Perspective Chapter: Emotion and Economic Decision Making

Abstract

This chapter delves into the intricate relationship between emotions and economic decision-making, challenging the traditional rational agent model prevalent in mainstream economics. Drawing from psychology, neuroscience, and behavioral economics, we explore how emotions influence decisions under risk and uncertainty, intertemporal choices, and social decisions. It argues that emotions, far from being peripheral, are central to the decision-making process. The chapter also discusses the evolutionary origins of emotions, highlighting their adaptive functions in small hunter-gatherer societies characterized by social interdependence and environmental uncertainty. It also highlights the potential of emotional intelligence and strategies such as distancing to temper negative emotional sway, enabling unbiased appraisals of situations. Emotions provide important information for making complex decisions, and one important component of emotional intelligence lies in understanding and harnessing the power of emotions to make more informed and optimal choices in economic settings. The chapter serves as a review for anyone interested in the intersection of emotions and economics, offering both theoretical insights and practical strategies for improving decision-making.

1. Introduction

For decades, the neoclassical framework based on the rational choice model has been dominating in the mainstream economics. This framework postulates that individuals, as rational agents, make decisions based on objective evaluations of costs and benefits in order to maximize the expected utility. The archetype of such decision-makers is often termed “Homo Economicus,” beings envisioned to navigate the economic landscape through a purely cognitive lens, untouched by the whims of emotions. The character of Spock from Star Trek epitomizes this notion; though not entirely devoid of emotions, his decisions predominantly resonate with logical, emotion-detached reasoning.

The rational choice model essentially has a consequentialist perspective, where utility is only a function of realized outcomes. Though not completely ruling out the role of emotions, this model assumes the influence of emotions can be cogently discerned and factored into the utility function through cognitive mechanisms [1]. Emotions unanticipated or unregulated by cognition are deemed obstacles to optimization and hence are glossed over by a rational decision-maker and left out of the model.

Emerging research in both psychology and economics, however, suggests that this traditional view is incomplete and potentially flawed. Many studies have indicated that utility transcends realized outcomes, encompassing emotions experienced in the anticipatory phase preceding those outcomes [2, 3]. A compelling case for the centrality of emotion in decision-making comes from neuroscience. Antonio Damasio [4] presented the case of a successful lawyer whose decision-making ability was crippled post-minor brain surgery. Despite retaining his intellectual prowess, he was paralyzed in the face of decisions. These symptoms were found to be linked to a lesion severing the connection between the amygdala, a hub of emotional processing, and the prefrontal cortex, the seat of “rational” thinking. This case accentuates that emotions are not mere adjuncts but fundamental to decision-making – without the final push by emotions, people simply cannot reach any decisions.

Further insights into the interplay of emotions and economic behavior come from studies like that of Knutson et al. [5], which revealed that purchasing decisions are often predicted by activations in brain regions associated with emotions rather than rational deliberation. The nucleus accumbens (NAcc) was activated in anticipation of rewards, while the insula was activated in anticipation of pain. The pros and cons of purchase were distilled into feelings, which then competed in a contest of conflicting emotions to determine the final decision. Consequently, it is suggested that reason primarily serves to inform these feelings, rather than to dictate the decision-making process. In essence, information can only influence a decision if it “talks” to emotion. The results of these studies resonate with the philosopher David Hume famous saying “Reason is, and ought only to be the slave of the passions.”

The notion that emotion is a significant player in decision-making is not novel. Emotion has long been intertwined with the study of economics, tracing back to the foundational works of Adam Smith and Jeremy Bentham. Before his well-known book The Wealth of Nations, Smith delved into the emotional resonance in human interactions, in his earlier and lesser-known book The Theory of Moral Sentiments. Bentham’s conception of utility intertwined pleasure and pain, hinting at an emotional appraisal at the heart of economic decisions. However, as economics evolved over time, the attention paid to emotion dissipated, giving way to the neoclassical school of thought which emerged in the late nineteenth century. This shift marked a transition toward a more mathematical and systematic exploration of economic behavior, sidelining the emotional and moral substrates of economic decisions. The appeal of quantifiable predictions that neoclassical economics offered seemed to overshadow the nuanced and often messy realm of emotions.

This exclusion of emotion from economic models has faced challenges in recent years, notably with the rise of behavioral economics. Scholars have highlighted the numerous ways in which real-world economic behavior deviates from the predictions of neoclassical models. They argue that emotions, biases, and heuristics significantly impact economic decisions [6]. Acknowledging the interplay of emotion and rationality is crucial for a holistic understanding of economic behavior. As the field continues to evolve, the insights from both classical and modern thinkers provide a richer understanding of emotions and economic decision making.

This chapter discusses the complex relationship between emotion and economic decision-making, challenging the conventional wisdom and exploring the nuances that emotions bring to our choices and actions. Beginning with an exploration of the evolutionary basis and functions of emotions, the chapter navigates through their influence in varying economic contexts: decisions under risk and uncertainty, intertemporal decisions, social decisions, and finally, a discussion on strategies for enhancing emotional intelligence in decision-making. Through this journey, the chapter aims to foster a richer understanding of the intertwined realms of emotions and economic decision-making, beckoning toward a more holistic appreciation of the economic behavior landscape.

2. Emotions and decision making

Our emotional responses to events can be swift and powerful, sometimes leading us to act before our rational side has a chance to intervene. Numerous studies have demonstrated how emotional responses can overpower rational reasoning. As pointed out by Jonathan Haidt [7], our emotional system is like an elephant, while our rational system is like the rider on the elephant. Even though the rider thinks he is in control, it is the elephant that often determines our actions. If the elephant wants to go in a certain direction, it is challenging for the rider to steer it elsewhere.

From an evolutionary standpoint, the emotional brain, or the limbic system, evolved before the “rational brain” that primarily “resides” in the prefrontal cortex. This evolutionary sequence suggests that emotions have been a fundamental part of human decision-making long before the development of complex cognitive abilities and executive functions. Indeed, studies in neuroscience have shown that the neural pathways for emotional responses are quicker than the pathways for cognitive processing, suggesting that emotions respond to environmental stimuli before cognitive appraisal occurs [8, 9]. The “somatic marker hypothesis” proposed by Antonio Damasio [10, 11] suggests that emotional processes guide or bias behavior and decision-making. When faced with a decision, internal bodily states associated with previous emotional experiences can be re-evoked as somatic markers. These markers serve as a kind of “gut feeling” or intuitive signal, helping to guide decision-making, even before we consciously deliberate on the options.¹ For instance, in the real-world scenario of financial trading, a trader might experience a gut feeling, derived from past emotional experiences, that guides their decision on whether to buy or sell, often before a thorough analysis is performed.

Somatic markers enable us to quickly reach decisions in complex environments, and they do an excellent job of guiding us toward beneficial choices in most situations. However, in novel or significantly altered environments, these emotional cues might mislead. For instance, fear associated with risk and uncertainty can lead to risk aversion and a present bias [2]. While these responses may have been evolutionarily advantageous in environments characterized by high uncertainty and danger, they manifest as low-risk tolerance and heightened impatience, which are maladaptive in the modern world and generally feature safer and more stable conditions [6]. This calls for a balanced interplay of emotion and rationality in decision-making.

When discussing emotional influence on decision making, researchers have identified two distinct types of emotions [13]: integral emotions and incidental emotions. Integral emotions arise directly from the judgment or choice at hand. They are intrinsically linked to the specifics of the decision-making process and are evoked by the potential outcomes or the process itself. For instance, when faced with an investment decision, the anxiety about potential loss or the excitement of a potential gain are task-related emotions. These emotions are directly tied to the perceived benefits or risks of the decision and are integral to the cognitive evaluation of the situation. They often serve as immediate feedback mechanisms, guiding individuals toward or away from certain choices based on the emotional valence associated with each option [2].

Incidental emotions, on the other hand, are derived from an individual’s current state or recent experiences unrelated to the judgment or choice at hand [13]. Although incidental emotions are not directly related to the decision-making task, they are shown to sway the decision-making process [14]. For example, someone who has just experienced a personal loss might approach a completely unrelated decision with heightened caution or pessimism. Incidental emotions can act as background filters that color our perceptions and judgments [15, 16].

Integral emotions can be further categorized into immediate emotions and anticipated emotions [1]. While immediate emotions are experienced at the time of the choice, anticipated emotions are projections about future emotional states. Anticipated emotions refer to the emotions that individuals anticipate they will experience as a result of their decision. For example, when contemplating a significant career move, one might anticipate feelings of disappointment if the change does not pan out as hoped, or anticipate feelings of satisfaction and pride if it proves successful. These anticipated emotional outcomes can significantly influence the decision-making process. Anticipated emotions as a projection by cognition are consistent with the rational choice model and can be easily integrated into the utility of the potential outcomes. As a result, economists have traditionally focus on anticipated emotions [1, 17, 18].

In the subsequent sections, we will explore how different types of emotions influence decisions in contexts of risk and uncertainty, intertemporal choices, and social interactions.

3. Decisions under risk and uncertainty

Decision under uncertainty is a common part of everyday life, from financial investments to health-related decisions. As a convention, when the probabilities of each possible outcome are known, we call it decision under risk or risky decisions, and we reserve the term decision under uncertainty for situations where the probabilities of outcomes are unknown. Balancing exploration and exploitation is vital for achieving a good outcome for decisions under uncertainty [19]. Since most existing studies on economic decision-making focus on risky decisions, this section will primarily explore decision-making in risk scenarios, transitioning to discussions of uncertainty toward the end.

The realm of risky decisions unveils the intricate relationship between emotion and rationality. Whether it is the choice to buy insurance or to, purchase a lottery ticket, to invest in an asset or to through a medical operation, emotions often serve as a guiding force in shaping our decisions. This first part of the section aims to explore the complexities of risky decision-making, focusing on the fourfold pattern of risk preferences and the concept of “risk as feelings” [2].

3.1 Emotions and the fourfold pattern of risk preferences

Central to decision theory, risky decisions have been traditionally examined through the expected utility (EU) Model in economics. This model posits that individuals, represented by their utility preferences, strive to maximize expected utility, indicating stable risk preferences through the curvature of the utility function.

The EU model, with its assumption of stable risk preferences, however, struggles to elucidate certain common economic behaviors: why do individuals simultaneously buy insurance and lottery tickets? The former suggests risk aversion, while the latter indicates risk-seeking. Contrary to stable preferences, studies have revealed that people’s risk preferences depend on the level of probabilities and whether they are in the gain or loss domain, summarized as the fourfold pattern of risk preferences in Figure 1: Individuals generally exhibit risk-averse tendencies for high-probability gains or low-probability losses, and risk-seeking behaviors for high-probability losses or low-probability gains.

Figure 1.

The fourfold-fold pattern of risk preferences.

In an effort to incorporate psychological realities and explain many of the empirical regularities that are inconsistent with the EU model, Kahneman & Tversky [20] proposed the Prospect Theory (PT). Unlike the EU model, PT considers a value function defined over gains and losses relative to a reference point. The value function reveals that losses impart more impact than equivalent gains, shifting the focus from a mere level of wealth to the psychological impact of gains and losses.

An essential component of the Prospect Theory is the probability weighting function, which depicts the non-linear transformation of objective probability p into subjective weight w(p). This function captures the idea that people tend to distort the probabilities of outcomes when making decisions under uncertainty. Instead of evaluating outcomes based solely on their objective probabilities, individuals tend to overweight low probabilities and underweight high probabilities [20, 21]. Figure 2 demonstrates two probability weighting functions, where the dashed line is more distorted than the solid line.

Figure 2.

Probability weighting function estimated based on the data from by Sun et al. [22], comparing decisions made for oneself and for others. The study involved 181 participants assessing the willingness to pay for 56 lotteries, evenly split ibetween the gain and the loss domains. In the gain domain, participants specified the willingness to pay for a lottery offering a probability of p to obtain the payoff $x and a probability of (1 − p) to obtain the payoff $y. In the loss domain, they indicated the willingness to pay to avoid a lottery with a probability of p to lose $x and a probability of (1 − p) to lose $y. the probability p takes the values of 1, 5, 10, 25, 50, 75, 90, 95, or 99%, whereas (x_i,y_i) takes the values of (50, 0), (100, 0), (200, 0), (400, 0), (100, 50), or (200, 100). For decisions made for one self and decisions made for others in the loss domain. In their study, 181 participants were randomly assigned to two groups: Making decisions for themselves or for another participant. Participants evaluated their willingness to pay across 56 lotteries, split evenly between gain and loss domains. Each lottery i offers a probability of p_i to obtain the payoff x_i and a probability of (1 − p_i) to obtain the payoff y_i. the probability p_i takes the values of 1%, 5%, 10%, 25%, 50%, 75%, 90%, 95%, or 99%, whereas (x_i,y_i) takes the values of (±50, 0), (±100, 0), (±200, 0), (±400, 0), (±100, ±50), or (±200, ±100). Probability weighting functions for each domain were estimated using maximum likelihood estimation based on the functional form proposed by Tversky and Kahneman probability weighting functions for both domains were then estimated using maximum likelihood estimation according to the model by Tversky and Kahneman [21]. In th this plot here shows the estimated probability weighting function in the loss domain, where the horizontal axis p represents the objective probability of the corresponding payoff, and the vertical axis w(p) represents the subjective probability weighting inferred from decisions.

The nonlinearity of the probability weighting function encapsulates two pivotal psychological effects: the certainty effect and the possibility effect. A dramatic shift in probability weighting occurs when probabilities transition from absolute certainty to slight uncertainty or vice versa. The certainty effect takes place when the probability of a desirable outcome changes from infinitesimally less than 1 to a probability of 1. This shift provides individuals with the assurance that a particular outcome will definitely occur, transitioning from a state of slight uncertainty to absolute certainty, signifying a qualitative shift. Conversely, the possibility effect occurs when a probability of a desirable outcome increases from 0 to a small positive value. This increase, no matter how minor, represents a qualitative change, instilling a strong hope in individuals that a certain outcome could materialize. These transitions are considerably more salient and emotionally impactful compared to minor probability changes in the intermediate range, such as from 0.2 to 0.3 or from 0.6 to 0.7, which do not entail a qualitative shift in certainty or uncertainty.

The prospect theory, and the probability weighting function in particular, has a profound connection with emotional influence. Loewenstein et al. [2] propose the “risk as feelings” hypothesis, which posits that people experience emotional reactions to various forms of risk, and make choices that are partially driven by these anticipated emotions [23]. The “risk as feeling” hypothesis elucidates the probability weighting function and the fourfold pattern of risk preferences. Table 1 delineates how the fourfold patterns of risk preferences are caused by the anticipated emotions of the potential prospect.

Risky decision	Reference point	Anticipated emotion	Outcome
Large probability gain	With the gain	Losing the likely gain; Generates great disappointment	Risk averse
Small Probability gain	Without the gain	Winning the unlikely gain generates great elation	Risk seeking
large Probability loss	With the loss	Avoiding the likely loss generates great elation	Risk seeking
Small probability loss	Without the loss	Suffering the unlikely loss generates great disappointment	Risk averse

Table 1.

The fourfold pattern and the corresponding anticipated emotion.

When faced with a high probability gain, as the gain is likely, the reference point aligns with the gain. This is because when individuals expect to receive something (especially when the odds are in their favor), not receiving it feels like a loss, even if nothing has been physically taken away. The anticipated disappointment of missing out on a probable gain drives individuals to opt for the safer choice, showcasing risk-aversion. Conversely, when facing a high probability of loss, the hope of evading an almost certain negative outcome motivates this choice. The anticipated elation renders the individual risk-seeking in this scenario.

A classic example associated with a small probability gain is the purchase of lottery tickets. The extremely low chance of winning a significant amount does not deter individuals; instead, it fuels the hope of acquiring a life-changing sum. The anticipated elation, should they win, renders them risk-seeking. In the scenario of a small probability loss, individuals’ risk aversion is evident in the widespread purchase of various types of insurance, ranging from health to home insurance. The fear of experiencing a catastrophic loss, however unlikely, propels individuals to pay premiums for peace of mind.

3.1.1 Emotional influence on the probability weighting function

The prospect theory assumes that probability weights are independent of the outcomes. The risk-as-feelings hypothesis, in contrast, foretells that outcomes inciting strong emotions would significantly influence judgment and decisions, displaying as overweighting the probabilities of such outcomes occurring. For instance, studies have revealed that individuals were more inclined to pay a premium for insurance against death due to terrorism as opposed to general causes [24], driven by the intense negative emotion tethered to terrorism. Moreover, Rottenstreich & Hsee [25] discovered that probability weighting is more skewed with affect-rich outcomes like the opportunity to meet and kiss a favorite movie star, experiencing a brief but painful electric shock, or receiving a coupon for a European vacation, in comparison to affect-poor financial outcomes. Hence, the probability weighting function tends to be flatter when the outcomes can evoke strong emotions – the solid and dashed lines in Figure 2 could illustrate the differences between affect-rich versus affect-poor outcomes.

In alignment with the risk as feelings hypothesis, any factor that diminishes the intensity of anticipated emotions could lessen the distortion in the probability weighting function. Enhancing the psychological or social distance between an individual and the outcome serves as one such method. For example, decisions made for others are likely to be less swayed by anticipated emotions, thereby reducing the distortion in the probability weighting function. This principle is widely acknowledged in the medical profession, where ethical guidelines advise against physicians treating themselves or close family members to curb emotional bias from impairing rational judgment (Ethics Manual, American College of Physicians; Code of Medical Ethics, American Medical Association).

Various studies corroborate the wisdom embedded in these ethical guidelines. Using the inclusion of others in the self (IOS) scale (Figure 3) [26] to manipulate social distance, Sun et al. [27] demonstrated that as social distance increases (from self to others, or from close friends to mere acquaintances), individuals become less risk averse, increasing their average payoff received in risky situations. Sun et al. [22] further elucidated that this heightened expected payoff is tied to a flatter probability weighting function as social distance increases, mediated by the reduced intensity of anticipated emotions. Figure 2 demonstrates, just as the comparison between the affect-rich vs. affect-poor outcomes, a decision made for oneself has a flatter probability weighting function.

Figure 3.

The inclusion of others in the self (IOS) scale proposed by Aron et al. [26].

Interestingly, the impact of increased social distance on the probability function is more accentuated in the gain domain. The probability weighting function in the gain domain, under the decision-for-other condition, closely aligns with the 45-degree line, indicating risk neutrality. The lesser effect of social distance in the loss domain could stem from the ease of empathizing with others’ losses compared to their gains [28], leading to a more substantial reduction of emotional intensity in the gain domain as social distance expands. Sun et al. [22] supplied evidence supporting this conjecture.²

According to the aforementioned studies, delegating the decision to an agent emerges as a viable strategy to improve risky decision-making. Nonetheless, finding responsible and competent agents may prove challenging. So, how can we improve decisions when we have to make decisions on our own? Sun et al. [30] explored the efficacy of self-distancing strategies in refining risky decision-making. Participants were randomly allocated to diverse conditions. In the self-distancing condition, they were guided to “consider each gamble in a rather distanced way; take a certain distance from what happens; look at what happens in each gamble from the perspective of an external observer.” Conversely, the self-immersing group was instructed to “consider each gamble with an emotional interest in it; enter into what happens; look at what happens in each gamble from the perspective of an involved participant.” Meanwhile, the neutral group was simply instructed to complete the task. Remarkably, a mere two lines of instructions led to participants in the self-distancing group accruing higher expected payoffs compared to their counterparts in the baseline and self-immersing groups.

3.2 Description-experience gap

The studies discussed so far in this chapter on risky decision-making have employed description-based tasks, where individuals receive explicit information regarding the probabilities and outcomes tied to each option. However, real-world decisions often unfold without such clear delineations, necessitating an estimation of probabilities based on past experiences. For instance, investors may lack knowledge about the risks tied to a particular investment, learning about them over time by investing and observing the returns. Hence, some researchers advocate the use of experience-based tasks to enhance external validity, where individuals, devoid of prior knowledge about the consequences, learn about the probabilities and outcomes through actual experience.

The comparison between description-based studies and experience-based studies unveils a notable description-experience gap [31]. Contrary to the predictions of prospect theory and the findings of description-based studies, individuals tend to underweight the probabilities of rare outcomes in experience-based tasks. Moreover, while individuals generally exhibit risk aversion for gains and risk-seeking for losses in description-based studies, the converse is true in experience-based studies.

Decision-making within experience-based tasks can be modeled as a two-stage process. First, individuals formulate beliefs regarding the probabilistic distribution of payoffs for each option, drawing on past experiences, and ascribe a level of confidence to these beliefs. Second, based on these beliefs and confidence level, individuals endeavor to strike a balance between exploration and exploitation. This entails capitalizing on existing knowledge to select the optimum option (exploitation) while also probing different options to amass more accurate knowledge that could potentially yield superior outcomes in the future (exploration) [19, 32]. The merit of exploration over exploitation hinges on the extent of knowledge one possesses regarding different options and the time horizon of the decisions.

Laureiro-Martínez et al.’s [33] study reveals a differentiation in brain activity during exploitation and exploration tasks (cf. [34]). Exploitation resonates with brain regions tied to anticipation and reward, suggesting a more emotionally-driven or reward-driven process, whereas exploration is closely associated with the brain’s executive centers governing attention, indicative of a cognitively demanding process. This neural differentiation posits that individuals may be naturally predisposed toward exploitation due to its rewarding facet, while exploration may necessitate heightened mental effort given the engagement of executive control centers.

A large part of the description-experience gap can be attributed to the emotions invoked during decision-making. Unlike description-based choices, where decisions are swayed by anticipated emotions stemming from potential outcomes, emotions in experience-based choices are often molded by recent actual outcomes. The somatic marker hypothesis posits that emotions experienced upon the realization of an outcome would create and shape somatic markers that influence subsequent decisions through conditioning and memory [10]. Essentially, past emotions distilled as somatic markers steer the choice among different options.

The somatic marker hypothesis sheds light on the description-experience gap from an emotional standpoint. Decisions in experience-based tasks are more prone to recency and memory effects. Given the infrequency of rare events, more common events, which are likely to be recent, are accorded greater weight. Moreover, extremely rare events, unlikely to transpire given the constrained number of trials in lab experiments, seldom leave an emotional imprint on decision-makers, elucidating the tendency to underweight rare events.

Because larger rewards engender more potent emotional and memorable impressions, they exert a greater sway on decisions. This memory effect elucidates the risk-seeking behavior in gains and risk aversion in losses observed in experience-based studies. For instance, when faced with a choice between a sure gain of $50 (Option A) and a 50-50 chance of gaining $30 or $70 (Option B), the thrill of receiving $70 from Option B imprints a stronger somatic marker, inducing individuals toward Option B. Conversely, in a scenario involving a sure loss of $50 (Option A) versus a 50-50 chance of losing $30 or $70 (Option B), the sting of losing $70 from Option B creates a stronger somatic marker, deterring individuals from opting for Option B.

3.3 Incidental emotions and market behavior

Incidental emotions – those unrelated to the task at hand – can also influence decisions under risk and uncertainty. Wright & Bower’s [35] study illustrate this. They manipulated participants into a happy or sad mood by reflecting on corresponding personal experiences, subsequently observing that happy individuals estimated higher probabilities for positive events and lower probabilities for negative events.³

Moreover, various research has unearthed the differential effects of negative emotions on risk preferences. For instance, Raghunathan & Pham [36] discovered that sadness propels individuals toward risk-seeking behaviors, while anxiety drives them toward risk aversion. Likewise, Lerner & Keltner [37] uncovered that anger and fear have opposing impacts on risk preferences, with anger fostering risk-seeking and fear promoting risk aversion. Expanding on these findings, Fessler et al. [38] employed an evolutionary lens to forecast gender-based differences in the effects of incidental emotions on risk preferences, identifying that anger enhances risk-taking in men, while disgust reduces it in women.

In an intriguing study, Hirshleifer & Shumway [39] identified a correlation between market index returns and sunshine levels. Their findings suggest that the positive moods induced by sunny weather lead investors to adopt more optimistic views of the economic outlook. Similarly, Edmans, Garcia, & Norli [40] noted a decline in a country’s stock market returns following significant losses in nationally popular sports, hinting at the extensive reach of incidental emotions into economic and financial realms.

4. Intertemporal decisions

Intertemporal decision-making involves choices where the costs and benefits occur at different points in time. Conventional economic models like the discounted utility model often fall short in capturing the nuances of these decisions. This section explores the emotional factors that sway intertemporal choices, diverging from traditional economic models. Unveiling these emotional dynamics can provide crucial insights for individuals and policymakers, aiding in navigating the intricacies of decisions stretched over time.

4.1 Emotions toward immediate vs. future outcomes

Anything that occurs in the future will involve some degree of risk and uncertainty. Since intertemporal decisions involve weighing present against future outcomes, they inherently possess an element of risk and uncertainty due to the temporal delay. Consequently, the emotional dynamics previously discussed in decisions under risk and uncertainty are relevant in understanding intertemporal choices as well. A case in point is the prevalent present bias, where individuals opt for a smaller present reward rather than wait for a larger future reward. This tendency can be partially elucidated by the certainty effect, a concept explored in our discussion on risky decision-making: a reward available presently is perceived with certainty, while a future reward, regardless of the delay, is shrouded in a layer of uncertainty concerning its eventual realization. The elusive nature of uncertain rewards often falls short of motivating individuals to relinquish immediate rewards that trigger strong emotional reactions. Due to this, the allure of instant gratification frequently supersedes the rational consideration of future gains, propelling individuals toward choices detrimental to their long-term interests, like impulsive shopping or unhealthy dietary choices.

Neuroscientific studies affirm the link between decision-making under uncertainty and intertemporal decision-making. As demonstrated by McClure et al. [41, 42], the limbic and paralimbic cortical structures, rich in dopaminergic intervention and associated with emotional influence, become activated when choices involve immediate rewards. In contrast, the frontoparietal regions of the brain, which are related to higher cognitive functions, are activated during all forms of intertemporal choices. Intriguingly, when individuals opt for larger delayed rewards, there is a notable uptick in activity within the frontoparietal regions compared to the limbic regions. This implies a heightened level of cognitive control and deliberation in overriding the emotional allure of immediate gratification. The more pronounced activity in the frontoparietal regions during such decisions highlights the role of cognitive evaluation and foresight in pursuing delayed rewards, which are often perceived to be more beneficial in the long run. So, based on the concept of the two systems of thinking [6], the slow, deliberate System 2 governs the balance between immediate and future rewards, while the intuitive, emotional System 1 is drawn toward the immediate rewards. When compared with the observations of Laureiro-Martínez et al. [33], the connection between decision under uncertainty and intertemporal decision-making becomes apparent: the exploration of new knowledge, which requires the executive function of the brain, is analogous to making intertemporal trade-offs, while exploitation to maximize short-term gains aligns with opting immediate rewards.

The neural basis of intertemporal decision-making clarifies the important role that emotion plays. Immediate rewards typically elicit stronger emotions compared to future rewards. Long-term benefits, such as being distant, appear intangible and psychologically remote, contrasting with the tangible rewards at hand. This emotional distance often renders the delayed option less appealing and, hence, seldom chosen, giving rise to the self-control problem.

Thaler & Shefrin [43] employ a principal-agent model to elucidate this concept. The model depicts the intrapersonal conflict between the planner (primarily associated with the frontoparietal regions of the brain) and a series of ephemeral doers (largely linked to the limbic and paralimbic cortical structures). A doer at each time point is tasked with making the decision, and these self-centered doers are indifferent to the future doers. On the other hand, the planner values long-term benefits but has restrained control over the doers. The planner’s dominion over the doers significantly wanes when fatigued, swayed by visceral factors, or when the temptation is apparent and accessible. For instance, a cognitive load that exhausts the brain’s executive function leads to a preference for cake over fruit salad [44]. When immediate rewards are out of sight or when they divert their attention to other enjoyable thoughts, children in the Stanford marshmallow test manage to wait considerably longer [45]. Moreover, trainee truckers possessing superior cognitive skills, indicative of a stronger planner, have been found to exhibit more patience (less present bias and discounting) and are more likely to persist on the job, even in a setting with a significant financial penalty for early exit [46].⁴

Given that the emotional pull from immediate rewards tends to shift focus toward short-term outcomes, it is reasonable to hypothesize that a stronger emotional connection to one’s future self would promote long-term thinking. Indeed, studies on the “future self-continuity” hypothesis find that individuals who feel a stronger connection to their future selves are more likely to save money and make healthier choices [47, 48].⁵ Moreover, since languages vary widely in how they encode time, the manner in which speakers articulate their future selves may unconsciously shape their future-oriented concerns. Chen [49] examined the hypothesis that languages that grammatically link the future and the present may nurture future-oriented behaviors. Comparative analyses across different countries, and among demographically similar native households within the same country, reveal that languages with such grammatical structures tend to correlate with higher savings, increased wealth at retirement, reduced smoking, lower rates of obesity, and safer sexual practices.

4.2 The role of anticipation

Besides the integral emotions felt toward present outcomes and the anticipated emotions regarding future outcomes, the emotions expected to be experienced during the wait for future outcomes also significantly impact intertemporal decision-making. Individuals derive pleasure from savoring upcoming positive outcomes and discomfort from dreading negative ones. The emotional journey during the waiting period can substantially sway the ultimate decision, often contradicting the economic rationale posited by the discounted utility model. Common scenarios illustrate this, where individuals might deliberately delay pleasurable events like an exotic vacation or a lavish dinner, while hastening undesirable events such as a dental appointment or a risky surgery.

Loewenstein’s [3] pioneering work unveiled some captivating facets of how anticipated emotions guide intertemporal decisions. Participants in the studies were willing to pay a premium to evade an electric shock deferred for 1 year or 10 years over a shock set to occur within 3 days. Similarly, individuals were ready to pay more for a kiss delayed by 3 days than an immediate kiss or one postponed by 3 hours or 1 day. Berns et al. [50] explored the neural basis for people’s inclination toward hastening dreaded events. They discovered that the anticipation of electric shock augmented neural activity in the posterior components of the cortical pain matrix. Moreover, neural activity responding to anticipated pain forecasted tendencies to expedite shocks.

4.3 Affective forecasting

As previously discussed, suboptimal intertemporal decision-making can arise from present bias and impulsivity – situations where decision-makers fail to implement choices that align with their long-term well-being, given their current and future preferences. Another factor contributing to suboptimal decisions is their inaccurate prediction of future preferences.

While there is evidence showing people are aware of their present bias,⁶ they also exhibit projection bias, the tendency to overestimate how closely our future preferences will mirror our current preferences [52]. For example, Conlin et al. [53] found that individuals’ purchasing decisions were significantly influenced by the prevailing weather conditions; colder weather heightened the propensity to purchase cold-weather items, even if they did not necessarily need them. These impulse purchases were frequently followed by a desire to return the items later.

Projection bias is particularly relevant in intertemporal decisions involving strong emotional states. For instance, being in a positive mood might lead individuals to underestimate the likelihood and the potential impact of adverse events, giving rise to overly optimistic decisions. One underlying cause of projection bias is empathy gaps [54]. The concept of the “hot-cold empathy gap” refers to how people struggle to understand and predict their feelings and behaviors across different emotional states. Specifically, when individuals are in a “hot” state (such as feeling hungry, thirsty, angry, or sexually aroused), they tend to underestimate how different their preferences are from times when they are in a “cold” state, which is a more calm and unemotional condition. This underestimation means they might not fully recognize how much their current intense feelings influence their choices and might believe that these choices reflect their normal preferences, which is often not the case. Conversely, when they are in a cold state, they also fail to accurately predict how much their preferences might change when they are in a hot state.⁷ For example, Sayette et al. [56] discovered that smokers in a cold state underpredicted the value they would attribute to smoking during a hot state, elucidating one reason why tobacco addiction is challenging to overcome.

Furthermore, research has indicated that individuals often overestimate the intensity and duration of emotions triggered by a future event when forecasting their emotional responses, a phenomenon psychologists refer to as impact bias [57]. Brickman et al. [58] revealed that individuals overestimate the emotional impact of both positive events (such as winning a lottery) and negative events (like becoming paraplegic) on their happiness. Gilbert et al. [59] documented a phenomenon termed immune neglect, which describes the overestimation of the impact of a wide range of negative events on individuals’ emotional well-being, including the dissolution of a romantic relationship, failure to achieve tenure, electoral defeat, negative personality feedback, children’s death, and rejection by a prospective employer, on individuals’ emotional well-being.

5. Social decisions

Social decisions form a cornerstone of human interaction and economic transactions, often swayed by a blend of rational deliberations and emotional impulses. For instance, a shared sense of threat might spark collective actions [60]. Emotions like guilt, shame, and anger can act as credible commitments to certain actions, steering us toward favorable outcomes. In this section, we will delve into the emotional facets of social decisions, using the Ultimatum Game as an illustrative example.

The Ultimatum Game is a two-player game where the players move sequentially [61]. The first player, known as the proposer, proposes a way to divide a sum of, say, $10. The second player, the responder, can either accept the proposition, leading to the division of the $10 as proposed, or reject it, whereupon both players receive nothing.

Under the assumption of rationality, the responder would accept any positive offer as it surpasses receiving nothing. Foreseeing this, the proposer would tender the smallest possible amount. However, real-world outcomes of the Ultimatum Game reveal that this Nash equilibrium predicted by game theoretical analysis falls short of predicting human behavior accurately. Typically, median and modal offers hover between 40 and 50%, with the mean offer lying between 30 and 40%. Offers below 20% face rejection around half of the time – a pattern that holds even when factors like high stakes, reputation, and anonymity are introduced [62].

The deviation from presumed rational behavior is rooted in emotional responses. Negative emotions toward unfair offers often overshadow monetary incentives, with anger toward unfair allocations by the proposer prompting responders to resort to costly punishment. Studies reported correlations between the likelihood of rejection and the intensity of self-reported anger [63] and between the rejection of unfair offers and the activation in the anterior insula – a brain region linked to emotions like anger, disgust, and pain [64].

Bosman et al. and Roider et al. demonstrate that cool-off periods do not diminish the rejection of unfair offers [65, 66]. However, when responders can communicate negative emotions to proposers, rejection rates tend to decrease [67]. This suggests that anger compels responders to act against unfairness. Specifically, when responders can express their anger through negative messages, they are less likely to reject the offer outright, as the message itself serves as a means to express attitude toward unfairness.

Incidental emotions also exert a significant influence. For example, incidental sadness lowers acceptance rates [68], while clinical depression correlates with higher acceptance rates [69]. Interestingly, happy responders are less inclined to reject unfair offers, and happy proposers are more likely to make unfair offers [70]. In different contexts, incidental happiness [71], incidental gratitude [72], and receipt of gratitude [73] bolster altruistic tendencies, whereas incidental guilt amplifies willingness to donate blood [74].

6. Emotional intelligence in decision-making

Originating from the Latin word “movere,” denoting “to move,” the term “emotion” often encapsulates the sensation of being propelled by an external force. As highlighted in the introduction, the dynamic between emotion and rationality may be analogized to that of an elephant and its rider [7]. It is futile for the rider to combat the elephant; indeed, it is, in a sense, undesirable to entirely discard emotions because they furnish vital insights aiding our decision-making processes [8, 10].

Despite the substantial impact of emotions on decision-making discussed above, many people ascribe their actions to rational contemplation, neglecting emotional undercurrents [75]. However, mastering emotional intelligence in decision-making lies in comprehending and channeling the energy of emotions [76]. Being aware of the influence of emotions allows us to implement strategies that mitigate their negative effects and harness them constructively [13, 77].

As explored in the section on risky decision-making, when the objective is to dampen emotional intensity, employing distancing – a form of cognitive reappraisal – can be beneficial. This strategy propels a psychological distance between the decision-maker and the outcome. Rather than succumbing to the immediate emotional surge, an individual employing the distancing strategy would appraise the situation from a detached or objective vantage point. This mechanism of distancing has proven efficacious in improving risky decisions [30].

In practice, various methods can be employed to actualize this distancing, each capable of mitigating the intensity of the immediate emotional response [78]. Here are some approaches:

• Spatial Distancing: Envisioning the scenario from a remote viewpoint, akin to observing it from afar or from a bird’s-eye perspective, can foster a sense of detachment [30].

• Temporal Distancing: Contemplating how one feels about the current situation in a distant future can also create a sense of distancing, leading people to realize the impermanence of their emotions [79].⁸

• Perspective Shifting: Adopting a third-person perspective can help in achieving a more distanced stance. For instance, rather than mulling over, “What should I do now?”, one might ponder, “What should [your name] do now?” This subtle modification in viewpoint can assist individuals in appraising the situation more objectively, thus aiding in making more rational decisions amidst emotional turbulence [1].

Entrepreneurship provides a compelling case study for the role of emotional intelligence in economic decision-making. Data reveal a stark statistical reality of startups. In the US, for example, 50% of all startups founded between 1976 and 2001 exited within the first 4 years, and almost three-quarters of venture-capital-backed startups between 1987 and 2008 exited with an equity value of zero [80]. However, entrepreneurs often harbor the belief that they are special, and these figures do not apply to them. This optimistic bias sways them to overestimate their capabilities and underestimate potential hurdles like competition from other enterprises, embodying an illusion of control that overlooks the influence of luck and external factors on success, as pointed out by Astebro et al. [80].

A study by Camuffo et al. [81], employing Randomized Controlled Trials, delved into the merits of a “scientific approach” to entrepreneurial decision-making, providing a practical instance of utilizing a distancing strategy to temper the optimistic bias of entrepreneurs. The study encompassed 116 Italian startups, segregated into a control group and a treatment group, each undergoing business training. While the control group was guided to rely on intuition for evaluating their ideas, the treatment group was directed to frame their ideas as hypotheses, subject to validation through data. This method notably amplified the psychological distance between the entrepreneurs and their ideas. The findings revealed that the control group largely adhered to their initial business strategies and products, amassing an average revenue of under $300. Conversely, the treatment group showed a greater propensity to pivot to new business models, accruing over $12,000 in revenue. This underlines the notion that the emotional intelligence derived from embracing a scientific approach can pave the way for more lucrative business decisions.

Intel’s history offers a notable illustration of this concept [82]. Amid escalating competition in the memory market and an enticing prospect in microprocessors, Intel’s executives found themselves at a pivotal juncture. Trapped in a quandary for a long time, Andy Grove, the president at the time, presented a hypothetical scenario to the chairman and CEO, Gordon Moore: “If we were ousted and the board installed a new CEO, what actions do you think he would take?” The answer was unequivocal: transition the focus to microprocessors. After the transition was made, the stock value of Intel in 2012 was 47 times that in 1985, implying the success of adopting an outsider’s perspective.

7. Conclusion

The extensive exploration of emotional influence on economic decision-making throughout this chapter illuminates a realm of human behavior often inadequately addressed by traditional economic theories. The rational agent model that is still dominating mainstream economics neglects the consequential role of emotions. However, the dissections of various economic decision-making scenarios within this chapter underscore the indelible imprint of emotions on our choices. Far from being mere peripheral elements, emotions emerge as central players, often steering decisions in directions that might seem perplexing through the lens of strict economic rationality. Understanding the interplay between emotional and cognitive factors holds immense promise for individuals, policymakers, and professionals across diverse fields.

Emotions evolved as swift arbitrators of decision-making in ancient environments of small, closely-knit tribes, where faces were familiar and resources scarce [83]. They facilitated survival, fostered social cohesion, and helped navigate the high-stakes, often life-or-death situations that were part of existence. The rapid, emotion-driven decision-making that was crucial in such settings continues to resonate in the complex economic decisions we face in today’s vastly different yet equally challenging environments [4]. The evolved functions of emotions extend beyond the personal sphere into the social realm, impacting not just individual choices but collective actions and societal norms. This integral nature of emotions in our decision-making apparatus highlights their role not as adversaries of rationality but as indispensable allies: emotions do not stand in opposition to rational economic decision-making; rather, they are an inherent component of it [8, 13].

As discussed, recognizing the impact of emotions is crucial for making sound economic decisions. Emotions should not be neglected; instead, they should be recognized, acknowledged, and utilized. We have reviewed how the distancing strategy provides a practical method to mitigate the negative effects of emotions. Moreover, in certain situations, their positive impacts can also be enhanced. For example, strengthening emotional attachment to one’s future self or a desired outcome could foster a longer-term perspective, potentially resulting in improved outcomes [47]. In social interactions, emotions such as anger can be strategically used to achieve an advantage [84]. Research on how to optimally leverage emotions for economic decisions is still in its early stages, but the prospects are promising.

In summary, the myriad hues of emotions tint our decisions, often in subtle manners yet with profound implications. The objective should not be a futile endeavor to extricate emotions from decisions but a deliberate effort to comprehend their influence, harness their potency, and weave this understanding into the texture of economic theories and practices.