The Effect of Emotions on Individuals' Inter-temporal Choices

Department of Business Administration – Quantitative Marketing
University of Zurich
Spring Term 2011
Supervisor: Prof. Dr. Florian Stahl
The Effect of Emotions
on Individuals’ Inter-temporal Choices
Zurich, August 25th, 2011
Giacomelli Stefano
Via Sceredascia 3a, 6828 Balerna
giacomes@gmail.com
Field of study: Management and Economics
Student ID: 06-983-514

Abstract
The aim of this paper is to investigate the still unknown relationship
between emotions and intertemporal choices of individuals. We in-
duced Bachelor and Masters students to experience happy, sad, and
angry emotional states. Then, collecting their WTPs for Internet sub-
scriptions, we constructed the respective discount functions from av-
erage monthly discount rates. The results confirm that showing pic-
tures related to the target emotions in combination with the evocation
of a past memory significantly induces happiness, sadness, and anger.
Moreover, we found evidence of decreasing and inverse N-shape time
discounting for our discount functions. Last, as we hypothesized, the
graphical analysis reveals that happy individuals discount the future
more than sad and angry ones in the short-medium term (up to six
months in duration). Moreover, happiness seems to induce people to
subscribe for longer contract durations (eighteen months), than sad-
ness, and anger do (twelve months). This is one of the first studies that
try to shed light on the effect of emotions on individual’s inter-
temporal choice. We hope our results can raise interest in this field of
study.
“The emotions aren't always immediately subject to reason, but they
are always immediately subject to action”
William James

i
Table of Contents
List of Figures and Tables .....................................................................I
List of Abbreviations..........................................................................IV
1. Introduction.........................................................................1
2. Theoretical Framework.......................................................6
2.1 Intertemporal choice Theory...............................................6
2.1.1 Criticism to DU model and Alternatives..................9
2.2 Emotions and Economic Theory ......................................14
2.3 Hypotheses........................................................................17
3. Data and Methods.............................................................20
3.1 Description of Data...........................................................20
3.2 Methods of investigation ..................................................24
4. Results ..............................................................................27
5. Conclusion........................................................................43
6. Bibliography ......................................................................V
7. Appendix............................................................................X

I
List of Figures and Tables
Figure 1: Discount Functions
Figure 2: Question 1 on three months WTP for an Internet sub-
scription
Figure 3: Discount function for Happy Condition (N=57)
Figure 4: Discount function for Sad Condition (N=47)
Figure 5: Discount function for Angry Condition (N=41)
Figure 6: Discount functions and Average Discount Rates from
Bachelor Class
Figure 7: Discount Functions and Average Discount Rates from
Masters Class (Control)
Figure 8: Percentage Variations in r between & Ques-
tionnaire
Figure 9: List of Emotions’ Levels Collected
Table 1: Brain’s Region Involvement Depending on Emotions
Table 2: Number of Observations
Table 3: Average Levels of Emotions in Bachelor Class
Table 4: Average Monthly WTP and Discount Rate (r)
Table 5: Kruskal-Wallis analysis of variance for Cheerfulness
Table 6: Mann-Whitney-Wilcoxon for Cheerfulness
Table 7: Summary of Kruskal-Walliss analysis of variance for
Sad and Angry experiments’ pairs of target emotions
Table 8: Summary of Mann–Whitney–Wilcoxon for Gloomi-
ness, Sadness, Furiousness, and Anger
Table 9: Summary of Mann–Whitney–Wilcoxon for Cheerful-
ness, Happiness, Furiousness, and Anger in Master
class (Control)

II
Table 10: Kruskal-Wallis analysis of variance for Arousal
Table 11: Mann–Whitney–Wilcoxon for Arousal
Table 12: Percentage Monthly Variations in between &
Questionnaire for Bachelor and Master
Table 13: Kruskal–Wallis analysis of variance for Happiness
Table 14: Mann–Whitney–Wilcoxon for Happiness
Table 15: Kruskal–Wallis analysis of variance for Sadness
Table 16: Mann–Whitney–Wilcoxon for Sadness
Table 17: Kruskal–Wallis analysis of variance for Gloominess
Table 18: Mann–Whitney–Wilcoxon for Gloominess
Table 19: Kruskal–Wallis analysis of variance for Furiousness
Table 20: Mann–Whitney–Wilcoxon for Furiousness
Table 21: Kruskal–Wallis analysis of variance for Anger
Table 22: Mann–Whitney–Wilcoxon for Anger
Table 23: Mann–Whitney–Wilcoxon for Cheerfulness Master
class (Control)
Table 24: Mann–Whitney–Wilcoxon for Happiness Master class
(Control)
Table 25: Mann–Whitney–Wilcoxon for Furiousness Master class
(Control)
Table 26: Mann–Whitney–Wilcoxon for Anger Master class
(Control)
Table 27: Mann–Whitney–Wilcoxon for Arousal Master class
(Control)
Table 28: Kruskal–Wallis analysis of variance for 3 Months Du-
ration Discount Rates

III
Table 31: Kruskal–Wallis analysis of variance for 12 Months
Duration Discount Rates
Table 32: Mann–Whitney–Wilcoxon for Happy vs Sad 15
Months Duration Discount Rates

IV
List of Abbreviations
DU model: Discounted Utility model
HD model: Hyperbolic Discounted model
Quasi-HD model: Quasi-Hyperbolic Discounted model
WTP: Willingness to pay
PET: Positron Emission Tomography

1
1. Introduction
In the past decades researcher’s interest in individual intertemporal
choice has gained more and more attention. A pioneer of this topic was
John Rae with his work The Sociological Theory of Capital1
in 1834.
With the intent to explain why nations differ in their wealth, Rae pro-
posed four psychological/sociological factors which can jointly explain
why a person should, or should not desire to accumulate during his/her
life. Other important studies were then conducted by Jevons2
(1888,
1905), and Eugen von Böhm-Bawerk (1890, 1891). All these authors
furthered Rae’s perspective that psychological determinants are a foun-
dation for individual time preference behavior.
In 1937 Samuelson introduced the concept of discount rate when formal-
izing his Discounted Utility Model. All the previous psychological fac-
tors involved in the intertemporal choice mechanisms were explained in
Samuelson’s model by that simple parameter. Despite Samuelson’s own
skepticism, economists from all over the world started to blindly trust in
the DU model mainly because its simplicity and elegance. Furthermore,
Koopmans (1960) provided a derivation of the model from a set of
proposition that pushed for an additional diffusion of the DU model.
In recent years economists as well as psychologists and neurobiologists
started to confute the DU model assumption using empirical evidence. In
particular Frederick et al. (2002) provided a critical review that exposes
the main criticism and major anomalies of the DU model. Moreover,
they enumerate alternative models such as Hyperbolic Discounting
1
Note that before Rae’s work Adam Smith already highlighted the determinant role of
intertemporal choice for the wealth of nations (Frederick et al. 2002).
2
Father and son.

2
Models, and Quasi-Hyperbolic Discounting Models. Among these mod-
els, the main area of interest is incorporating “visceral” influences on
behavior proposed by Loewenstein (1996), while a model that accounts
for the main anomalies reported to the DU model is the one of Loewen-
stein and Prelec (1992):
This section presents a model of intertemporal choice that accounts for
the anomalies just enumerated. Our model assumes that intertemporal
choice is defined with respect to deviations from an anticipated status
quo (or "reference") consumption plan; this is in explicit contrast to the
DU assumption that people integrate new consumption alternatives with
existing plans before making a choice.3
Several authors focus on other aspects of intertemporal choice such as
cognition in decisions (Ainslie 1975, O’Donoghue and Rabin 2000, and
Della Vigna and Malmendier 2006), reactions to cues (Mano 1992, Wil-
son and Daly 2004, and Winkielman et al. 2005), and delay of gratifica-
tion (Mischel and Ebbesen 1970, Mischel et al. 1972, and O’Donoghue
and Rabin 2001).
For this work, the publications of Elster (1998) and Loewenstein (2000)
are of interest. They analyze the impact of emotions in economic theory
shedding light on the important role played in decision-making and eco-
nomic behavior. What emerges from their results is that in recent year
little attention was paid by economists when considering emotion-
related arguments:
I think we need a better understanding of how emotions actually influ-
ence behavior before we can begin to think about how they may have
3
(Loewenstein and Prelec 1992, page 578)

3
evolved. … The more urgent task is to understand how emotions interact
with other motivations to produce behavior.4
Perhaps put off by their perceived unpredictability, economists have
only rarely incorporated visceral factors into their models of human
behavior.5
It seems reasonable that future studies of intertemporal choice should
consider to incorporating and trying to explain the impact of emotions
on individual’s behavior and decision-making process.
In spite of this, we have no knowledge of previous literature concerning
the effect of emotions on individuals’ intertemporal choices. Specifical-
ly, it remains unclear what mechanisms support the decision making
process and the consequent behavior when experiencing a given emo-
tion. Authors like Mano (1992) and Lewinsohn and Mano (1993) focus
on the role of unpleasantness and arousal in judgment formation, finding
them to have a strong impact. Winkielman et al. (2005) studied how
inducing emotions through showing emotional facial expressions can
cause aroused states, which have a direct impact on the willingness to
pay of the subjects. In addition to this evidence, physiological studies on
animals showed that there are dramatic changes in dopamine-associated
signals in rats’ nucleus accumbens during the development of self-
administration habit (Gratton and Wise 1994), and that reward-
associated cues alone can induce elevated extracellular dopamine
(Blackburn et al. 1989, and Pfaus et al. 1990). Similar study was con-
ducted on human beings using PET (positron emission tomography)
(Damasio et al. 2000). This leads to the conclusion that:
4
(Elster 1998, pages 72-73)
5
(Loewenstein 2000, page 427)

4
All emotions engaged structures related to the representation and/or
regulation of organism state, for example, the insular cortex, secondary
somatosensory cortex, cingulate cortex, and nuclei in brainstem tegmen-
tum and hypothalamus. These regions share a major feature in that they
are all direct and indirect recipients of signals from the internal milieu,
viscera and musculoskeletal frame.6
In addition, evidence for visceral responses can be found in Panksepp
(1998). Moreover, Davidson and Irwin (1999) proved that both in the
perception of emotional cue, and in the production of emotional re-
sponses, there is a main involvement of specific brain’s region.
It seems clear that not enough attention was given recently to the deter-
minant role that emotions can have in the individual’s decision-making
process for intertemporal choice.
The purpose of this paper is to investigate the effect that emotions play
on individual’s intertemporal choice through evocation of happy, sad,
and angry moments in one’s personal sphere. In particular, the research
wants to prove that when feeling one of the mentioned emotions, indi-
vidual’s willingness to pay for a wireless subscription is different de-
pending on the particular condition he/she is experiencing. Furthermore,
the average monthly discount rate for that service, in periods ranging
from three to twenty-four months, should have a proper pattern for each
of the three conditions submitted to the students participating the survey.
The results confirm the original hypotheses. It is shown that it is possible
to trigger basic emotions like happiness, sadness, and anger and the re-
lated arousal in individuals’ emotional sphere by self-evocation method
in combination with selected pictures. Furthermore, the results indicate a
6
(Damasio et al. 2000, page 1051)

5
clear matching between the three discounting functions patterns we cal-
culated and the recent evidence of decreasing discount rates found in
intertemporal choice literature. Finally, analysis of the role of emotions
on individuals’ intertemporal choice behavior shows that emotional
states actually impact on people’s discount rates in various way. In par-
ticular, evidence of higher time discounting during the happy condition
for three to twelve months subscription durations was found. For longer
time periods, the discounting functions share a similar pattern.
The results confirm the opinion that future studies should take the fun-
damental role played by emotions in intertemporal choice decisions
more into account. This paper argues that economists have neglected the
importance of emotional states in decision-making and their conse-
quences for too many years. This work attempts to help to show how
strong that impact can be, which would raise interest for further research
in this field. As a consequence, we believe that a better physiological,
psychological, and economical understanding of the determinants and
mechanisms underlying a certain behavior when feeling a specific emo-
tion, will be the key for novel and innovative marketing strategies.
The remainder of the paper is organized as follow. Chapter 2 provides a
wide theoretical framework to offer an insight into various disciplines
correlated to our study and to consequently construct hypotheses. The
data collection process is successfully described and some descriptive
statistics are presented in Chapter 3. Furthermore, the same section in-
troduces the methods used to investigate our hypotheses. Chapter 4 is
entirely dedicated to the interpretation of the results and to check their
robustness by some controls. The last chapter is left for conclusions and
further considerations and discussions.

6
2. Theoretical Framework
This section is entirely dedicated to a review of the relevant literature for
this work. In Subsection 2.1 we retrace the evolution of intertemporal
choice theory from its birth to the newest and most interesting approach-
es. Subsection 2.2 incorporates all of these elements that are related with
evocation of emotions, cue’s effect on individuals, and physiological
reactions interesting for intertemporal choice behavior. Finally, in Sub-
section 2.3, the hypotheses are stated supported by the preceding theo-
ries.
2.1 Intertemporal choice Theory
With the intent to explain why Nations differ in their wealth in his So-
ciological Theory of Capital (1834), John Rae first introduced inter-
temporal choice as a distinct topic. Rae identified six psychological and
sociological factors that were jointly assumed to be responsible for inter-
temporal choice behavior:
The desire to accumulate would then seem to derive strength, chiefly
from three circumstances.
1. The prevalence throughout the society of the social and benevolent
affections, or, of that principle, which, under whatever name it may be
known, leads us to derive happiness from the [future] good we com-
municate to others.
2. The extent of the intellectual powers, and the consequent prevalence
of habits of reflection, and prudence, in the minds of the members of the
society.
3. The stability of the condition of the affairs of the society, and the reign
of law and order throughout it.

7
It is weakened, and strength given to the desire of immediate enjoyment,
by three opposing circumstances.
1. The deficiency of strength in the social and benevolent affections, and
the prevalence of the opposite principle, a desire of mere selfish gratifi-
cation.
2. A deficiency in the intellectual powers, and the consequent want of
habits of reflection and forethought.
3. The instability of the affairs of the society, and the imperfect diffusion
of law and order throughout it.7
Frederick et al. (2002) identifies the first two factors as the most im-
portant in the individual’s desire for accumulation, while the last points
can be identified as limiting factors. The following discussions related to
this first psychological approach were made by N.W. Senior (1836),
W.S. Jevons (1888) and H.S. Jevons (1905). Senior believed that indi-
viduals judge the present and the future with the same weight but they
suffers the self-negotiation task during intertemporal choice. The other
two authors defend the thesis that people care only about immediate util-
ity (consumption) in their selfish delayed choices.8
In the second chapter of Capital and Interest (1890) E. von Böhm-
Bawerk challenges Senior’s Abstinence theory, and adds a new factor to
the Rae’s list in his next work The Positive Theory of Capital (1891):
IT is one of the most pregnant facts of experience that we attach a less
importance to future pleasures and pains simply because they are future,
and in the measure that they are future.9
7
(Rae 1834, pages 58-59)
8
See Frederick et al. (2002) for more details
9
(v. Böhm-Bawerk 1891, page 253)

8
Successively, according to the Austrian Economist’s previous publica-
tions, I. Fisher proposed a formal model of intertemporal allocation of
consumption in Part III of his work The Theory of Interest (1930).
Unfortunately, Rae’s first psychological approach, which lasted slightly
more than one century, was completely swept away from P.A. Samuel-
son’s DU model (1937):
( ) ∑ ( ) ( ) ( ) ( )
The Greek letter in the above formula represents the amalgamation of
all previous psychological elements into a single parameter, that is, the
discount rate. Samuelson was skeptical at first about the strong and un-
realistic assumptions in his model:
Our task now is to indicate briefly the serious limitations of the previous
kind of analysis, which almost certainly vitiate it even from a theoretical
point of view.10
Unfortunately, the DU model had a wide diffusion among economists
for many years. The cause of this wide spread can be explained in two
different points in time. The model was immediately widely accepted
thanks to Samuelson’s elegant formulation; this was mainly because of
its simplicity. At a second time, T.C. Koopmans (1960) provided a for-
mal derivation of the model from a set of axioms, which definitely estab-
lished it as the standard model of intertemporal choice (Frederick et al.
2002). Important critics of the DU model are now presented along with
its main anomalies, and the most used alternatives such as Hyperbolic
Discounted models and Quasi-Hyperbolic discounting models.
10
(Samuelson 1937, page 159)

9
2.1.1 Criticism to DU model and Alternatives
The first serious challenge to the DU model was posed by G. Ainslie in
1975 (Berns et al. 2007). In fact, while studying why human beings are
often oriented to choose the worse of two alternative rewards, even
when they are conscious of it, Ainslie casts doubt directly on the expo-
nential discounting assumption:
Highly concave delay curves from some pairs of smaller-earlier and
larger-later alternative rewards can cross, predicting an initial prefer-
ence for the larger reward, which changes in favor of the smaller (spe-
cious) reward as the smaller reward becomes imminently available. This
description accords with an intuitive view of what temptation is like.11
Similar conclusions can be found in G.F. Loewenstein (1996). If
Ainslie’s explanation of individuals’ short-time preferences in inter-
temporal behavior can be attributed to impulsiveness, Loewenstein’s
interpretation focuses on visceral influences. The result is that at a suffi-
cient level of intensity, visceral factors can cause a present-time orienta-
tion behavior. This evidence, known as hyperbolic discounting, is well
documented in several other studies (e.g. Thaler 1981, O’Donoghue and
Rabin 1999, Carstensen et al. 1999, and Zauberman 2003).
An example of HD model, state the following (Zauberman et al. 2009):
( ) ∑ ( ) ( ) ( )
It is evident from the functional form of ( ) that
( )
. This speci-
fication of HD model was first introduced by R. Herrnstein (1981) and
11
(Ainslie 1975, page 492)

10
later proposed by J. Mazur (1987). Other authors used different hyper-
bolic functional forms, however, all of them share the pattern of declin-
ing discount rates. For instance, G. Ainslie (1975) suggested ( ) ,
while G. Loewenstein and D. Prelec (1992) proposed a more sophisti-
cated version, ( ) ( ) . All these models of
non-constant discounting allow individuals time-inconsistent behavior,
challenging one of the strongest assumption of the DU model. In fact,
Samuelson’s model assumes that once an agent choose an alterna-
tive/plan (of consumption), she will not change her preference over time;
the so called Dynamic Consistency. Despite this, there is empirical evi-
dence of preference reversals, which can be attributed to anything from
hyperbolic time discounting (Frederick et al. 2002), to visceral influ-
ences (Loewenstein 1996), and to consumers’ subjective perception of
time horizon per se (Zauberman et al. 2009). Time-inconsistent behavior
was already mentioned by R. H. Strotz (1955-56) when analyzing “the
deliberate regimenting of one’s future economic behavior” (p. 165):
To summarize, we have said that the optimal plan of future behaviour
chosen as of a given time
(A) may be a plan which will be followed under conditions of certainty
(the harmtiony case), or
(B) may be inconsistent with the optimizing future behaviour of the indi-
vidual (the intertemporal tussle).12
For instance, consumers naiveté, and the consequent overestimation of
future consumption frequency, when subscribing to a gym for a long
period (Della Vigna and Malmendier, 2006) demonstrate the Myopia
concept first introduced by Strotz (1955-56) well. Another interesting
12
(Strotz 1955-56, page 180)

11
example of preference reversals was found (and explained by hyperbolic
discounting curves) monitoring pregnant women pre, during, and post
childbirth (Christensen-Szalanski, 1984). He asked 18 pregnant women
to make a non-binding decision between having or not anesthesia during
parturition. Most of them opted for avoiding medicaments during birth.
However, when they started to experience pain, most of them exhibited
preference reversals by asking for anesthesia.
Hyperbolic discount is not the only way to explain such preference re-
versals, they can also be modeled in terms of quasi-hyperbolic discount
function. A formalization of Quasi-HD model is the following (Zauber-
man et al. 2009)13
:
( ) ( ) ( ) ∑ ( ) ( )
( ) ( )
Again, as in the case of HD models, the discount rate decreases as the
time horizon gets longer. After comparing the shape of these alternative
models discount functions against the DU model one, it is evident from
Figure 1 that they successfully catch individuals’ present bias.
, -
Lowenstein and Prelec (1992) enumerated four anomalies of the DU
model. They first discuss the common difference effect, which is related
to the above explanation of time-inconsistent behavior and decreasing
13
For the first application of this Q-HD model see Laibson (1997).

12
discount rate over time. Second, critiques posed by empirical evidence
(Holcomb and Nelson, 1992) is the so called absolute magnitude effect,
meaning that large amounts of money suffer a smaller discounting if
proportioned with small ones. The third challenge to the DU model
comes from the gain-loss asymmetry. This shows that losses are strongly
discounted less than gains (Loewenstein, 1987). This evidence is in con-
flict with Samuelson’s assumption that the baseline consumption level is
constant across time periods. The last anomaly is the delay-speedup
asymmetry. Loewenstein (1988) found that when presenting people the
same option of speeding up and delaying consumption, in different for-
mats, the result is a framing effect. This directly conflicts any normative
theory, including DU model one.
Another Critical Review of intertemporal choice models is presented by
Frederick et al. (2002). This more recent analysis of the DU model as-
sumptions and anomalies takes into account all the previous critiques
proposed by Loewenstein and Prelec (1992). Furthermore, new empiri-
cal evidences, in contrast with Samuelson’s model, are illustrated. For
instance, applying hyperbolic functional forms to sets of data collected
from different studies leads to a significantly better fit than using the
exponential one (Myerson and Green 1995, Kirby 1997). Another im-
portant challenge to one of the flimsiest assumptions of the DU model is
the violation of consumptions independence. In fact, Loewenstein and
Prelec (1993) showed that individual’s preferences over profiles are af-
fected by the nature of consumption in periods in which consumption is
identical to the two profiles. Among the various recent critics to the DU
model assumptions, the authors highlight the weakness of the stationary
instantaneous utility function one. Generally, individuals’ preferences
change over years (Loewenstein and Angner 2003), as a consequence it
is unlikely that the cardinal instantaneous utility function can be constant

13
across time. Finally, the authors cast doubt on the independence of dis-
counting from consumption. According to them, it seems more reasona-
ble that people discount utility from food consumption and utility from
holiday using a different rate.
All the above literature and related empirical evidence against the DU
model explains the recent proliferation of alternative models such as
HD, Q-HD, and their variants (e.g. including visceral factors, reference
points, time orientation, etc.) well. Therefore, it is not surprising that
these models are more and more inclined to incorporate sophisticated
versions of those psychological mechanisms which underlay Rae’s first
analysis of intertemporal choice behavior.

14
2.2 Emotions and Economic Theory
The role of emotions in economic theory and economic behavior is not a
recent development. Already in 1789 J. Bentham, when he first intro-
duced the construct of utility, strongly believed in the prominent influ-
ence played by emotions in his theory:
Nature has placed mankind under the governance of two sovereign mas-
ters, pain and pleasure. It is for them alone to point out what we ought
to do, as well as to determine what we shall do. , - They govern us in
all we do, in all we say, in all we think: every effort we can make to
throw off our subjection, will serve but to demonstrate and confirm it.
, - The principle of utility recognizes this subjection, and assumes it for
the foundation of that system, the object of which is to rear the fabric of
felicity by the hands of reason and of law.14
As Rae’s (1834) first psychological approach to intertemporal choice
was swept away from Samuelson’s DU model (1937), so Bentham’s
(1789) attempt to explain the concept of utility involving emotions was
eclipsed by the Samuelson’s theory of revealed preference (1938).
Again, as the discount rate alone incorporated all previous psychological
factors, so did the index of preference substituted the emotional part
(happiness) in the construct of utility.
Fortunately, recent works (Elster 1998, Loewenstein 2000) revisited the
fundamental consequences of considering individual’s economic behav-
ior with respect to emotions. Moreover, not only economists but also
psychologists gave the above relation their attention. As a result, in re-
cent decades the emotions-related literature has experienced a dramatic
burst. Among the most important publications for investigation are the
14
(Bentham 1789: Chapter I1)

15
ones of Mano (1992), Loewenstein (1996), Damasio et al. (2000), and
Wilson and Daly (2004).
Economist H. Mano (1992) showed that pleasantness and arousal are
predominant dimensions in the individuals’ decision-making process and
its outcomes. In fact, his results lead to the conclusion that when experi-
encing a high level of pleasantness, individuals tend to spend more time
and to be more careful in decision strategies. Vice versa, high levels of
arousal cause people to behave in the opposite way15
. Moreover, the rela-
tion between positive/negative affect and high/low levels of arousal is
still puzzling. What is known is that, for example, negative affect and
intermediate arousal (e.g. sadness) give rise to different judgmental pro-
cesses and outcomes than positive affect and middle arousal (e.g. happi-
ness).
Another of the most accurate and revealing studies is the analysis of
visceral influences on behavior proposed by G. Loewenstein (1996). The
main point of his work is that visceral factors (e.g. anger, fear) under-
mine individual’s rational behavior and cause them to behave contrary to
their long-term self-interest. This can happen with or without full aware-
ness of the subjects, depending on how strong their visceral influence is.
Recent empirical confirmations of the concepts explained above come
from psychological/physiological researches conducted by Damasio et
al. (2000), and Wilson and Daly (2004). Using PET, the Portuguese neu-
rologist and his team investigated the neural basis of emotion and feel-
ing. To trigger a determinate emotion, that is, sadness, happiness, anger,
and fear, they ask the subjects participating in the experiments to re-
experience personal life episodes through detailed mental evocations of
those moments. PET’s outputs provide the map of the physiological
15
Note that opposite conclusions were found to Isen and Means (1983).

16
functional process for each condition experienced by the individual. Ta-
ble 1 below shows their results in the detail.
, -
What is really interesting for this work is the fourth, second to last, and
last row. In fact, when processing a reward-related stimulus the ventral
tegmental area (VTA) of our brain is activated by a signal from the cor-
tex. Successively, the VTA releases dopamine into the nucleus accum-
bens, the septum, the amygdala, and the prefrontal cortex. The neuro-
transmitter dopamine reaches the nucleus accumbens, which is situated
in the forebrain, and allows for desire promotion. This implies that when
experiencing emotions like happiness, sadness and anger, distinct re-
gions of the brain are involved in the process of a reward leading to dif-
ferent individuals’ behaviors. For example, there are evident significant
reactions of the brain during happy and sad conditions, despite this, their
patterns show qualitative distinctions.
Later, Wilson and Daly (2004) obtain results from magnet resonance
imaging data, which confirm the activation of the nucleus accumbes in
middle aroused men. Furthermore, they found that those men discount
the future more when stimulated with cues of sexual opportunity.
What emerges from analyzing emotions and economic theory is that to
investigate their effect on individuals’ intertemporal choices, we need to
take into account not only mere variations of individuals’ preferences
across time, but also physiological and psychological components like
arousal and visceral factors.

17
2.3 Hypotheses
It seems so clear from past literature that a multitude of factors work in
concert to promote a series of mechanisms which drive individuals to
determinate behaviors in reward evaluation and intertemporal choice
when experiencing happy, sad, and angry emotions. Arousal levels and
visceral factors surely play a determinant role, as well as different emo-
tional states do.
Knowledge of studies that try to explain how emotional state like happi-
ness, sadness, and anger influence the discount rate that one applies in
intertemporal choice for a subscription are not known. Despite this,
while stating hypotheses, the most important previous findings that are
relevant to this study are reviewed.
Concerning the possibility to trigger the above-mentioned emotions in
an experimental setting, Wild et al. (2001) found additional evidence of
the emotional contagion hypothesis (Hsee et al. 1990, and Hatfield at al.
1992). In particular, individuals viewing pictures of happy faces feel
happiness and showing sad facial expression evoke sadness within the
viewer. This process is almost immediate, that is, it takes more or less
500 millisecond to take place. Damasio et al. (2000) asked subjects to
evoke sad, happy, and angry episodes through the production of detailed
mental pictures of those moments in order to map, via PET, which brain
regions were involved during the feeling of each emotion. Their results
show that each one of the selected self-inducted emotions produce a
proper mental pattern. For the empirical investigation this paper uses
both pictures and self-evocation methods to trigger happiness, sadness,
and anger in the subjects participating in the data collection process.

18
Moreover, Winkielman et al. (2005) find that in low/middle thirsty peo-
ple the arousal level is higher for happy people than for angry ones16
.
H1 : Showing happy-, sad-, and angry-related pictures, in addition to
the individual’s self-evocation through writing a detailed person-
al life episode inherent to the target emotion, trigger as a conse-
quence happiness, sadness, and anger in the persons’ emotional
sphere.
H2 : The arousal level is similar for people during happy and sad
conditions but higher if those are compared with persons who
self-evoked angry emotional state.
Previous literature on intertemporal choice theory suggests hyperbolic
discounting pattern (Ainslie 1975, Thaler 1981, Loewenstein 1996, Zau-
berman et al. 2009, etc.). Furthermore, Stahl et al. (2010) provide evi-
dence of an inverse N-shaped pattern for discount rates of subscriptions,
where the point in which the discount rate increases correspond to the
maximum contract duration that consumers typically subscribe to a ser-
vice.
H3 : The discount rate for all happy, sad, and angry conditions de-
creases as the time horizon get longer showing inverse N-shaped
pattern.
H4 : The maximum contract duration for the wireless subscription
varies depending on the in-class triggered emotional state.
Finally, this paper’s main interest focuses on clarifying how happiness,
sadness, and anger directly impact individuals’ intertemporal choices.
Discount rate patterns for each emotional state directly from individual’s
WTP for an internet subscription will be attempted to be defined. The
16
A title of comparison, note that Mano (1992) defines sadness as middle arousing.

19
most related previous findings are presented in Winkielman et al.
(2005). They studied how WTP varies depending on the actual emotion-
al state (i.e. happiness and anger) and on the effect of a visceral factor
(i.e. thirst). However, their results do not confirm that happy people are
present oriented. In other words, the WTP of individuals experiencing
angry feelings is lower than for their happy feeling counterparts. This
result is believed to be influenced by the intensity of the visceral factor,
which strongly conditions individual’s behavior in the opposite way we
expect that it should be. Thus, the fifth and sixth hypotheses are in con-
trast with Winkielman et al. (2005), because happiness, sadness, and
anger are assumed to be basic emotions, thus not as influencing as vis-
ceral factors are.
H5 : The WTPs for the internet subscriptions of happy people is
higher in the short term (first six months) than for sad and angry
ones.17
H6 : The monthly discount rates of happy people are always higher
than for sad ones.18
17
This is equivalent to saying that the respective (to monthly WTP) discount rate is
higher in the short term (first six months) for happy people than for sad or angry
ones.
18
Apparently this can be partly in contrast with H2 in which happy and sad levels of
arousal were expected to be similar and higher than to angry ones. What plays in
favor of H6 is that similar levels of arousal do not directly imply same behavior
because of the contrasting impact of positive/negative affect (Mano 1992). Tak-
ing some insight from that two-dimensional model it is argued that, given H2 and
happiness present-time orientation effect (H5), the perfectly opposite affect in
happy versus sad conditions should leads to constantly higher discount rates for
self-inducted happiness.

20
3. Data and Methods
This section explains the data collection process and the methods that
were used to investigate our hypotheses. Subsection 3.1 explain how
happiness, sadness, and anger are triggered in subjects participating the
experiments, then summary statistics of the variables of main interest are
provide. Lastly, the data their reliability are discussed. Subsection 3.2 is
dedicated to the description of the methods used to investigate the six
hypotheses, and to motivate the them with respect to the previously de-
scripted data.
3.1 Description of Data
The final scope of the experiments is to obtain the data necessary to shed
light on the effect of emotions on individuals’ intertemporal choices. In
particular, we are interested in how three self-generated emotional states,
that is, happiness, sadness, and anger, influence the WTP for internet
subscriptions with variable durations ranging from three to twenty-four
months. The main challenge in this evocation process is to select an ap-
propriate strategy to actually trigger subjects’ emotions.
As a first step, three waves of questionnaires with bachelor’s students in
Business Administration and Management & Economics19
were per-
formed. In the first round of the experiment, they were asked to produce
a mental memory of a happy moment and to write a detailed summary of
that on a private sheet. Afterwards they respond to a questionnaire with
several questions about their feelings and emotions in that moment. Fur-
thermore, they express the own WTP for different durations of an inter-
19
During the lecture Introduction in Quantitative Marketing at the University of Zur-
ich.

21
net subscription contract (3 months, 6 months, …, 24 months). In the
following two weeks similar experiments were conducted for the two
other emotions, in chronological sequence, sad and angry. In contrast to
the first experiment (happy condition), they were asked to evoke the
emotions by writing a personal life episode, only after viewing a set of
pictures, related to the respective condition (sad or angry). During these
two waves, the students were not allowed to sit next to each other.20
Moreover, in weekly sequence, a control in a master class21
of Business
Administration and Management & Economics students was made, for
the angry and happy conditions using the same two procedure described
above for the bachelor class.22
Table 2 below shows the number of observations we left with for each
condition in each class.
Table 2: Number of Observations
Class
Experiment
Happy Sad Angry
Bachelor 57 47 41
Master 35 - 22
Notes: Recall that in the Master class we perform just two controls
20
This is justify by the fact that one can feel observed and consequently be shy when
writing a very private past feeling like sad or angry moments are.
21
During the lecture Innovation Marketing - Marketing of Innovations and Technology
Products at the University of Zurich.
22
Please note that all the treatments in the two class (bachelor and master) are per-
formed separately with at least one week of distance between each other. Moreo-
ver, to stimulate students to a reliable compilation of the questionnaires, a lottery
for winning an iPad2 was announced among participants who give serious an-
swers.

22
Table 3 provides some descriptive statistics relative to the average
arousal levels as well as to the average levels of experienced emotions
for the subjects in the bachelor class for each experiment, before and
after answering the questions related to their WTP for the subscriptions.
Table 3: Average Levels of Emotions in Bachelor class
Emotional
states
Happy Sad Angry
Before After Before After Before After
Arousal 3.61 3.04 3.72 3.53 2.71 2.95
Scared 1.74 1.84 2.21 1.89 1.73 1.54
Fearful 1.56 1.61 1.96 1.85 1.63 1.61
Disgusted 1.60 1.93 1.98 1.91 1.98 1.73
Hostile 1.84 2.21 2.15 2.34 3.93 3.46
Furious 1.68 2.23 2.64 2.47 4.51 3.98
Angry 2.26 2.68 3.02 2.74 4.80 4.20
Sad 2.02 1.81 4.19 3.19 2.71 2.15
Gloomy 2.04 1.93 3.94 3.06 2.78 2.29
Ashamed 1.47 1.49 1.87 1.70 1.51 1.54
Guilty 1.51 1.60 2.11 1.70 1.73 1.85
Cheerful 7.23 6.81 4.68 5.11 5.17 5.12
Happy 7.42 6.82 5.09 5.49 5.46 5.54
Notes: Arousal levels are measured on a scale ranging between 1 to 5, while the levels
of felt emotions on a scale ranging between 1 to 10. Bolded figures refer to target emo-
tions for each condition.
At first sight, it seems that the self-evocation process alone, as well as in
combination with viewing emotional pictures has the expected effect on

23
individuals’ emotional states. Moreover, the intensity of the feelings
seems to weaken very rapidly in all experiments.
Table 4 shows the average monthly WTP for each condition. Moreover,
the average monthly discount rate (r) is also displayed in a separate col-
umn.
Table 4: Average Monthly WTP and Discount Rate (r)
Duration
Happy Sad Angry
WTP r WTP r WTP r
3M 41.77 5.99% 43.18 4.89% 44.69 3.74%
6M 38.76 4.24% 39.88 3.77% 40.26 3.61%
9M 36.02 3.64% 36.64 3.45% 37.13 3.31%
12M 32.75 3.53% 35.07 2.96% 34.21 3.16%
15M 30.11 3.38% 31.41 3.10% 29.06 3.62%
18M 27.90 3.24% 28.96 3.03% 27.39 3.34%
21M 23.86 3.52% 26.60 3.01% 24.67 3.36%
24M 21.85 3.45% 25.05 2.88% 21.92 3.44%
Notes: The discounts rate above are calculated according to Stahl et al. (2010). The
relative formula is presented in Subsection 3.2..
Again, a raw analysis of the table above confirms the hypotheses that
happiness induces higher time discounting. Nevertheless, an accurate
data investigation is needed to obtain more meaningful results.
Overall, the data collected seem to be a very useful instrument for this
study’s final scope. We are also in possess of a small data set for further
controls and check of results’ reliability.

24
3.2 Methods of investigation
One of the main goals of this study is to clarify if and how individuals
experiencing different types of feelings change their intertemporal pref-
erences and consequently apply diverse discount rates depending on the
subscription’s duration. This information was collected indirectly by
WTP as follow:
Figure 2: Question 1 on three months WTP for an Internet subscription
Source: Zahlungsbereitschaft für ein Internet-Abonnement, Fragebogen Version
1: p.7.
The above example corresponds to Question 1. Furthermore, for each of
the three experiments, there were seven more identical questions. The
only difference being that they randomly increase by three months steps
in the duration of the hypothetical subscription up to twenty-four
months (e.g. Question 7 asks for 18 Months, and Question 5 for 24
Basic offer of the Internet Service Provider:
Price for a contract duration of 1 Month: 50.- CHF
Alternative offer of the Internet Service Provider:
Contract duration of 3 Months
For a Monthly Price of ____________ CHF/Month, I would accept
the Alternative offer of 3 Months contract duration instead of the
Basic offer (with monthly payment of the internet subscription charge)

25
Months).23
By completing the three waves of questionnaires in weekly
sequence, students provided their WTPs for an internet subscription with
durations ranging from three to twenty-four months, subject to evocation
of happiness, sadness, and anger.
To translate subjects’s WTPs to monthly discount rate we use the same
method of Stahl et al. (2010):
( )
In the above equation the discount factor ,
( ), and * +. Rearranging it with respect to , we
find the equation necessary to calculate the discount rate for a given du-
ration:
(
. /
)
Then, to obtain the discount function for each experiment the average
discount rates were calculated from observations for each of the dura-
tions, and then was simply plotted on a line chart.
All the average monthly discount rates, the average levels of arousal,
and the average intensity of feelings for each experiment, were collect-
ed, according to our hypotheses two main tasks were performed. The
first one is a graphical check of the three discount functions shapes for
testing H3 and H4. The second is slightly more sophisticated because of
the nature of H1, H2, H5, and H6. In fact, for these hypotheses the chart
23
Note that to randomize even more the results, students were randomly assigned to
two different versions of the questionnaires, which vary in order of the eight
questions.

26
analysis does not tell us if the differences, between happy, sad, and an-
gry conditions, are statistically significant. Furthermore, usual tests of
mean comparisons, like ANOVA or t-test, are not applicable to our data
because they do not satisfy the requested parametric assumptions.24
As a
consequence, we opted for non-parametric counterparts of the above-
mentioned tests. To check differences on a multivariate level the Krus-
kal–Wallis one-way analysis of variance was applied, then Mann–
Whitney–Wilcoxon tests were run as post-hoc analysis for differences in
groups.
The next section provides a deeper explanation of the results with re-
spect to the hypotheses. Moreover, we present some controls using the
observations collected in the masters class in which we performed the
angry, then the happy experiment.
24
In particular the sample data do not follow a normal distribution.

27
4. Results
The findings are presented following the hypotheses order. The first
claim is that the evocation technique we use for each of the three condi-
tions, that is, happy, sad, and angry, actually trigger happiness, sadness,
and anger in the students participating the experiment. The next tables
present the relative results. Table 5 introduces a multivariate level com-
parison of medians for the first condition tested in class. Note that
among the set of feelings collected for all experiments, just six of them
are useful for our investigation of H1, while the remaining are simply
controls.25
For the happy condition, the two relevant emotion levels to
compare against the ones collected in sad and angry experiments are
cheerfulness and happiness (target emotions).
Table 5: Kruskal–Wallis analysis of variance for Cheerfulness
Experiment Obs. Rank Sum
Happy 57 5570.00
Sad 47 2531.50
Angry 41 2438.50
Chi-squared with ties = 33.661 with 2 d.f.
Probability = .0001
Notes: Recall that we are testing
.
The table above clearly shows that there is a significant difference
among the medians of the three experiments for the variable cheerful-
ness.
25
Figure 9 in the Appendix displays all types of emotions we used.

28
To have more information about how the groups differ at univariate lev-
el, they are compared in pairs.
Table 6: Mann–Whitney–Wilcoxon for Cheerfulness
Pair 1 Obs. Rank Sum
Happy 57 3751
Sad 47 1709
z = 5.002
Probability = .0000
Happy 57 3472
Angry 41 1379
z = 4.753
Probability = .0000
Sad 47 1950.5
Angry 41 1965.5
z = -1.188
Probability = .2348
Notes: Recall that for each Conditions’ pair we are testing
univariate differences in medians for Cherfulness’s levels.
The results in Table 6 perfectly reflect what was expected. The level of
intensity of the emotion cheerfulness is significantly higher during the

29
happy condition than for the other two. Moreover, during sad and angry
experiments those lower levels are not significantly different from each
other. This confirms that only during the self-evocation of happy memo-
ries students strongly relive emotional states involving happiness.
The results for the second target emotion are in line with our expecta-
tions. In fact, the Kruskal–Wallis test confirms the differences among
the three conditions with respect to happiness levels ( = 27.832, p <
.05), further evidence is provided by the Mann–Whitney–Wilcoxon test
for all the three comparisons at the univariate level (happy-sad z =
4.527, Prob > |z| = 0.0000 ; happy-angry z = 4.387, Prob > |z| = 0.0000 ;
sad-angry z = -0.733, Prob > |z| = 0.4635).26
The same tasks were performed for the second and third experiment. In
the sad experiment the target emotions are sadness and gloominess,
while we are interested in significant differences in the levels of furious-
ness and anger among conditions in the angry experiment. The results
can be interpreted as for the happy condition, thus, fully supporting H1.
Table 7 and 8 briefly summarize them.
26
For simplicity only the results are reported. The relative tables, if not presented di-
rectly, can be found in the Appendix (i.e. Tables 13 and 14).

30
Table 7: Summary of Kruskal-Walliss analysis of variance for Sad and
Angry experiments’ pairs of target emotions
Sad Angry
Gloominess Sadness Furiousness Anger
Chi-squared
with ties (2 d.f.)
14.173 17.183 33.670 21.408
Probability .0008 .0002 .0001 .0001
Notes: When presenting just the test’s results, the relative tables can be found in
the Appendix (i.e. Tables 15, 17, 19, and 21)
Table 8: Summary of Mann–Whitney–Wilcoxon for Gloominess, Sad-
ness, Furiousness, and Anger
Target
Emotions
Happy-Sad Happy-Angry Sad-Angry
z Prob. z Prob. z Prob.
Gloominess -3.667 .0002 -1.741 .0816 2.018 .0436
Sadness -4.041 .0001 -1.415 .1572 2.533 .0113
Furiousness -2.792 .005227
-5.650 .0000 -3.305 .0010
Anger -1.762 .781 -4.507 .0000 -2.968 .0030
Overall, evidence was found that the procedure used to trigger happi-
ness, sadness, and anger in student’s emotional sphere is valid. The re-
sults are particularly strong because when comparing the target emotions
of the two experiment which are not directly related to them, their levels
27
Despite the fact that there is no difference in the medians of furiousness levels be-
tween happy and sad experiments, when comparing these against the angry one
we find significant differences which lead to evidence of higher levels of furious-
ness during angry experiment.

31
are not significantly different from each other but lower than the one of
the tested condition. This suggests that the feeling level of a target emo-
tion really increases when being self-generated during the experiment.
Generally, all the results above confirm the first hypothesis that the lev-
els of self-inducted emotions are higher for those that are expected to be
higher which vary according to the weekly condition. Finally, when us-
ing data collected in the master class as a control, the results are still the
same (Table 9).
Table 9: Summary of Mann–Whitney–Wilcoxon for Cheerfulness,
Happiness, Furiousness, and Anger in Master class (Control)
Target
Emotions
Happy-Angry
z Prob.
Cheerfulness 3.153 .0016
Happiness 2.674 .0075
Furiousness -3.304 .0010
Anger -3.727 .0002

32
To investigate the second hypothesis the same methods were applied.
First, we look at multivariate differences in arousal levels among the
three conditions by Kruskal–Wallis one-way analysis of variance. Then
significant univariate dissimilarities in medians between pairs of exper-
iments by Mann–Whitney–Wilcoxon test were checked for. The claim is
that subject’s arousal levels when experiencing happiness and sadness
are similar, and both higher than the one registered during the angry
condition. Table 10 and Table 11 illustrate the results.
Table 10: Kruskal–Wallis analysis of variance for Arousal
Happy 57 4650.00
Sad 47 4015.50
Angry 41 1919.50
Probability = .0001

33
Table 11: Mann–Whitney–Wilcoxon for Arousal
Happy 57 2933.5
Sad 47 2526.5
z = -0.404
Probability = .6864
Happy 57 3369.5
Angry 41 1481.5
z = 4.078
Probability = .0000
Sad 47 2617
Angry 41 1299
z = 4.572
Probability = .0000
Notes: Recall that for each Condition we are testing univariate
differences in medians
The evidence suggests that there is no statistically significant difference
between the arousal level registered during happy and sad conditions.
However, when comparing those levels to the one reached in the angry
experiment, both are significantly higher. The results are perfectly in

34
line with the second hypothesis. Unfortunately, using data collected in
the master class the null hypothesis of medians equality between the
level of arousal during happy and angry condition (z = 1.461, Prob > |z|
= 0.1440) cannot be rejected. This is probably due to the small number
of observations available.
The third and fourth hypotheses are directly implications of inter-
temporal choice theory for which a deep revision of such literature has
provided in Section 2.
The inverse N-shaped pattern (decrease-increase-decrease) of discount-
ing described in Stahl et al. (2010) was found by studying individual’s
WTP for membership plans in a health club. Given the similarities with
this study, we expect to find similar patterns for all the discount func-
tions we calculate with respect to average monthly discount rates. Fig-
ures 3, 4, and 5 reports them singularly.
Figure 3: Discount function for Happy Condition (N=57)
3.00%
3.50%
4.00%
4.50%
5.00%
5.50%
6.00%
6.50%
3M 6M 9M 12M 15M 18M 21M 24M
AverageDiscountRate
Months

35
Figure 4: Discount function for Sad Condition (N=47)
Figure 5: Discount function for Angry Condition (N=41)
2.50%
3.00%
3.50%
4.00%
4.50%
5.00%
3M 6M 9M 12M 15M 18M 21M 24M
AverageDiscountRate
Months
3.00%
3.20%
3.40%
3.60%
3.80%
4.00%
3M 6M 9M 12M 15M 18M 21M 24M
AverageDiscountRate
Months

36
The graphical analysis reveals a clear inverse N-shape discounting with
respect to subscription’s duration for the happy and sad condition. Dif-
ferently, the discount function for the angry condition seems to initially
follow that pattern by decreasing-increasing however instead of restart-
ing to decrease, it suddenly has a new raise at 18 months duration.
Generally, the evidence found by Stahl et al. (2010) also applies for this
study and supports H3. We can motivate the slightly anomalous shape of
the discount function for anger by looking at the very small range of the
average discount rate.28
The figures above are also useful to test H4. According to Stahl et al.
(2010) the points at which the discount function switches from decreas-
ing to increasing pattern corresponds to the maximum contract durations
that consumers typically subscribe to a service. We believe that the ef-
fect of evoked emotions might lead to differences in duration prefer-
ences. Looking at Figure 3 it is evident that in the happy condition this
point is clearly at eighteen months, while Figure 4 and 5 show that for
sad and angry experiments the rise occurs at twelve months.
Because we are not completely able to confirm the inverse N-shape dis-
counting for anger from the graphical analysis, we avoid to overreach in
unreliable interpretations for that condition. On the other hand, the re-
sults support the hypothesis that the maximum duration for the subscrip-
tion vary depending on the other two, in-class triggered, emotional
states.
A possible explanation of these findings is that happy people surely dis-
count the future more because of their short-time preference, but it is
28
This can be ascribed to the experiment setting for the angry condition, which being
the last performed might have suffered by a stronger “order effect” in computing
the questionnaire.

37
also true that they are more optimistic about future events in general.29
In
this sense, it is not surprising that a lot of people pay for a long member-
ship duration after they enjoyed the one-week free of entry, during
which one can have fun with new friends and get in touch with amazing
exercise equipment. However, because of the same logic, it is even less
surprising that most of those people stop to go to the gym (exhibiting
preference reversals) when they start the first month of routinely train-
ings with its correlated physical effort. Overall, the results support H4,
showing a maximum contract duration for the internet subscription of
eighteen and twelve months for the happy and sad condition respective-
ly. This can most likely be explained by the happy emotional state itself,
given that there is also a big rise at twelve months in the angry condi-
tion. However, we do not have clear evidence for this, consequently fu-
ture studies should investigate the underlying reasons for these findings.
The last set of hypotheses, H5 and H6, focus completely on the mere
effect of emotions on individual’s WTP and the consequently discount
rates they apply, with respect to durations. First of all, discount functions
differences are analyzed among the three conditions graphically by look-
ing at Figure 6.
29
It is not necessary to have empirical evidence proving that bad things do not stop
happening when one is in a bad mood, nor vice versa sequence of good things
happen to happy people. Anyhow, Kaniel et al. (2010) found evidence that opti-
mists are more successful.

38
Figure 6: Discount functions and Average Discount Rates from Bache-
lor Class
Preliminary results from the graphical analysis are very interesting. First,
as expected, the monthly average discount rates resulting from self-
evoked happiness are always higher than the ones calculated for the sad
conditions for all of the contract durations proposed. Furthermore, we
hypothesized lower discounting in the first six months for sad and angry
experiments, the results suggest an even longer lasting period. In fact,
only for contracts of more than twelve months duration, the discount
function for the angry condition intersect the happy one. In a long time
point of view, over twelve months, the sad condition line is the lowest
while the other two follow a very similar trend.
One can argue that the discounting shapes presented above are the result
of an “order effect”. In other words, when first filling in the question-
naire during the happy experiment, students are more cautious in their
choice, while in the next two waves they get more and more familiar
3M 6M 9M 12M 15M 18M 21M 24M
HAPPY (N=57) 5.99% 4.24% 3.64% 3.53% 3.38% 3.24% 3.52% 3.45%
SAD (N=47) 4.89% 3.77% 3.45% 2.96% 3.10% 3.03% 3.01% 2.88%
ANGRY (N=41) 3.74% 3.61% 3.31% 3.16% 3.62% 3.34% 3.36% 3.44%
2.50%
3.00%
3.50%
4.00%
4.50%
5.00%
5.50%
6.00%
6.50%AverageDiscountRate

39
with it. This might result in quick and less accurate responses on their
WTPs, causing sad- and angry-related discount functions to be generally
lower compared with the happy one. To disprove this idea, it is enough
to look at Figure 7, which displays the discount functions calculated
from the data collected in the masters class where the angry condition
was the first to be performed and the happy one was second.
Figure 7: Discount Functions and Average Discount Rates from Master
Class (Control)
Despite the order of the experiment being inverted, the discount function
for the happy condition is still the highest one. Moreover, the discount
rates converge for longer subscription periods using data from the mas-
ter class, such as for bachelor ones.
A last control was performed for the “order effect” by calculating the
percentage variations among the average discount rates of the first and
second condition in both bachelor and masters class. The idea is the fol-
lowing. For the bachelor class the happy condition was performed first
3M 6M 9M 12M 15M 18M 21M 24M
HAPPY (N=35) 5.61% 4.12% 3.16% 2.89% 3.21% 2.67% 2.72% 2.58%
ANGRY (N=22) 4.37% 3.25% 2.86% 2.73% 2.86% 2.53% 2.57% 2.43%
2.00%
2.50%
3.00%
3.50%
4.00%
4.50%
5.00%
5.50%
6.00%
AverageDiscountRate

40
and afterwards the sad one, Figure 6 shows that there is a decrease in the
average monthly discount rate for all durations from the first (happy) to
the second (sad) condition in that class. If there is “order effect” with
respect to our questionnaires, one would expect that in the masters class,
where angry one was performed first, then the happy condition, it will
comes up that the average monthly discount rate also decrease from the
first (angry) to the second (happy) condition. This formula was used to
calculate the percentage variations:
. /
There is no evidence from the results that the “order effect” takes place.
Table 12 and Figure 8 clearly challenge this possible confounding factor.
Table 12: Percentage Monthly Variations in between & Ques-
tionnaire for Bachelor and Master
Duration
Class
Bachelor Master
3M -18.4% 28.5%
6M -11.1% 26.9%
9M -5.2% 10.7%
12M -16.2% 5.7%
15M -8.3% 12.4%
18M -6.4% 5.2%
21M -14.7% 6%
24M -16.5% 6%

41
Figure 8: Percentage Variations in between & Questionnaire
It is evident from the graph that the order in which students fill in the
questionnaires does not influence the individua’s intertemporal choice.
The controls we made allow to ascribe the different discounting patterns
of the three experiments to the momentary self-triggered emotional state.
Using graphical and descriptive comparisons, these findings confirm H5
and H6.30
Unfortunately, when applying Kruskal–Wallis one-way analy-
sis of variance and Mann–Whitney–Wilcoxon test, all the results are not
statistically significant. This is not particularly surprising because of the
restricted number of observations and the small range of differences that
are being tested. However, in both bachelor and masters classes almost
30
Note that we define in H5 as short term a subscription duration of six months. The
results confirm the hypothesized pattern even for a longer time period (twelve
months).
-30.00%
-20.00%
-10.00%
0.00%
10.00%
20.00%
30.00%
40.00%
3M 6M 9M 12M 15M 18M 21M 24M
%ChangeintheAverageDiscountRatebetween1st
and2ndQuestionnaire
BACHELOR
MASTER

42
the same discounting pattern was observed tested conditions. This plays
in favor of further research in this field using broader experimental set-
tings or collecting the data directly from a real setting.
Overall, the results fully or partly confirm the six hypotheses. In particu-
lar, strong evidence was found for the way used to trigger happiness,
sadness, and anger. This is perfectly in line with earlier literature on ev-
ocation of emotions in an individual’s emotional sphere (Hsee et al
1990, Hatfield et al. 1992, Wild et al 2001). Moreover, the arousal level
for each of the three experiments respect the theoretical framework
(Damasio et al. 2000, Winkielman et al. 2005), suggesting that it plays a
determinant role in emotional states. The findings also support the mid-
dle hypotheses, which belong to the classical literature on intertemporal
choice (Ainslie 1975, Thaler 1981, Loewenstein 1996, O’Donoghue and
Rabin 1999, Carstensen et al. 1999, Zauberman 2003, Berns 2007, Stahl
et. al. 2010, etc.). In fact, the discounting patterns resulting from the
calculations do not deviate from the most recent studies. Thus, it is safe
to say that even when experiencing distinct memories and the related
emotions, that is, happiness, sadness, and anger, individuals apply de-
creasing discount rate over time. Finally, raw data support the view that
for each emotional state it is possible to track a proper discounting
shape, in particular that happiness decreases one’s WTPs and reversely
increases, as a consequence, the related discount rates if it is compared
with sadness. This last consideration is directly in contrast with scarce
previous studies, in fact Winkielman et al. (2005) obtained opposite re-
sults when studying thirsty individual’s WTP for happy and angry emo-
tional states.

43
5. Conclusion
The main goal of this paper is to clarify the effect of emotions on indi-
viduals’ intertemporal choices. The empirical evidence suggests that
their involvement cause people to behave differently depending on their
momentary emotional state. In particular, happy people showed a lower
WTP for durations ranging from three to twenty-four months when
compared with individuals who evoked sadness and anger. The results
can be summarized as follows.
Emotional states were successfully triggered in students by showing
them pictures inherent to the three target emotions and afterwards asking
them to mentally evoke a past memory and writing it on a private sheet.
This result is fundamental for further research on intertemporal choice
involving emotions. In fact, the possibility to significantly trigger basic
feelings like happiness, sadness, and anger in an experimental setting
really simplifies studies in this area. To reinforce the first finding even
more, differences in arousal levels of individuals experiencing the three
self-evoked emotions were tested. Perfectly in line with previous litera-
ture (Mano 1992, Winkielman et al. 2005), the results indicate that hap-
piness and sadness are moderately arousing and not significantly differ-
ent from each other, while anger produces significant lower arousal lev-
el. Again, this analysis is useful for further studies. As social and politi-
cal theorist John Elster (1998) wrote: “emotions without arousal are a
bit like Hamlet without the Prince of Denmark”31
. For this reason, future
studies should focus more on the strong linkage between arousal, as well
as the relation between positive and negative affect, and emotions which
then influence intertemporal decision behavior.
31
(Elster 1998, page 50)

44
The results obtained by investigating the third and fourth hypotheses
allow us to get some interesting insight on intertemporal choice theory
but also, on a broader perspective, on marketing selling strategy. First of
all, evidence of the inverse N-shape discount pattern with respect to sub-
scription duration described by Stahl et al. (2010) was found. More pre-
cisely, the discount function presents a hyperbolic shape until the maxi-
mum contract duration that a consumer is willing to subscribe to a ser-
vice is reached. Then, there it suddenly increases before it starts to de-
crease again. What makes this result important is that once more it cast
doubt on Samuelson’s DU model. In fact, in the last decades several
authors challenged the DU model assumption of constant discounting in
time (Ainslie 1975, Thaler 1981, Loewenstein 1996, O’Donoghue and
Rabin 1999, Carstensen et al. 1999, Zauberman 2003, Berns 2007, Stahl
et. al. 2010, etc.) providing various explanations for a decreasing dis-
counting pattern. Furthermore, our results allow us to get an idea of how
emotional states affect the maximum contract duration. For sadness and
anger that point is at twelve months, while for happiness it is at eighteen
months. This should be useful for psychological marketing strategies, in
fact, one can use emotional states as a driver for shorter or longer mem-
bership offers.
Finally and most importantly, it was investigated how happiness, sad-
ness, and anger directly impact individual’s intertemporal choice behav-
ior. The main interest here is in understanding the differences in subjects
discount rates for each duration depending on the above emotions.
Shedding light on these mechanisms gets raise attention mainly because
of the scarce consideration this argument has received. In fact there is no
previous knowledge of similar studies, except for a small section dedi-
cated in their analysis of the effect of visceral factors on individuals’
WTP by Winkielman et al. (2005). Probably because visceral factors

45
differ in intensity from basic emotional states like the ones we tested,
our results are opposite of theirs. In fact, by using descriptive statistics
and graphical comparison we found that individual’s WTP actually var-
ies depending on the three experimental settings. The evidence shows
that during the happy condition the collected discount rates are higher
than the ones in the sad experiment for all the durations proposed. This
is also true with the angry condition for the first twelve months. After
this membership time length, the three discount functions share a very
similar trend. The consequence of these results, if confirmed, can have
deep impact on both future studies involving intertemporal choice, and
for business in general. It is unquestionable that knowing exactly how a
happy, sad, angry person will behave in his choice over periods of time
will allow sellers to prepare ad-hoc contracts, or to discriminate among
consumers. Furthermore, the today’s non-existent literature would prob-
ably experience a strong rise in interest for establishing how different
emotional states impact on individals’ WTP and discount rates over
time, and consequently develop innovative marketing strategies.
Despite the evidence found, this study suffers from remarkable limita-
tions. It is the first time that an economical empirical study directly ap-
proaches such a niche argument as the effect of emotions on individuals’
intertemporal choice. As one can guess from the theoretical framework,
this study not only incorporates economic factors, but also psychologi-
cal, biological, physiological, and neurological ones. Given this unusual
mix of disciplines, it would be arrogant to pretend that these results are
enough to causally explain the mere effect of emotions on people’s be-
havior within this puzzling set of inter-correlated mechanisms, which is
still almost unknown. The main limitation of this paper is identifiable in
the not fully satisfactory completeness of the data set, in particular in the
number of observations. In fact, the results regarding the direct effect of

46
the three emotions tested on individual’s intertemporal choice are not
statistically significantly different when applying Mann–Whitney–
Wilcoxon tests among conditions. However, the clear pattern that
emerges in favor of higher discounts rates for the happiness experiment
is undeniable after looking at the descriptive statistic. Another weakness
of this study is the experimental setting from which the data were col-
lected. Student’s effort in answering about their WTPs for a hypothetical
subscription is quite far away from the complex process that is beneath a
real decision. Thus, it is desirable that future studies evaluate the option
of collecting the data directly from subscription services providers, or
offering stronger incentives (e.g. monetary rewards).
Finally, we want to specify that this study does not intend to immediate-
ly clarify all the mechanisms among emotions and intertemporal choice.
However, we clearly found evidence of several guidelines that can serve
for further studies. In fact, we suggest that future research should focus
more on the interconnections between emotional states and arousal.
Moreover, it could be interesting to better investigate the causes that
lead to different maximum contract duration from a real setting. Lastly,
further studies should be conducted to investigate the psychological
mechanisms underneath these first revelatory findings regarding emo-
tions and intertemporal choice discounting.
For too many years economists neglected the importance of emotional
states in intertemporal choice decision-making and their consequences.
This paper is meant to show how strong that impact can be, raising in-
terest for further research in this area.

V
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X
7. Appendix
Figure 1: Discount Functions
Source: Berns et al. (2007), p. 483

XI
Figure 9: List of Emotions’ Levels Collected
Source: Fragebogen Version 1, p. 5

XII
Table 1: Brain’s Regions Involvement Depending on Emotions
Source: Damasio et al. (2000), p. 1052

XIII
Table 13: Kruskal–Wallis analysis of variance for Happiness
Happy 57 5448.00
Sad 47 2658.00
Angry 41 2479.00
Probability = .0001

XIV
Table 14: Mann–Whitney–Wilcoxon for Happiness
Happy 57 3678.5
Sad 47 1781.5
z = 4.527
Probability = .0000
Happy 57 3422.5
Angry 41 1428.5
z = 4.387
Probability = .0000
Sad 47 2004.5
Angry 41 1911.5
z = -0.733
Probability = .4635

XV
Table 15: Kruskal–Wallis analysis of variance for Sadness
Happy 57 3389.50
Sad 47 4316.00
Angry 41 2879.50
Probability = .0002

XVI
Table 16: Mann–Whitney–Wilcoxon for Sadness
Happy 57 2401.5
Sad 47 3058.5
z = -4.041
Probability = .0001
Happy 57 2641
Angry 41 2210
z = -1.415
Probability = .1572
Sad 47 2385.5
Angry 41 1530.5
z = 2.533
Probability = .0113

XVII
Table 17: Kruskal–Wallis analysis of variance for Gloominess
Happy 57 3400.50
Sad 47 4202.00
Angry 41 2982.50
Probability = .0008

XVIII
Table 18: Mann–Whitney–Wilcoxon for Gloominess
Happy 57 2456.5
Sad 47 3003.5
z = -3.667
Probability = .0002
Happy 57 2597
Angry 41 2254
z = -1.741
Probability = .0816
Sad 47 2326.5
Angry 41 1589.5
z = 2.018
Probability = .0436

XIX
Table 19: Kruskal–Wallis analysis of variance for Furiousness
Happy 57 3027.00
Sad 47 3432.50
Angry 41 4125.50
Probability = .0001

XX
Table 20: Mann–Whitney–Wilcoxon for Furiousness
Happy 57 2603.5
Sad 47 2856.5
z = -2.792
Probability = .0052
Happy 57 2076.5
Angry 41 2774.5
z = -5.650
Probability = .0000
Sad 47 1704
Angry 41 2212
z = -3.305
Probability = .0010

XXI
Table 21: Kruskal–Wallis analysis of variance for Anger
Happy 57 3291.00
Sad 47 3340.00
Angry 41 3954.00
Probability = .0001

XXII
Table 22: Mann–Whitney–Wilcoxon for Anger
Happy 57 2733.5
Sad 47 2726.5
z = -1.762
Probability = .0781
Happy 57 2210.5
Angry 41 2640.5
z = -4.507
Probability = .0000
Sad 47 1741.5
Angry 41 2174.5
z = -2.968
Probability = .0030

XXIII
Table 23: Mann–Whitney–Wilcoxon for Cheerfulness Master class
(Control)
Single Check Obs. Rank Sum
Happy 22 828
Angry 35 825
z = 3.153
Probability = .0016

XXIV
Table 24: Mann–Whitney–Wilcoxon for Happiness Master class
(Control)
Happy 22 800
Angry 35 853
z = 2.674
Probability = .0075

XXV
Table 25: Mann–Whitney–Wilcoxon for Furiousness Master class
(Control)
Happy 22 451
Angry 35 1202
z = -3.304
Probability = .0010

XXVI
Table 26: Mann–Whitney–Wilcoxon for Anger Master class (Con-
trol)
Happy 22 417
Angry 35 1236
z = -3.727
Probability = .0002

XXVII
Table 27: Mann–Whitney–Wilcoxon for Arousal Master class (Con-
trol)
Happy 22 721.5
Angry 35 931.5
z = 1.461
Probability = .1440

XXVIII
Table 28: Kruskal–Wallis analysis of variance for 3 Months Duration
Discount Rates
Happy 57 4619.00
Sad 47 3245.50
Angry 41 2720.50
Probability = .1586

XXIX
Discount Rates
Happy 57 4400.00
Sad 47 3297.00
Angry 41 2888.00
Chi-squared with ties = .975 with 2 d.f.
Probability = .6141

XXX
Discount Rates
Happy 57 4314.50
Sad 47 3308.00
Angry 41 2962.50
Probability = .8027

XXXI
Table 31: Kruskal–Wallis analysis of variance for 12 Months Dura-
tion Discount Rates
Happy 57 4501.00
Sad 47 3169.50
Angry 41 2914.50
Probability = .3488

XXXII
Table 32: Mann–Whitney–Wilcoxon for Happy vs Sad 15 Months
Happy 57 3034.5
Sad 47 2425.5
Probability = .7827

XXXIII
Happy 57 3039
Sad 47 2421
Probability = .7599

XXXIV
Happy 57 3134.5
Sad 47 2325.5
Probability = .3511

XXXV
Happy 57 3171
Sad 47 2289
Probability = .2397

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