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Affective forecasting for future consumption improves across the life span
Lisa Zaval, Ye Li and Eric J. Johnson
Author note: Lisa Zaval is a post-doctoral researcher at the Center for Decision Sciences in the
Graduate School of Business at Columbia University. Ye Li is an Assistant Professor of
Management & Marketing in the School of Business Administration at the University of
California, Riverside. Eric J. Johnson is Norman Eig Professor of Business and co-director of the
Center for Decision Sciences in the Graduate School of Business at Columbia University.
Correspondence concerning this article should be addressed to the first author at Columbia
University, 3022 Broadway Avenue, New York, NY, 10027 ([email protected]). This
research has been supported by NIA Grant R01AG044941. We thank Elke Weber for helpful
comments; and Jon Westfall, Min Bang, Jie Gao, Zeynep Enkavi, and Brian Huh for technical
support in running the studies.
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CONTRIBUTION STATEMENT
Although age differences in affective forecasting have important implications for consumer
behavior and for the welfare of older adults, only a handful of papers on this topic exist and none
have examined underlying mechanisms. Given large cognitive declines with age (e.g. Salthouse
et al. 2008), it is critical to investigate whether other skills, such as affective forecasting, may
also show declines or, instead, might help mitigate the impact of cognitive decline on older
consumers’ decision-making. More research on consumer decision making and aging is
particularly important for developing an improved understanding of ways to maintain consumer
satisfaction and high decision quality across the life span (Yoon and Schwartz 2010; Carpenter
and Yoon 2012). Increasing focus on how different consumers make these types of pervasive
affective judgments may be crucial to understanding impulsive buying and purchase regret
(Patrick and MacInnis 2007).
Taken together, our findings contribute to the literature on age differences in decisionmaking by showing that affective forecasting is a skill that actually improves across the life span.
Of the potential underlying mechanisms measured or manipulated in the present study (including
cognitive ability, domain-specific experience, and current affective state) we find that
perceptions of future self-continuity (the degree to which one perceives connection between
one’s current and future identity) showed the most promise in explaining age-related differences
in affective forecasts. Further, our results also offer a new potential explanation of increasing
patience in intertemporal choices over the life span, as we find that increased patience in older
adults is associated with age-related improvements in future anhedonia.
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ABSTRACT
Affective forecasting plays a major role in consumer choice but suffers from many
systematic errors. However, little is known about how forecasting accuracy changes over the
adult life span. We present four studies that investigate age differences in consumers’ ability to
forecast how they will feel about upcoming events (e.g., receiving a gift basket). We show one
way that affective forecasting improves across the life span: Older adults are less likely than
younger adults to wrongly predict that their affective response to an event will be less intense if
the event occurs later in time—a reduction of future anhedonia. We find this age-related
improvement for predictions about money as well as consumer goods, but not for predictions
about losses. An examination of underlying mechanisms suggests that the age difference in
future anhedonia is driven by age differences in the perceived psychological connectedness
between one’s current and future self. Further, we show that less susceptibility to future
anhedonia may contribute to older adults’ more patient temporal discounting. These results have
implications for age-related changes in an array of consumer judgments including product
evaluation, consumer satisfaction, and purchase regret.
Keywords: affective forecasting, aging, time preference, future self-continuity
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INTRODUCTION
Many consumer decisions involve future rather than immediate consumption. In these cases,
peoples’ decisions must be based on predictions about how they will feel at a later time. When
planning to purchase new clothes, for example, shoppers must make predictions about how they
will enjoy wearing the clothes later that season, and when booking a vacation, a consumer is
making a forecast of their future enjoyment. Consumer welfare therefore depends on the ability
to accurately forecast future feelings about potential purchases.
Prior research confirms that people regularly engage in affective forecasting (Gilbert et
al.1998)—i.e., they anticipate or predict how they will feel in the future. Unfortunately, people
are often poor predictors of their future affective states (Gilbert et al. 1998; Loewenstein and
Schkade 1999), and experienced affect often deviates from predicted affect (Gilbert and Ebert
2002; Kermer et al. 2006).
One particular forecasting error that has attracted research attention is future anhedonia, in
which consumers assume that their affective responses to a positive event will be less when the
event occurs further in the future than when it occurs today (Kassam, Gilbert, Boston, and
Wilson 2008). Future anhedonia contributes to impatient intertemporal choices, a phenomenon
associated with consumer problems such as obesity (Chabris et al. 2008; Reimers et al. 2009),
credit card debt (Meier and Sprenger 2010), and substance abuse (Kollins 2003; Bickel and
Marsch 2001). The detrimental consequences of consumer impatience highlight the need for a
better understanding of factors that impact susceptibility to affective forecasting errors, since
some consumers may be at greater risk for poor affective forecasting than others.
We examine if consumers’ susceptibility to affective forecasting errors may differ by age.
Understanding potential age differences in affective forecasting ability is essential, as inaccurate
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forecasts have important practical relevance for older consumers: Aging is associated with a
broad range of critical decisions about the future in areas such as retirement planning (Hershey et
al. 2007), long-term investments (Frolik 2009), and health care choices (Anderson 2007).
However, despite considerable research suggesting that affective forecasting errors have
important impacts on consumer judgments (e.g., Patrick and MacInnis 2007), less is known
about how age influences the accuracy of these forecasts. Moreover, the research that has
examined age-related differences has focused on identifying inaccuracies, but work is needed to
investigate the underlying processes by which age differences emerge.
The effect of age on affective forecasting ability may depend on key psychological factors
that change across the life span, including those that decline with age such as cognitive ability
(Salthouse, Pink, and Tucker-Drob 2008), and those that improve with age such as accumulated
life experiences (Tentori et al. 2001; Yoon, Cole, and Lee 2009; Li et al. 2013; Li et al. 2015)
and adaptive emotional processing (Scheibe and Carstensen 2010). Further, because affective
forecasting decisions are embedded in a temporal context, age-related changes in mental
representations of time, such as the general capability to know that the future is going to feel the
same as today, suggest that the accuracy of affective projections may improve across the life
span (Rutt and Löckenhoff 2016).
The present research investigates the hypothesis that affective forecasting accuracy improves
with age. In particular, we set out to test whether age reduces susceptibility to future anhedonia,
such that older adults are less likely than younger adults to wrongly predict that their affective
response to an event will be less intense if the event occurs later in time. Recent research
suggests that the experience that comes with age can compensate for cognitive declines (Li et al.,
2015), and we expect that the aging process may also lead to learning that affective responses to
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future outcomes do not diminish in scope. Of course, that experience has many components, and
we examine several alternative mechanisms that might mediate this hypothesized age-related
improvement in future anhedonia. To preview our results, among the potential underlying
mechanisms included in the present study, we find that future self-continuity (the degree to
which one perceives connection between one’s current and future identity) alone explained agerelated differences in affective forecasts.
To put our predictions into context, we first review existing lines of research that have
relevance to age differences in future anhedonia, integrating across diverse literatures on mental
representations of time, affective processing and accumulated domain-specific experience. We
discuss the theoretical rationale for our predictions and then consider the possible implications
for age differences in affective forecasting ability and consumer judgments and decisions.
Theoretical Background
Affective Forecasting and Aging
Prior work on affective forecasting errors reveals that mispredictions can take a number of
forms, and that people often make inaccurate forecasts concerning both the intensity and the
duration of their affective responses (Frederick, Loewenstein and O'Donoghue 2002; Wilson and
Gilbert 2003; Busse et al. 2015). The inability to accurately predict future affective states can
lead to sub-optimal purchasing decisions (Kahneman and Snell 1992) and may contribute to
consumer judgments such as product dissatisfaction (Sevdalis et al. 1983), negative product
evaluations (Patrick and MacInnis 2007), purchase regret (Dittmar 2001) and product returns
(Conlin, O’Donoghue and Vogelsang 2007).
Although age differences in affective forecasting ability have important implications for
consumer behavior and the welfare of older adults, only a handful of papers on this topic exist.
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Two studies found age improvements: When playing an incentivized game involving gains and
losses, younger, but not older adults underestimated increases in arousal during anticipation of
small monetary gains and losses, and overestimated increases in arousal in response to gain
outcomes (Nielsen, Knutson, and Carstensen 2008). Forecasting accuracy also improved with
age in a study in which participants predicted how they would feel if their preferred presidential
candidate won or lost the 2008 election, particularly among supporters of the winning candidate
(Scheibe et al. 2011). In contrast, no age differences in forecasting accuracy were found in a
study in which older and younger adults predicted how satisfied they would feel after choosing
among everyday products (Kim et al. 2008).
In summary, despite some preliminary evidence that older adults more accurately predict
future affective states, research is needed to clarify the scope of this age difference and provide
an explanation for what psychological processes may contribute to age-related changes. We
focus on one forecasting error, future anhedonia, the prediction that affective states will be less
intense for events that happen in the future than the present (Kassam et al. 2008). According to
this conceptualization, it may be more difficult to mentally represent the emotional response that
follows receipt of a temporally distant reward compared with a reward received in the present
(Kassam et al. 2008; Lempert & Pizzagali, 2010). Although consumers should discount delays in
receiving rewards to some degree, discounting it due to future anhedonia is an error: Your
happiness upon receiving a gift basket should be the same at the moment of receipt whether it
happens today or 1 month in the future. In the next sections, we outline several potential
mechanisms that may produce changes in future anhedonia over the life span.
Aging, Future Anhedonia, and Mental Representations of Time
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A body of work indicates that the temporal distance of an event influences people’s mental
representation of that event. Future anhedonia inherently involves the evaluation of future events
and outcomes, and thus may be related to people’s mental representations of the future. Research
demonstrates that mental representations of time and of the future vary across the adult life span
(for a review, see Löckenhoff 2011). One aspect of future time perspective that has recently been
shown to increase across the life span is future self-continuity (Rutt and Löckenhoff 2016),
defined as the degree to which a person believes that the current self’s psychological
characteristics will persist in the future self (Hershfield et al. 2009; Bartels and Rips 2010;
Bartels and Urminsky 2011; Bartels and Rips; Hershfield, Cohen, and Thompson 2012).
Enhanced feelings of future self-continuity among older adults may play a key role in preserving
emotional well-being and a sense of identity as one grows older (Baltes, Lindenberger and
Staudinger 2006). These age-related shifts have important implications for intertemporal
decision making and affective forecasting, since one determinant of people’s predictions about
future events is the person they expect to be when those events occur (Ersner-Hershfield et al.
2009). Feeling disconnected from the future self may lead to inaccurate valuations of future
outcomes, including the mistaken belief that one will experience less intense affect when an
event occurs in the future than when the same event occurs in the present.
Indeed, research suggests that when people believe that their identity remains stable over
time, they will tend to exhibit greater consideration of their future needs. For example, high
levels of future self-continuity have been shown to facilitate savings and investment behavior
(Ersner-Hershfield et al. 2009) and reduce long-term discount rates (Bartels and Urminsky 2011).
An age-related increase in future self-continuity is therefore consistent with evidence showing
that as people age, they discount the value of delayed rewards less steeply and thus behave more
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patiently relative to young adults (Li et al. 2013; Löckenhoff et al. 2011; Whelan and McHugh
2009; Reips 2002; Green, Fry, and Myerson 1994). It stands to reason that older adults’ more
patient intertemporal choices may be related to reductions in future anhedonia, such that older
adults make more realistic affective predictions regarding present and future events.
In summary, prior research indicates that future self-continuity is an important determinant of
intertemporal decisions, and is positively associated with age and patience. We posit that agerelated improvements in future anhedonia occur, at least in part, because older adults feel a
stronger connection with their future selves. If older adults are more likely to believe that the
current self’s psychological characteristics will persist in the future self, then older adults should
project that their affective reactions to outcomes will likely feel the same, regardless of when that
outcome is realized.
Age and Affective Processing
An alternative account suggests that age differences in affective forecasting accuracy are
informed by changes in emotional processing abilities. A growing body of research indicates that
affective processing abilities show differential age trajectories (Carstensen 2006; Figner,
Mackinlay, Wilkening, and Weber 2009) with implicit forms of knowledge, such as affect,
becoming more important inputs into decisions as deliberative processes decline with age
(Mather, 2006; Peters, Finucane, MacGregor, and Slovic 2000; Peters et al. 2007).
To explain this difference, socioemotional selectivity theory (SST; Carstensen,
Isaacowitz and Charles 1999) contends that priorities shift as time horizons become increasingly
limited, with positive affect-focused goals becoming increasingly salient (e.g., Williams and
Drolet 2005). One important way in which people incorporate emotions into their judgments is
when constructing affective forecasts, and it stands to reason that age differences in emotional
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processing would result in systematic differences in young versus older adults’ forecasting
ability. Indeed, work consistent with SST indicates that older adults display improved emotion
regulation and problem solving strategies (Kessler and Staudinger 2009; Scheibe and BlanchardFields 2009), which may confer advantages in constructing more accurate affective forecasts
(Kafetsios 2004).
Age, Knowledge and Domain Experience
In addition to age-related improvements in domain-general capabilities (affective processing
and mental representations of the future), age-related changes in situation-specific learning may
also play a role in reducing forecasting errors. To make accurate predictions about future
emotional states, people may rely on domain-specific semantic knowledge, including beliefs
about the levels and kinds of emotions generally experienced in particular situations (Robinson
and Clore 2002). Specifically, when making forecasts, people may identify when they have
experienced a comparable event in their past and accurately recall their emotional response to
that event (Wilson and Gilbert 2003), an ability that may improve with the accumulation of
experience and situation-specific knowledge. Some research has demonstrated that people rely
on such theories to remember their feelings in the past (e.g., McFarland & Ross 1987). For
example, evidence suggests that people who have prior experience with or knowledge of a
particular situation make more accurate affective forecasts concerning adaptation. For example,
Schkade and Kahneman (1998) showed that people who know someone who is parapelegic make
more accurate affective forecasts concerning the frequency with which paraplegics exhibit
happiness-related behaviors. It is possible that accumulated emotional experiences with prior
events and outcomes (a form of domain-specific knowledge) should help older adults accurately
construct personal forecasts and thereby circumvent future anhedonia errors. This logic is similar
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to that used in recent research on older adults that demonstrates that their relevant knowledge
and experiences compensates for the impact of age-related changes in cognitive abilities (Yoon,
Cole, and Lee 2009; Li, Baldassi, Johnson, and Weber 2013; Li et al. 2015; Zaval et al. 2015).
The Present Research
While research on age differences in decision making suggest that older adults may exhibit
greater accuracy in affective forecasting, there have been limited demonstrations of this
phenomenon. We examine age-related reductions for errors of future anhedonia, the recognition
that an outcome will produce similar affective responses regardless of whether it occurs now or
in the future. We present four studies that investigate this hypothesis. In studies 1 and 2, we test
the relationship between age and future anhedonia across a range of domains. Study 2 also rules
out a cognitive explanation of the age effect and tests the link between age-related differences in
future anhedonia and age-related increases in patience. In study 3, we explore the implications of
this age effect on post-purchase consumer judgments, and examine several theoreticallyimplicated mechanisms that may account for age differences in affective forecasting, identifying
the unique role of future self-continuity. Study 4 extends these results by experimentally
manipulating future self-continuity to infer causality.
STUDY 1: IMPACT OF AGE ON FUTURE ANHEDONIA FOR UTILITARIAN AND
HEDONIC GOODS
We designed study 1 to explore the relationship between age and the affective forecasting
error of future anhedonia (FA). Specifically, we predicted that FA would decrease across the life
span, such that older adults would be less likely to believe that they would experience less
intense affect if an event happened in the future than if the same event happens in the present.
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The study scenarios involved receiving either a financial reward or one of two consumer
goods. To manipulate affect-rich versus affect-poor consumption, participants were asked to
make decisions about both hedonic or utilitarian goods. To control for monetary value, both
products were presented as $35 Amazon.com gift certificates redeemable for either for
electronics (e.g., TVs, headphones) or for household products (e.g., cleaning products). We
hypothesized that age-related improvements in affective forecasting ability would lead to older
adults showing reduced FA for both categories of products.
Methods
We used a commercial survey firm to recruit a diverse sample of 645 U.S. participants
ranging in age from 18-89 (M = 45.7, SD = 19.4) to complete a web-based survey. Participants
were recruited in approximately even distribution across three age groups (18-35, 36-60, and
60+). See Supplementary Table S1 for demographic details. In a within-subjects design based on
the methodology used by Kassam et al. (2008), participants read scenarios and estimated their
present reaction to a present event, and their future reaction to a future event (at the time of its
occurrence). Specifically, participants first predicted their present reaction to receiving $35, “If
you were given $35 dollars right now, how happy would you be?” (1= not at all happy; 9 =
extremely happy). They then predicted their future reaction to the same event in 3 months, “If
you were given $35 dollars three months from now, how happy would you be at that time?”
Participants reported predicted happiness levels on a 9-point scale anchored from not at all
happy to extremely happy.
Participants also predicted their reactions to scenarios about receiving $35 Amazon® gift
certificates restricted to either electronics (hedonic) or home care (utilitarian) categories
(categories selected based on Crowley, Spangenberg, and Hughes 1992). Participants read brief
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descriptions about the gift card promotion and products. They were then asked to “imagine that
as a promotion today, Amazon® is going to give away a few $35 [Electronics/Home Care] gift
cards…How happy would you be if you won this home care gift card today?” and “imagine that
as an August promotion, Amazon® is going to give away a few $35 [Electronics/Home Care]
gift cards in 3 months…How happy do you predict you would you be if you won this gift card 3
months from now?” The two category scenarios were presented in counter-balanced order and
separated by a number of questions from an unrelated survey (see Supplementary Materials for
scenario text). Participants also provided demographic information, including gender, income
and education.
Results
To explore age differences in future anhedonia, we first ran an omnibus mixed-effects
regression on the affect ratings to assess the effects of time (within: now vs. 3 months), domain
(within: financial vs. hedonic vs. utilitarian), age (between: continuous variable), and their
interactions, controlling for participant-level variance. Consistent with the findings of Kassam
and colleagues (2008), participants demonstrated future anhedonia: We observed a main effect of
time, β = -0.31, z = -5.16, p < 0.001, such that participants predicted they would be less happy
about events occurring in 3 months. More importantly, this main effect of time was qualified by
an age × time interaction, in the predicted direction (β = .006, z = 2.11, p < .05), meaning that
future anhedonia errors were smaller for older adults.
We observed no main effects of domain (β = -0.04, z = -0.77; β = 0.02, z = .28, ps = ns),
no domain × time interactions (β = .12, z = 1.43; β = .07, z = 0.81, ps = ns), and no three-way
interactions (β = -.003, z = -0.77; β = -.001, z = -0.40, ps = ns), suggesting that future anhedonia
errors and age effects were similar across these three domains. Finally, we found a main effect of
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age, β = -0.01, z = -3.73, p < 0.001, such that older adults tended to feel less strongly about the
events in the present as well. This main effect of age was unpredicted but also not theoretically
interesting.
For each forecasting scenario and each participant, we also calculated a future anhedonia
index (FAI) for descriptive purposes, defined as the participant’s prediction of their present
reaction to the present event minus their future reaction to the future event. We ran separate
regressions FAI on age for each domain, again finding that older adults made smaller errors
compared to younger adults for the financial gain (β = -0.15, t(644) = -3.98, p < .001), utilitarian
good (β = -0.11, t(644) = -2.75, p < .01), and hedonic good (β = 0.08, t(644) = -2.02, p < 0.05).
As can be seen in Figure 1, FAI for the hedonic good decreases with age, and this is due to the
convergence of the predicted feelings for present and future events, as shown by the boxes in the
figure. The reduction of FA with age was also found using logistic regressions on whether or not
a participant exhibited any degree of future anhedonia (i.e., FAI > 0, for financial gain, z(644) = 3.54, p < 0.001, utilitarian, z(644) = -3.51, p < 0.001, and hedonic goods, z(644) = -3.54, p <
0.001. Results remained robust after controlling for gender, education, and income.
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FA Index
0.9
Present
0.8
Future
9
8
Future Anhedonia Index
0.7
0.6
0.5
7
0.4
0.3
Affect Rating
1
6
0.2
0.1
0
5
18-25
26-35
36-45
46-55
56-65
66-75
(n = 154)
(n = 92)
(n = 52)
(n = 46)
(n = 108)
(n = 135)
Age
Figure. 1. Mean Future Anhedonia Index scores for receiving a hedonic good (left y-axis; study
1) and mean affect ratings for both present and future scenarios (right y-axis) as a function of age
group. Error bars denote ±1 SEM. Note that age was entered as a continuous variable for all
regressions reported, but for ease of visualization, means for FAI are displayed categorically.
Discussion
These results provide initial evidence that older adults are less likely to wrongly believe that
they will experience less intense affect when an event happens in the future than when the same
event happens in the present. Future anhedonia appears to hold for consumer judgments
regardless of whether people considered money or gift cards that were more utilitarian or more
hedonic in nature, but older adults seem to make better affective forecasts in all domains.
In the next study, we provide further evidence of this relationship between age and future
anhedonia and explore whether age differences in affective forecasting ability may help explain
empirical evidence finding that older adults are more patient than younger adults.
STUDY 2: AGE, FUTURE ANHEDONIA AND TIME PREFERENCE
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The objectives of study 2 were threefold. First, we explored the robustness of the relationship
between age and FA by investigating FA age differences in domains such as financial gains,
financial losses, and free-time gains, as well as measuring FA using a second dependent
variable—willingness to pay.
Second, we examined the potential role of changing cognitive abilities over the life span.
Cognitive aging is a robust phenomenon whereby people’s speed and capacity for generating,
transforming, and manipulating information (i.e., fluid intelligence) decreases while their
experience, knowledge, and expertise (i.e., crystallized intelligence) increase (Salthouse et al.
2008). It is possible that age-related changes in one or both types of intelligence contributes or
detracts from the age-related changes in FA.
Third, we explored the potential relationship between age-related differences in affective
forecasting accuracy to age-related changes in patience on intertemporal choices. If younger
adults are more likely to believe that their future feelings regarding an event will be less intense
than their present feelings about that same event, then this belief may influence their tendency to
maximize benefits by enjoying them in the present.
Methods
In study 2, 619 U.S. participants ranging in age from 18 to 86 (M = 45.6, SD = 16.3) were
recruited from a private university’s online panel (n = 469) and a survey sampling company (n =
150) to ensure a broad sample with a wide dispersion of cognitive abilities and backgrounds.
Participants completed four waves of a web-based surveys consisting of cognitive ability,
decision-making, and demographic measures across the life span, including our target variables
and the DEEP Time task. (These data were collected as part of a larger study on aging and
decision making; see Li et al. 2015 for details).
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To measure future anhedonia, participants, in a within-subjects design, predicted their present
reaction to receiving $100, “If you were given $100 dollars right now, how happy would you be?”
(1= not at all happy; 9 = extremely happy). They then predicted their future reaction to a future
financial outcome at the time of its occurrence, “If you were given 100 dollars three months from
now, how happy would you be at that time?” We also investigated FA for temporal gains by
asking participants how happy they would be today [in 3 months], upon discovering that they had
an unexpected hour of free time. Finally, we assessed future anhedonia for financial losses by
asking, “If you lost $100 dollars right now [3 months from now], how sad would you be [at that
time]?” (1= not at all sad; 9 = extremely sad).
All participants who completed this first part of the study were invited to complete the next
part 3 months later, and 478 completed it (22.8% attrition). This delay period allowed for
measurement of the test-retest reliability for decision measures run as part of a larger study on
aging and decision making, which will not be included in the present results. In the second part,
we examined whether a standard economic measure of value—willingness to pay (WTP)—
revealed age differences in future anhedonia when the focal event involved receiving a consumer
good. Participants first responded to: “Imagine that as a promotion today [three months from
now], Amazon® gave you a box set of DVDs of your favorite TV show, worth $100.00…How
happy would you feel today if you were given this gift today [when you received the gift at that
time]?” They then estimated their WTP: “Now imagine that [in three months,] Amazon® is
considering selling the box set at a discounted price instead…[Three months from now, ] what is
the maximum amount of dollars you would be willing to pay for the boxset?”).
To measure cognitive abilities, we included several measures of fluid intelligence, including
Raven’s Progressive Matrices, Letter Sets, the Cognitive Reflection Test, and Numeracy, and of
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general crystallized intelligence, including the WAIS-III Information task and tests of synonym
and antonym vocabulary (see Li et al. 2015 for details).
Finally, to test whether age differences in future anhedonia are related to age differences in
patience, participants completed the DEEP Time task (Toubia et al. 2013). DEEP Time is an
adaptive measure of time preference that presents 20 binary choices between smaller, sooner
cash rewards and larger, later rewards. Participants’ time preferences were estimated from these
choices using Bayesian Markov chain Monte Carlo methods. Importantly, the DEEP Time task
estimates the quasi-hyperbolic discounting function (Laibson 1997), which includes both
standard, exponential discounting of future consequences (δ), and “present bias” (β), or how
much a decision maker discounts all future rewards regardless of delay length. For a full
discussion of this adaptive measure and its Bayesian estimation procedure, including validity
checks of the estimation of time preference parameters, see Toubia et al. (2013).
Results
We first ran an omnibus mixed-effects regression on the affect ratings to assess the
effects of time (within: now vs. 3 months), domain (within: financial gain vs. free time vs.
financial loss), age (between: continuous variable), and their interactions, controlling for
participant-level variance. As expected, we observed a main effect of time, β = -0.31, z = -3.97, p
< 0.001, such that participants predicted that they would experience less emotion in response to
events occurring in 3 months, indicative of future anhedonia. The main effect of time was
qualified by a marginal age × time interaction, β = .008, z = 1.74, p = .08, in the predicted
direction, such that future anhedonia errors were reduced for older adults.
We also observed main effects of domain, such that participants predicted more intense
affect ratings for the $100 financial gain compared with the hour of free time, β = -0.71, z = -9.16,
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p < .001. Participants also reported feeling sad about losing $100 than they felt happy about
gaining $100, β = -1.13, z = -14.6, p < .001. This was qualified by a time × domain interaction
for financial loss (vs. gain), β = 0.31, z = 2.81, p < .01, such that FA errors were observed for
financial gains (financial: Ms = 8.57 vs. 8.26, t(618) = 9.03) but not for losses (Ms = 7.43 vs.
7.44, t(618) = -0.03). The time × domain interaction for free time gain (vs. financial gain) was
not significant, β = -0.02, z = -0.24, p = ns (ratings for free time: Ms = 7.86 vs. 7.52, t(618) =
7.23). We observe no main effect of age, (β = -.001, z = 0.52, p = ns), no age × domain
interactions (β = -.005, z = 1.16; β = -.005, z = -1.10, ps = ns), and no three-way interactions (β =
-.003, t = -0.48; β = -.004, t = -0.70, ps = ns).
For ease of exposition, we also calculated a future anhedonia index (FAI = present minus
future) for each participant and scenario as we did for study 1. Regressions of FAI on age
showed that older adults made less FA errors compared to younger adults for the financial gain
(see Figure 2), (β = -0.16, t(616) = -4.00, p < .001), and hour of free time (β = -0.07, t(616) = 1.79, p = .07). However, we did not observe a significant effect of age on FAI for the $100 loss
scenario, β = -0.05, t(615) = -1.25, p = ns. Figure 2 again shows the declining FAI and the
convergence of the present and future ratings, paralleling study 1.
Age differences in future anhedonia also extended to receiving a consumer good and
WTP for it. There was a marginally negative relationship between age and FAI regarding receipt
of the gift and FAI for willingness to pay for the gift. A regression of FAI on age found that
older adults were less susceptible to FA in terms of happiness of receiving the DVD box-set, β =
-0.10, t(476) = -1.60, p = .11, and WTP for it, β = -0.08, t(476) = -1.64, p = .10.
Fluid and Crystallized Intelligence
20
Results of age differences in FAI remain the same after controlling for fluid intelligence in
multiple regression analyses. Consistent with prior research, fluid intelligence was higher for the
younger participants in this study (rage = -0.33, p < .001). However, measures of fluid
intelligence, such as Raven’s Progressive Matrices, were found to be negatively related to FA,
(i.e. financial gain scenario: r = -0.08, p < .05; free time scenario: r = -.10, p < .01), suggesting
that lower fluid intelligence is associated with increased FA errors. Thus, despite age-related
cognitive declines, which are associated with increased FA, older adults made less FA errors
compared with their younger counterparts.
Age differences in FAI were also robust controlling for age differences in crystallized
intelligence. Consistent with prior research, crystallized intelligence was found to be higher for
older participants (r = 0.33, p < .001). We found that measures of crystallized intelligence (i.e.,
measures of vocabulary) were negatively related to FA for the financial gain scenario (r = -0.12,
p < .01), but were not related to FA for the other scenarios (free time reward: r = -0.04, financial
loss: r = 0.001 ps = ns). Using a bootstrapping procedure with 5,000 samples (Preacher and
Hayes 2008), we observe partial mediation through crystallized intelligence of the effect of age
on FA for the financial gain scenario CI95 [-0.002, -0.001], p < .05), suggested that domaingeneral knowledge and experience may play a role in attenuating FA errors relating to financial
gains for older adults.
21
FA Index
Present
Future
1
9
0.9
8
0.7
0.6
0.5
7
0.4
0.3
Affect Rating
Future Anhedonia Index
0.8
6
0.2
0.1
0
5
18-25
26-35
36-45
46-55
56-65
66-75
(n = 154)
(n = 92)
(n = 52)
(n = 46)
(n = 108)
(n = 135)
Age
Figure 2. Mean Future Anhedonia Index for $100 financial gain (left y-axis; study 2a) and mean
affect ratings for both present and future scenarios (right y-axis) as a function of age group. Error
bars denote ±1 SEM.
Time preference and future anhedonia
We next examined whether observed age differences in future anhedonia were related to age
differences in time preferences. First, we found support for older adults have more patient time
preferences: Older adults displayed less present bias (the overvaluation of immediate outcomes,
where smaller β indicates greater present bias; r(608) = .10, p < .05) and lower exponential
discount rates (general impatience; where larger δ are more impatient; r(608) = -.09, p < .05).
More importantly, future anhedonia was associated with greater present bias. Participants
with higher FAIs for the $100 gain and for 1 hour of free time displayed more present bias
(money: r(607) = -.23, p < .001; time: r(606) = -.13, p < .001). Participants’ exponential discount
22
rates (δ) were also correlated with their FAI for the $100 gain, r(607) = 0.20, p < .001, and for
the 1 hour of free time, r(606) = .09, p < .05, indicating that less patient participants tended to
believe that they would be happier upon receiving $100 or an hour of free time in the present
than in the future. This suggests that future anhedonia is not only associated with the
overvaluation of immediate outcomes, as would be expected, but also predicts general
discounting behavior. Neither present bias nor exponential discount rates were related to FAI for
the $100 financial loss; β: r(607) = .064, p = ns; δ: r(607) = -.05, p = ns.
We also conducted mediation analysis with 5,000 bootstrapped samples for FAI as a
mediator of the effect of age on time preference and found significant mediation: Exponential
discount rate: age, direct: t(609) = -2.31, age, mediated: t(609) = -1.59, indirect effect; CI95 [0.001, -0.001], p < .001). Present bias: age, direct: t(609) = 2.53, age, mediated: t(609) = 1.71,
CI95 [0.001, 0.001], p < .001).
Discussion
Consistent with study 1 results, older adults again made more accurate affective forecasts in
terms of less future anhedonia. These findings suggest that with age comes the awareness that
events will likely feel the same, regardless of whether they occur in the immediate present or at
some delay in the future. Although all participants mistakenly believed that a receipt of a
monetary gain, an hour of free time, and a consumer good would bring them less happiness when
it happened in the future than when it happened in the present, this bias was diminished for older
adults.
Our findings also indicate that age differences in affective forecasting extend into the realm
of temporal discounting, as we find that increased patience in older adults is related to agerelated improvements in future anhedonia. Youthful short-sightedness has long been implicated
23
as a cause of poor judgment in risky decision-making. In line with this account, our results
indicate that age-related improvements in FA may be linked to the extent to which one discounts
future outcomes.
Thus far, our investigations have largely been limited to identifying age differences in future
anhedonia. We next investigate the potential underlying processes driving this age-related
improvement, as well as its impact on post-purchase consumer judgments. Some theorists have
suggested that problems with intertemporal decision making occur because of conflicts between
temporally distinct selves (Hershfield 2011). These previous findings suggest that age
differences in time discounting are at least partially explained by an age-related tendency to
perceive one’s present feelings as more connected to future emotions (Löckenhoff, O’Donoghue,
and Dunning 2011). Conceivably, age-related increases in future-self continuity may underlie the
relationship between age, discounting and future anhedonia bias that we observed in study 2.
STUDY 3: EXPLORING UNDERLYING PROCESSES
Studies 1 and 2 provided evidence that older adults show reduced future anhedonia. We next
focus on two questions raised by these results: What underlying psychological factors may
account for this age difference, and what are the implications of this age effect on post-purchase
consumer judgments?
The results of study 2 also suggest that the effect of FA may depend upon category and
valence, as we did not find FA for a $100 monetary loss. We therefore explore the
generalizability of the age effect across outcome valence and consumer product category. In
addition to examining future anhedonia for the loss of consumer goods, we examine whether the
type of product (hedonic versus utilitarian) described in the scenario moderates age differences
in FA. The product categories described in study 3 improve upon those used in study 1 in two
24
ways. First, we designed scenarios that eliminated gift cards and instead asked participants to
imagine that they would receive a product by mail. Second, we changed the product domains in
order to better distinguish between hedonic and utilitarian aspects.
As we have argued, there are many possible explanations for age differences in future
anhedonia. Thus, study 3 also assesses the role of a range of theoretically-implicated
mechanisms that may change with age, including future self-continuity, dispositional affect, and
domain-specific consumer experience. One hypothesis suggests that perceived future selfcontinuity is associated with age differences in future anhedonia. In our view, feeling
disconnected from the future self may generally lead to inaccurate valuations of future outcomes,
including future anhedonia.
We also explore one potential consumer judgment related to the construct of future
anhedonia; post-purchase regret. It is possible that when consumers do not project their current
tastes onto their later selves, future anhedonia may induce people to consume benefits sooner,
when their positive qualities are expected to be more intense, rather than later (Kassam et al.
2008). Indeed, if older (and potentially more experienced) consumers are less likely to commit
forecasting errors, then they may be less likely to experience purchase regret, or actually negate a
forecasting error by returning a product. To explore this hypothesis, study 3 also tests whether
age differences in future anhedonia are related to diminished post-purchase regret among older
consumers.
Methods
We recruited 752 U.S. participants ranging in age from 18 to 80 (M = 36.7, SD = 12.02) from
Amazon’s Mechanical Turk in three similarly-sized age groups (18-30, 31-45, 46+).
25
To measure future anhedonia, participants read five scenarios involving (1) receiving a
financial reward, (2) receiving a hedonic good, (3) receiving a utilitarian good, (4) losing a
hedonic good, and (5) losing a utilitarian good. We used the same financial gain wording as
study 1: “If you were given $35 dollars today [three months from now], how happy would you
be?” [1 = not at all happy; 9 = extremely happy].
For the hedonic gain scenarios, participants were asked to “imagine that as a special winter
[spring] promotion, Godiva® Chocolatier is mailing some people free gift baskets, filled with
chocolate worth $35 dollars [in three months]…How happy would you be [at that time] if you
received this gift basket today [three months from now]?” For the utilitarian gain scenarios,
participants were instead asked to imagine a scenario in which their utility company was mailing
customers a free package of light bulbs worth $35 dollars.
To measure future anhedonia for losses, participants were asked to imagine that they spent
$35 on [a bag of clothing you like from their favorite store (hedonic loss)/food you need from
your local supermarket (utilitarian loss)], but that the purchased item was then lost and cannot
be recovered. Participants were asked how sad they would be if this loss occurred today versus
three months from now on a 9-point scale [1= not at all sad; 9 = extremely sad].
Participants also completed measures of psychological constructs that may be related to
future anhedonia. To assess the extent to which participants felt their identity is enduring over
time, participants completed an index of future self-continuity, adapted from the Future SelfContinuity Scale (Hershfield et al. 2009; Hershfield and Thompson 2012). This scale asks
participants to specify which pair of 7 overlapping Euler circles (that range from no overlap to
almost complete overlap) best represent the extent to which their identity now overlaps with their
identity five years in the future. In addition, to examine whether domain specific consumer
26
experiences underlie age differences in future anhedonia, we assessed participants’ level of
experience with the focal event described in each scenario. For example, to assess experience
with the hedonic product, participants were asked to approximate how many times over the
course of their life they had received chocolates or sweets as a gift. Additionally, we examined
positive and negative affect, using the Positive and Negative Affect Schedule (PANAS; Watson,
Clark, and Tellegen 1988), which distinguishes clearly between two emotional dimensions of
subjective well-being.
Finally, to assess the relationship between future anhedonia, age, and post-purchase
judgments, participants answered questions about purchase impulsivity and consumer regret.
Participants were asked to report their level of agreement with the following statements on a 5point scale: “I like to plan purchases rather than relying on impulse” and “I often regret making a
purchase and feel buyer’s remorse” (adapted from Lee and Cotte 2009). Participants also
provided self-reports of how many times over the past year they had returned a purchase or let a
gift card expire.
Results
We first ran an omnibus mixed-effects regression on the affect ratings to assess the effects of
time (between: now vs. 3 months), domain (between: financial gain vs. hedonic product vs.
utilitarian product vs. hedonic loss vs. utilitarian loss), age (within: continuous variable), and
their interactions, controlling for participant-level variance. Participants exhibited future
anhedonia overall as evidenced by the main effect of time, β = -0.62, z = -18.30, p < .0001. The
main effect of time was qualified by time × domain interactions for hedonic losses (β = -0.20, z =
-2.25, p < .05) and for utilitarian losses (β = -0.32, z = -3.83, p < .001) but not for hedonic gains
(β = -0.069, z = -0.64, p = ns) or for utilitarian gains (β = 0.002, z = 0.02, p = ns). That is,
27
participants exhibited more future anhedonia for losses of both hedonic and utilitarian consumer
goods than for financial gains.
More importantly we again found an age × time interaction, β = 0.006, z = 4.41, p < .0001,
such that older adults showed less future anhedonia, with no significant three-way interactions.
As in the previous studies, for each forecasting scenario, we calculated for each participant a
future anhedonia index (FAI). Regressions of FAI on age showed that older adults made less FA
errors compared to younger adults for the financial gain, β = -0.09, t(751) = -2.59, p < .01, and
for the hedonic (chocolate) gain, β = -0.07, t(751) = -2.69, p < .05. However, we did not observe
age difference in FA for the utilitarian gain, β = -0.02, t(751) = -0.65, p = ns, or for product
losses (hedonic: β = -0.05, t(751) = -1.38; utilitarian: β = -0.04, t(751) = -0.98, ps = ns).
Role of Future Self-Continuity
Since future anhedonia may be related to discontinuity with the future self, we examined
whether individual differences in future anhedonia were related to differences in future selfcontinuity. Consistent with prior research (Rutt and Löckenhoff 2016), older adults felt more
connected to their future self, r = .29, p < .0001. Importantly, participants who felt their current
self would overlap considerably with their self five years into the future showed less FA across
all scenarios (hedonic gain: r = -.18, p < .001; utilitarian gain: r = -.14, p < .0001; financial gain:
r = -.12, p < .001; hedonic loss: r = -.12, p < .01; utilitarian loss: r = -.10, p < .01).
Next, we examined whether greater future self-continuity mediated the effect of age on future
anhedonia error across gain domains using bias-corrected confidence intervals constructed from
5000 bootstrapped samples (Preacher and Hayes 2008). For receiving a hedonic good, agerelated reduction in FA was mediated by future self-continuity (indirect effect; CI95 [-0.007, -
28
0.002], p < .01). Similarly, future self-continuity also mediated the effect of age on future
anhedonia for the monetary gain (CI95 [-0.004,-0.001], p < .05).
Consumer experience
We hypothesized that previous experience with a particular consumer product may underlie
age differences in future anhedonia for that product. As expected, older adults did report greater
experience with both the hedonic (chocolate) and utilitarian (light bulb) goods described in our
scenarios (hedonic; β = 0.10, p < .01; utilitarian; β = 0.19, p < .001). However, consumer
experience was not related to FAI. For example, participants who reported more experience
receiving chocolates or sweets as a gift were not less likely to exhibit FA for this scenario (r =
0.02, ns). Experience with the utilitarian gain was also unrelated to FAI for that scenario
(utilitarian gain; r = 0.02, p = ns).
Emotional well-being
Consistent with socioemotional selectivity theory, older adults reported less negative mood
than younger adults on the negative affect score of the PANAS (β = -0.18, p < .001), and
reported more positive mood than younger adults on the positive affect score (β = 0.21, p < .001).
However, negative mood was not significantly related to FAI for any of the loss or gain
scenarios (rs < .03, ns). Similarly, positive mood was not significantly related to FAI for any
scenarios (rs < .05, ns). That is, differences in emotional states did not explain age differences in
FA.
Post-purchase evaluations
Finally, we examined whether consumer behaviors relating to accurate affective forecasting,
including post-purchase regret and product return rates, are reduced among older consumers. We
found that age was negatively associated with the frequency of feeling “buyer’s remorse,” (β = -
29
0.12, t(751) = -3.31, p < .001), frequency of purchase returns (β = -0.09, t(751) = -2.50, p < .05),
and frequency of letting gift cards expire (β = -0.12, t(751) = -3.19, p < .001).
Importantly, these individual differences in post-purchase judgments were also related to
future anhedonia. For example, FAI for gain outcomes was positively associated with the
frequency of feeling post-purchase regret; hedonic gain: β = 0.09, t(751) = 2.38, p < .05.
Reduced errors in FA can alternatively be viewed as mediating the effect of age-related declines
in post-purchase regret. For example, we find FAI for the hedonic good partially mediated the
effect of age on post-purchase regret; (CI95 [-0.002,-0.0001], p < .05). Taken together, these
finding support the argument that age-related improvements in future anhedonia may be part of
an overall improvement in affective forecasting, and contribute to age-related declines in postpurchase regret.
Discussion
Results from study 3 replicate the finding that older adults are less likely than younger adults
to mistakenly believe that they will experience less intense affect when events occur in the future
than when they occur now. This age difference did not generalize across domains, however.
Although we did observe age-related improvements for hedonic product gains, we did not
observe age differences for utilitarian product gains. Further, age differences in FA were not
observed for loss outcomes, consistent with study 2 results. This discrepancy may be due to the
finding that people generally discount gains and losses differently (Appelt, Hardisty and Weber,
2012) and thus may not exhibit similar patterns for future anhedonia: Present bias for losses (the
desire to get the loss over with now) has been shown to translate to lower discounting, while for
present bias for gains (the desire to have the gain now) increases discounting behaviors.
30
In addition, we explore the practical implications of this age difference on consumer
behavior. With respect to post-purchase judgments and future anhedonia, we found a significant
correlation between FAI and post-purchase regret. Although this data is correlational, it is not
difficult to imagine a causal relationship between future anhedonia and purchase regret: Future
anhedonia may induce people to purchase a product sooner, when their positive qualities are
more intense, which may lead to more impulsive purchases, and consequential feelings of
buyer’s remorse among a younger consumer segment. Future work could benefit from
manipulations of these constructs to explore how these complex phenomena are linked.
Among the factors measured in the present study, including previous experience and current
affective state, only future self-continuity was significantly associated with age-related
improvements in future anhedonia. These findings support the notion that the degree that one
feels connected to one’s future self increases as people grow older, which leads to a greater
awareness that events will likely feel the same, regardless of whether they occur in the present or
at some delay. Although previous empirical studies have already verified the role of future selfcontinuity in temporal discounting, to our knowledge, this study is the first to find evidence
supporting the relationship between naturally occurring variations in future self-continuity and
affective forecasting. Prior research has shown that inducing psychological connectedness by
asking participants to consider reasons why their identity would remain stable over time can
reduce long-term discount rates (Bartels and Urminsky 2011). In study 4, we test whether
experimentally-induced feelings of future self-continuity can similarly influence future
anhedonia errors.
STUDY 4
31
The aim of study 4 was two-fold. First, we attempted to replicate the mediating effect of
future self-continuity on age differences in future anhedonia when the outcome occurred further
in the future (1 year). Based on the potential influence of perceived future-self continuity, we
anticipated that age differences in future anhedonia would be apparent (or even more pronounced)
for far future events, as younger adults would feel more dissociated from their future identity.
Second, we aimed to test whether an experimentally manipulated sense of connectedness to
future identity induces differences in people’s subsequent affective forecasts – specifically,
changes in future anhedonia.
Methods
Six hundred young (R = 18-30, M = 26.1, SD = 2.9) and old (R = 45-79, M = 55.0, SD = 7.4)
U.S. participants were recruited from Amazon’s Mechanical Turk, excluding middle-aged people
to improve power. To manipulate future self-connectedness, participants were randomly assigned
to one of two conditions and read a passage that described one’s identity as being highly stable
over time (high connectedness) or highly unstable over time (low connectedness), adapted from
Bartels and Urminsky (2011) (see Supplementary Materials for full text). Participants were then
asked to write a one-sentence summary of the passage.
Next, participants completed two of the measures of future anhedonia used in study 3; the
financial ($35) and hedonic good (chocolate) scenarios. For each scenario, participants indicated
how happy they would be about the event today, 3 months from now, and 1 year from now.
Finally, as a manipulation check, participants completed the Future Self-Continuity Scale, in
which they specified the extent to which their identity now overlaps with their identity five years
in the future.
Results
32
Overall, we replicated the effect of age on future anhedonia across scenarios and for both 3
month and 1 year delays. We found that younger participants displayed greater FAIs compared
with older participants when the future outcome was in 1 year: $35: β = -0.14 t(626) = -3.51, p
< .001; chocolate: β = -0.08, t(625) = -2.09, p < .05. Younger participants also showed greater
future anhedonia errors when the future outcome occurred in 3 months: $35: β = -0.11, t(627) = 2.68, p < .01; chocolate: t(625) = -2.74, p < .01.
Manipulating Future Self-Continuity
As expected, we found that reading about the stability or instability of one’s identity over
time influenced ratings of Future Self-Continuity. Participants shown the high-continuity
manipulation reported higher feelings of future self-continuity (M = 5.14, SD = 1.54) compared
with those in the low-connectedness condition (M = 4.77, SD = 1.64), t(1, 625) = 2.89, p < .01.
The connectedness manipulation was equally effective for young (Ms = 4.25 vs. 4.62, t(1, 296) =
2.20, p < .05) and old participants (Ms = 5.22 vs. 5.64, t(1, 296) = 2.20, p < .05).
We next explore whether future self-continuity mediates the relationship between the
connectedness inductions on future anhedonia by testing for the presence of an indirect effect
(i.e., Zhao et al., 2010). Using bootstrapped mediation analysis with 5000 samples (Preacher and
Hayes 2008), our results demonstrated that future self-continuity significantly mediated the
effect of the connectedness induction on future anhedonia at 3 month and 1 year delays for both
the $35 (3 month: CI95 [-0.09, -0.01], p < .01; 1 year: CI95 [-0.13, -0.02], p < .01) and chocolate
scenarios (3 month: CI95 [-0.05, -0.003], p < .05; 1 year: CI95 [-0.09, -0.01], p < .05).
Discussion
Results from study 4 replicate the finding that older adults are less likely to believe that they
will experience more intense affect when events occur in the present than the future (three
33
months as well as one year). Furthermore, this age effect is mediated by the degree to which one
perceives continuity between one’s current and future identity. The results of the future-self
continuity manipulation suggest that this link is causal.
GENERAL DISCUSSION
Investigating age-related changes in consumer decision-making constitute a vital, but
understudied area of consumer research (Carpenter and Yoon 2012). With the aging consumer
segment growing in purchasing power and economic significance (e.g., Copeland 2012),
researchers cannot afford to ignore how this group makes consumer judgments, including how
they make affective forecasts. Although the literature on affective forecasting is broad and wideranging, it has largely neglected to examine whether older adults share deficits in properly
predicting affective responses to future events. The present research attempts to address this gap
by investigating age differences in one type of affective forecasting error, and exploring what
underlying processes may contribute to age-related improvements.
Across four studies, we find that older adults are less likely to mistakenly predict that an
event would bring them less happiness when it happened in the future than in the present. These
findings make theoretical contribution on several fronts. First, given age-related cognitive losses,
it is critical to investigate whether other abilities may help to compensate for and mitigate
declines in decision making. Taken together, the present results add to the literature on age
differences in decision-making by suggesting that future anhedonia is a skill that improves across
the life span. These results are consistent with research demonstrating that emotion-related
capabilities are relatively spared or even enhanced in advancing age (Labouvie-Vief, DeVoe, and
Bulka 1989; Carstensen, Fung, and Charles 2003).
34
Our findings also add to a body of evidence demonstrating that people tend to devalue future
outcomes and have a fundamental inability to project their feelings into the future. We find that
increased patience in older adults is related to age-related improvements in affective forecasting
for future events. Moreover, we demonstrate that age is related to diminished future anhedonia
and that this may occur because older age fosters connection with the future self. Consistent with
this result, our results indicate that age differences in future anhedonia are driven primarily by
differences in judgments about future, rather than present, affect (see Supplementary Table 2)
While both younger and older adults made similar judgments concerning their immediate
affective responses to outcomes, older adults tended to predict that they would be happier upon
receipt of future gains. This pattern of results is consistent with notion that future self-continuity
contributes to age-related improvements in future anhedonia: Perceived connection to the future
self should influence judgments about future, but not present affective responses. Additional
research could expand on these results by exploring whether age differences in predictions of
future events are moderated by the event’s temporal distance from the present, by exploring a
range of future times.
Of the potential mechanisms measured in the present study, only future self-continuity was
significantly associated with age-related improvements in future anhedonia. Although we did
find that the other variables were significantly correlated with age, these constructs were not
associated with future anhedonia. Of course, there are possible mechanisms other than the ones
we have considered as well as potential alternative explanations for our findings. It is possible
that considering a wider distribution of pertinent consumer experiences and emotional responses
may be crucial to the age effects we obtained: Older adults’ advantage in affective forecasting
may stem from their ability to identify the specific emotions that arise from complex affective
35
experiences. The challenge for future research will be to further delineate the determinants of
age-related improvements in forecasting accuracy as a function of increased knowledge and
experience, particularly concerning emotional responses.
In addition to theoretical implications, we believe that knowledge of forecasting differences
between older and younger consumers has considerable practical value. We situated our research
in the context of consumer judgments and showed that younger adults are more likely to
mistakenly believe that they will experience less intense affect when the receipt of a consumer
good occurs in the future than in the present. An increased focus on how different consumer
segments make these types of nearly ubiquitous judgments may be crucial to developing
effective marketing strategies (Patrick and MacInnis 2007). This is important, as studies of
impulse buyers have shown that 80% refer to some negative consequences from their purchases
(Rook 1987), and 55% explicitly reported regret at least once in a purchase diary (Dittmar 2001).
Our results indicate that age-related differences in impulsive buying and purchase regret vary
with age and are related to future anhedonia. Future research is needed to confirm whether realworld errors in consumer forecasting, including actual purchase return rates, are decreased
among the aging segment. Moreover, investigations should ascertain the temporal stability and
reliability of forecasting errors, and whether this stability is moderated by age.
Additional research on consumer decision making and aging will be required in order to
develop an improved understanding of the different ways to maintain consumer satisfaction and
high decision quality across the life span (Yoon and Schwartz 2010; Carpenter and Yoon 2012).
Such research should take into account the rapidly growing evidence for age-related preservation
in consumer judgments, how older adults make long-term decisions regarding their emotional
36
well-being (including financial and investment decisions), and how they might optimize those
decisions—especially those involving tradeoffs between present and future outcomes.
37
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