Contributed by: Milan Lovric, Erasmus University Rotterdam

Dual-process Systems
Dual-process theories of information processing and reasoning have a long tradition in psychology literature. In a neuroeconomics paper (Camerer et al, 2005), the authors proposed a two-dimensional framework of neural functioning which combines two of such dual-process theories: controlled vs. automatic processes, and cognition (deliberation) vs. affect (emotion). A distinction between controlled and automatic processes has been noted in contemporary psychology literature under various names of dual-processing theories (see Camerer et al, 2005)). Controlled processes are serial (step-by-step), evoked deliberately, they cause the subjective feeling of effort, and are accessible by introspection. Automatic processes, on the other hand, operate in parallel, they are relatively effortless, and are inaccessible to consciousness. A distinction between affect and cognition is also pervasive in contemporary psychology and neuroscience literature. Affective processing is associated with feeling states when affect states reach a certain threshold level. However, most of the affective processing operates unconsciously. The central role of affective processing is in human motivation - affects address "go- no go" questions, while cognitive processes address "true or false" questions (Zajonc, 1998).

In dual-process theories the choice is determined as the result of the interplay between the cognitive and affective system. This interaction can be collaborative (when both systems work in the same direction), or competing (in which one system wins and overrides the other system). A number of variables can influence the relative strength of these systems, e.g. cognitive load can undermine controlled cognitive processes. Research on "emotional regulation" studies how cognitive system influences affective system, and implies the capacity for controlling emotion (Camerer et al, 2005). While the conscious control over emotions is weak, emotions can easily flood consciousness. LeDoux explains the reasons for this asymmetry: This is so because the wiring of the brain at this point in our evolutionary history is such that connections from the emotional systems to the cognitive systems are stronger than connections from the cognitive systems to the emotional systems. Exactly how cognitive and affective systems interact in the control of behavior is not completely understood.

Risk Attitude
In decision theory and economics an attitude towards risk can be characterized as risk-aversion, risk-seeking (risk- tolerance, risk-taking, risk-loving), or risk-neutrality; and can be defined in a classical sense as a preference between a risky prospect and its expected value (the method of revealed preference). In these theoretical considerations risk attitude is usually captured through the curvature of utility function, or alternatively, through nonlinear weighting of probabilities. But a strong empirical phenomena that is driving risk aversion to a large extent is known as loss aversion (Kahneman and Tversky (1979), Markowitz (1952)). "Losses loom larger than gains," and while people are typically risk-averse for gains, they are risk-seeking in the domain of losses (Kahneman and Tversky, 1979). This highlights reference dependence, i.e. the importance of reference point against which outcomes are coded as losses or gains. Loomes (1999) suggests that the current evidence in literature is more in favor of the notion that individuals have only basic and fuzzy preferences, and that each decision problem triggers its own preference elicitation. This is in line with the claim that preferences are constructed (not elicited or revealed) as a response to a judgment or choice task (Bettman et al., 1998).

Slovic (1998) argues that although knowledge of the dynamics of risk taking is still limited, there is an evidence of little correlation in risk-taking preferences across different domains and situations. Only those tasks highly similar in structure and payoffs have shown any generality. Also, previous learning experiences in specific risk-taking settings seem more important than general personality characteristics. Furthermore, risk attitude can change depending on the outcomes of previous decisions. Thaler and Johnson (1990) found that previous gains increase risk-seeking behavior (house money effect), while in the presence of previous losses, those bets which offer a chance to break even seem particularly attractive (break-even effect). These are examples of what Thaler refers to as mental accounting.

In financial experiments Ganzach (2000) found that judgments of risk and return for familiar financial assets were consistent with their ecological values (a positive relationship between risk and return), however, for unfamiliar assets he found that both judgments were based on a global attitude, which resulted in a negative relationship between risk and return (assets were perceived to have high risk and low return, or low risk and high return).

Emotions can affect perceptions of risks - anger makes people less threatened by risks, and sadness makes them more threatened (Lerner and Keltner, 2001). Risk averse behavior is driven by fear and anxiety responses to risk and the stored pain of experienced losses (Camerer et al., 2005). Risk taking behavior is driven by the pleasure of gambling (Camerer et al., 2005). The feelings need not be mediated by the cognition. One evidence for the importance of emotions in decision making comes from patients with brain lesions in regions related to emotional processing. Shiv et al. (2005) made an experiment with 20 rounds of investment decisions (choosing whether to invest 1 dollar in a risky prospect with a 50-50 chance of winning 2.5 dollars or nothing), and found that target patients (with brain lesions in emotion-related areas of brain) made more investments than the normal participants and control patients, and thus earned more on average. Normal and control patients seem to have been more affected by the outcomes of previous decision - upon winning or losing they adopted a conservative strategy and less invested in subsequent rounds. However, the inability to learn from emotional signals (Somatic Marker Hypothesis, Damasio et al. (1996)) can also lead to unadvantageous decisions such as excessive gambling. Thus, emotion and cognition both play a crucial role in decision making.

Risk attitude is influenced by the competition and collaboration between the cognitive and affective system (Loewenstein et al., 2001). The "risk-as-feelings" perspective on decisions under risk and uncertainty (Loewenstein et al., 2001) differs from the classical cognitive-consequentialist perspective in the sense that feelings or affects play a crucial role in decision making: emotional evaluations of risky choices may differ from cognitive, and when such a divergence occurs, they often drive behavior. Both emotional and cognitive evaluations are influenced by expected outcomes (and expected emotions) and subjective probabilities, however, emotional evaluations are also influenced by a variety of factors, such as vividness of associated imagery, proximity in time, etc. In the light of the Prospect Theory, Loewenstein and O'Donoghue (2004) propose that the affective system contributes to the risk attitude through loss aversion and non-linear (usually S- shaped) probability weighting; however the deliberative system responds to risk in a way predicted by Expected Utility Theory (or perhaps Expected Value). To support this interpretation, the authors point to research which suggests that emotional responses depend on mental images of outcomes, whereas they tend to be insensitive to probabilities.

Emotions in Economics
The interplay of cognition and emotion has a lot potential to explain the behavior of individuals in various economic domains. This idea was brought up only recently with the advent of behavioral economics and neuroeconomics. In traditional economic theory the term "Homo Economicus" has been used for a formal representation of an individual, who acts as a utility maximizer, given his preferences and other constraints. An economic man adheres to the axioms of rational choice theory. Even though this hypothetical construct has been useful in formulating economic theories and models, over the past decades psychologists and behavioral scientists have documented robust and systematic violations of principles of Expected utility theory, Bayesian learning, and Rational expectations - questioning their validity as a descriptive theory of decision making (DeBondt, 1998). Furthermore, Simon (1991), to whom the term "bounded rationality" is usually attributed, has emphasized "the limits upon the ability of human beings to adapt optimally, or even satisfactorily, to complex environments."

Emotions have powerful effects on decisions, and decision outcomes have powerful effects on emotions (Mellers et al., 1998). Emotions can have both a predecision and postdecision effect. Most of the research focused on a unidimensional model in which a predecision emotion can be either positive or negative. However, a more detailed approach is needed given the variety and domain-specificity of emotions (Mellers et al., 1998). Positive emotions are shown to increase creativity and information integration, promote variety seeking, but also cause overestimation of the likelihood of favorable events, and underestimation of the likelihood of negative events. Negative emotions promote narrowing of attention and failure to search for alternatives. They promote attribute- vs. alternative-based comparisons (Mellers et al., 1998).

One of the most studied emotions that can follow a decision is the feeling of regret. Gilovich and Medvec (1995) showed that in the short run people experience more regret for actions rather than inaction, while in the long run they experience more regret for their inactions. Anticipated emotions, such as regret and disappointment, have drawn most attention of economist, whereas immediate emotions (experienced at the moment of decision making) have been mainly studied by psychologists (Loewenstein, 2000). Loewenstein emphasizes that economists should also pay attention to immediate emotions and a range of visceral factors which influence our decisions.

The material presented in this briefing is based on the following working paper:

M. Lovric, U. Kaymak, J. Spronk, A Conceptual Model of Investor Behavior, ''ERIM Report Series'', May 2008

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