotions, as well as the specific emotions that they will feel.4 Often, this is based on prior experiences. However, people tend to overestimate the impact of future events on their emotions, consisting of both intensity and duration. In order for people to accurately predict how they will feel after an event occurs, they will need to know the acceleration of their initial emotional reaction, the peak level of intensity of their reaction, and the rate of deceleration.

This is easier said than done, which is why people tend to make inaccurate predictions on all three components: they overestimate the rate of acceleration and the peak level of intensity, while they underestimate the rate of deceleration.4 Figure 1 illustrates the discrepancies between one’s predicted and actual emotional reactions to an event. Of course, emotions are complex and can thus result in more complex patterns than said figure, as reactions are influenced by environmental reminders of the event.

Affective Forecasting

Wilson and Gilbert referred to emotional mispredictions as impact bias. People tend to overestimate the lasting impact that a future event will have on our emotional reactions, including both intensity and duration.4 The researchers found the impact bias to be present in a variety of populations (i.e. college students, dieters, and sports fans) and for a variety of emotional events (i.e. romantic breakups, learning the results of a health-related test, and sports victories). Wilson and Gilbert also considered errors that lead to impact bias, such as the misconstrual problem (imagining the wrong event) and the isolation effect (comparing the predicted event to alternative events, and focusing on how little features they share).


Daniel T. Gilbert

An American psychologist and writer, Gilbert wrote international bestseller Stumbling on Happiness, which has been translated into over 30 languages and was the recipient of the 2007 Royal Society Prizes for Science Books. Gilbert’s research focuses on social psychology and cognitive biases, as reflected in his work on affective forecasting and his teachings at Harvard University. Beyond academia, Gilbert delivers TED talks and has hosted the PBS television series “This Emotional Life”, which won several Telly Awards.

Timothy D. Wilson

Also an American psychologist and writer, Wilson is known for his research on introspection as a source of self-knowledge, the influence of the unconscious mind on our preferences, and decision making.6 Related to his psychological interests, Wilson has published two popular books on psychology entitled, Redirect: The Surprising New Science of Psychological Change and Strangers to Ourselves: Discovering the Adaptive Unconscious. Beyond his contributions to affective forecasting, Wilson also teaches social psychology at the University of Virginia.


Affective forecasting has been applied to a variety of fields beyond psychology, including law and health care. As it pertains to psychology, affective forecasting is important for decision making.7 As people make predictions of their future emotions, they may be swayed toward a certain choice. When considering transportation, for example, those who lack experience with public transportation predict they will feel more negative emotions when using such methods of transportation (i.e. buses, trains) than they actually experience.8 Due to erroneous affective forecasts, people may feel more inclined to purchase a personal vehicle, which then has environmental and financial implications.

Most people with a law degree will recall their foundational Tort Law class in first year, which deals with the types of disputes that arise when one party causes property loss or injury to another.9 Beyond the classroom, compensations awarded by the jury for tort damages are related to the victim’s pain, suffering, and decrease in quality of life.10 Considering affective forecasting in the context of the legal system, there has been concern that juries overcompensate victims due to overestimating the intensity and duration of negative impact. As a result, some have suggested developing programs to educate jury members on potentially inaccurate predictions and how to decrease such erroneous forecasts.11 Affective forecasting is part of a larger discussion of the role emotions play in the legal world.

There is a “disability paradox” in the realm of health care, such that there is a discrepancy between self-reported levels of happiness among chronically ill people and predictions of their happiness levels by healthy people.12 Affective forecasting results in erroneous judgements about patients’ future quality of life, which then informs medical decision making.13 For example, inaccurate forecasts can cause health care agents or caregivers to refuse life-saving treatments for their patients when said treatment would result in lifestyle changes (i.e. a leg amputation). As a result, a medical debate has emerged: some doctors suggest medical paternalism is necessary to override the consequences of affective forecasting, while others hold that these biases simply require changes in doctor-patient communication patterns.14


Traditional economists assume that humans are rational decision makers who will act in ways to maximize utility.15 However, affective forecasting and the expected experience of emotions complicates such assumptions of rationality: if forecasts are inaccurate, how can people reliably measure the choices that will offer them the most utility in the future?

To overcome these discrepancies, it was necessary for economists like Daniel Kahneman and Richard Thaler to incorporate differences between affective forecasts and future  outcomes into types of utility.15 Current forecasts reflect expected utility, which is the weighted average of all possible outcomes under certain circumstances.16 However, the actual outcome of an event will reflect experienced utility, which includes the perceptions of pleasure and pain associated with the outcome.15

For example, take someone who heads to the grocery store while hungry. In their current state, they will take pleasure in their purchase and expect high utility when the food satisfies their hunger. The actual utility of their grocery store purchase will depend on their experience while consuming the food and its anticipated pleasure.

Case Study

Real versus imagined harassment

An estimated 80% of sexual harassment cases consist of blaming the victim, based on beliefs that they failed to respond to the harassment in a “correct” way.16 However, research shows a discrepancy between imagined and actual reactions to harassment. To investigate the role of affective forecasting in victim blaming, Woodzicka and LaFrance asked female participants to read a written scenario describing a job interview where they were asked questions like: Do you have a boyfriend? Do you think it is important for women to wear bras to work? As predicted, most respondents predicted they would confront the harasser and that they would most intensely feel anger, followed by fear.

While most women accurately predicted which emotions they would feel when asked a sexually inappropriate question, predictions regarding the intensity of said emotions were inaccurate.16 Woodzicka and LaFrance devised a job interview in which a male interviewer asked female applicants sexually harassing questions like the ones above, interspersed with more typical interview questions. While women still reported feeling anger and fear, it was fear that was most intensely experienced. Additionally, few women confronted the interviewer.

The study’s results highlight harassment victims’ actual reactions, and the role that affective forecasting plays in victim blaming.16 While people may predict how they would feel and act in a certain situation, their actual reactions may differ. Failure to understand the influence of affective forecasting and these discrepancies impede effective education on harassment and negatively impact targets of harassment, as they may also blame themselves for their lack of action. Continued research on emotional and physical reactions to harassment is important for developing programs and procedures to alleviate the stigma associated with being a target of harassment.

Travelling during a pandemic

People often base travel decisions on predictions: whether they think they will prefer lounging on the beach or exploring a historic site, and which location they think will best serve their interests.17 Thus, affective forecasting is an important part of travel decision making. Existing literature focuses on the mechanisms by which people make predictions about future travel, such as mentally pre-experiencing a holiday. Researchers have also considered the roles of emotions in that process, such that tourists will attribute a specific emotion to a specific destination. However, we know that affective forecasting can be erroneous, so what happens in the context of travelling during a pandemic?

The COVID-19 pandemic has resulted in travel restrictions and important considerations of risk.17 A group of European researchers wanted to know whether affective forecasting would lower tourists’ perceived risk of travelling during the pandemic, and thus influence future travel decisions. They considered the role of episodic future thinking, which is the projection of oneself into the future to pre-experience an event. The researchers purposely sampled from the United States, as it was the country most affected by COVID-19 (in terms of deaths and cases) during May 2020, the time of data collection.

The researchers assigned 291 participants to one of two conditions: (1) affective forecasting, where participants engaged in episodic future thinking and imagined a future holiday; and (2) the control, where there was no simulated affective forecasting.17 After this initial simulation, participants reported their perceived travel coronavirus-infection risk, willingness to travel after restrictions were lifted, and how soon they would travel.

The researchers found that those who engaged in affective forecasting perceived lower levels of travel-related infection risk, increased willingness to travel, and increased willingness to wait for travel, compared to the control group.17 Since there was greater promise of exciting adventures to come, this made the wait easier, as participants believed that it was worth something great. The study’s results highlight the role that affective forecasting can play in altering tourists’ attitudes, which are unlikely limited to the context of a pandemic. Of course, this was an important context to consider given present reality.

Related TDL Content

Empathy gap

Another forecasting error, the empathy gap describes our inability to correctly identify how our emotions impact our behavior. Similar to affective forecasting, the empathy gap impacts our ability to make accurate predictions. Take a read through this article on the effects of the empathy gap, why it happens, and how to avoid it.

Protecting your projects from cognitive bias

Forecasting errors are far and few between, and don’t stop at an emotional level. These cognitive biases can also play out in tangible ways, like our ability to complete a project as planned. The planning fallacy acknowledges how people underestimate the resources needed for a project: take a look at consultant Natasha Hawryluk’s article on remedies to this bias.


  1. Myers, D., Jordan, C., Smith, S., & Spencer, S. (2018). Social Psychology. McGraw Hill.
  2. Kahneman, D. (2013). Thinking, Fast and Slow. Farrar, Straus and Giroux.
  3. Kahneman, D., & Snell, J. (1992). Predicting a changing taste: Do people know what they will like? Journal of Behavioral Decision Making, 5(3), 187-200.
  4. Wilson, T. D., & Gilbert, D. T. (2003). Affective forecasting. Advances in Experimental Social Psychology, 35, 345-411.
  5. (2021). Daniel Gilbert.
  6. (2021). Timothy D. Wilson.
  7. Hoerger, M., Quirk, S. W., Lucas, R. E., & Carr, T. H. (2010). Cognitive determinants of affective forecasting errors. Judgement and Decision Making, 5(5), 365-373.
  8. Pedersen, T. (2009). Affective forecasting: Predicting future satisfaction with public transport (Doctoral dissertation, Karlstad University).
  9. University of Toronto Faculty of Law. (2020). First Year Academic Program. Academic Handbook.
  10. Swedloff, R., & Huang, P. H. (2010). Tort damages and the new science of happiness. Indiana Law Journal, 85(2), 553-595.
  11. Maroney, T. A. (2006). Law and emotion: A proposed taxonomy of an emerging field. Law and Human Behavior, 30(2), 119-142.
  12. Albrecht, G. L., & Devlieger, P. J. (1999). The disability paradox: High quality of life against all odds. Social Science & Medicine, 48(8), 977-988.
  13. Halpern, J., & Arnold, R. M. (2008). Affective forecasting: An unrecognized challenge in making serious health decisions. Journal of General Internal Medicine, 23(10), 1708-1712.
  14. Gligorov, N. (2009). Reconsidering the impact of affective forecasting. Cambridge Quarterly of Healthcare Ethics, 18(2), 166-173.
  15. Kahneman, D., & Thaler, R. H. (2006). Anomalies: Utility maximization and experienced utility. Journal of Economic Perspectives, 20(1), 221-234.
  16. Chen, J. (2021, May 7). Expected Utility.
  17. Karl, M., Kock, F., Ritchie, B. W., & Gauss, J. (2021). Affective forecasting and travel decision-making: An investigation in times of a pandemic. Annals of Tourism Research, 87, 103139.

About the Author

Cece Li

Cece was a former content creator with a passion for behavioral science. She previously created content for The Decision Lab, and her insights continue to be valuable to our readers.

Read Next

Notes illustration

Eager to learn about how behavioral science can help your organization?