Kahneman Tversky Research Articles

Why IR scholars should care about quantum theory, part I: burdens of proof and uncomfortable facts

AbstractHow burdens of proof are allocated in science has an important bearing on how new knowledge develops. Usually, the burden is on new theories to prove their worth relative to a default, baseline of knowledge that is considered established and secure. However, in the case of classical vs. quantum social science matters are not that simple because the long-standing classical default has itself already failed to pass crucial tests, which has spurred the search for quantum solutions instead. Part I of this paper, therefore, tries to ‘re-balance’ the burdens of proof with Quantum Mind and Social Science’ critics, by highlighting two significant limits to date of classical thinking about the mind and society: the philosophical problem of finding a place for consciousness in the universe, and the scientific problem of explaining the Kahneman–Tversky anomalies in psychology. Acknowledging these outstanding problems does not equalize the burdens of proof, but it does mean that as we head into the more substantive discussion in Part II there is no secure default position. Just burdens of proof all around.

Reformulating prospect theory to become a von Neumann–Morgenstern theory

This paper reformulates Kahneman–Tversky’s (KT’s) cumulative prospect theory to become a von Neumann–Morgenstern (vNM) theory that is compatible with many existing economic, finance, psychology and decision theories. This vNM theory has the following desirable characteristics: consistently increasing utility of wealth, loss aversion, concave over favorable outcomes, convex over unfavorable outcomes, consistent preference for positively skewed outcomes and it spans the real line between $$ - \infty $$ and $$ \infty $$ . The weighted probabilities in KT’s cumulative prospect theory do not align with the vNM requirement that the probabilities sum to one; nevertheless, important advantages are gained from this vNM assumption.

Using ELECTRE to analyse the behaviour of economic agents

According to behavioural finance, economic agents display cognitive bias, heuristics and emotional factors that generate preferences which systematically violate the rationality assumptions of the normative model of classical decision theory. Rather than maximizing the expected utility, representing the optimal choice, they attempt to accept a satisfactory solution. Morton and Fasolo (J Oper Res Soc 60:268–275, 2009) outlined some behavioural findings relevant to the practice of multicriteria approach. In this paper, we propose a multicriteria model for analysing some experiments proposed by Kahneman and Tversky (Econometrica 47:263–29 l, 1979). Our aim is to verify whether a multicriteria tool reduces or minimizes cognitive biases. We focus on ELECTRE due to its main features: it accepts the violation of some mathematical axioms. By a simulation study, we represent a set of prospects by means of decision matrices: the prospects are considered as alternatives, the events as criteria, the probabilities of events as the weights assigned to criteria. Then, we apply ELECTRE to verify whether the preference ranking among the alternatives confirms the results obtained by Kahneman–Tversky, that is, whether it is able to describe the emotional behaviours of economic agents.

Applying Behavioral Finance to Investments: The Existence and Importance of 'Investment Tribes'

Investment organizations are complex to understand because decisions are the aggregation of multiple individuals who influence the process. This applies to organizations that apply both quantitative and qualitative investment approaches because the first step in a quantitative approach is still a qualitative statement of the investment hypothesis that is then formalized by the models. Increasingly, finance practice is starting to incorporate behavioral finance insights and recognize that individuals are not “rational utility maximizers”, but rather complex psychological beings that can exhibit non-traditional behaviors. Kahneman-Tversky (KT) introduced this notion of individuals being “humans” and not “econs” but made broad generalizations about behaviorally affected decisions (BADs) and did not provide a methodology to examine individual biases. A technique has been proposed to use KT’s questions to provide individual behavioral diagnostics and previous research demonstrated dramatic differences within and across groups based on age, gender and financial literacy, especially for gambles based on prospective gains and losses. This paper is a case study of a single asset management company that uses a mix of quantitative and qualitative investment techniques, driven by five decision makers with equally weighted votes in the final decision. In addition to demonstrating that each individual in the investment committee is unique and providing individual diagnostics that show that age, gender and education need not lead to a particular behavior, this paper highlights the fact that organizations have “investment tribes”; namely, that there are groups of individuals who appear to exhibit similar risk tendencies for gambles involving gains or losses. These tribes can influence and impact decision-making. Quantifying and making transparent the existence of these tribes could improve decision-making. This case study can be helpful for investment firms allowing them to become aware of potential biases, and also for asset owners that delegate decisions to third parties, as it allows them to understand how the investment firms they delegate to might behave when they experience drawdowns.

An Economic Assessment of Criminal Behaviour

Abstract A utility maximising framework for criminal behaviour is developed and a number of precise functional forms considered for the utility function of a representative criminal. The Kahneman–Tversky form seems to fit current empirical evidence, expressed mainly as the ratio of certain elasticities, better than some other candidates but a more general Markowitz function, centred at current wealth, is another possibility. The criminal’s optimal level of crime is obtained and comparative statics derived to help suggest how crime might be controlled. The solution involves an upper limit on the odds against detection of the criminal. Further empirical work is encouraged to ascertain if crime is a favourable bet and to elicit the utility function of a representative criminal in this analytical framework.

Effects of Cognitive and Affective Tags in Mental Accounting on Consumer Decision Making

Mental accounting is the set of cognitive operations used by individuals and households to organize, evaluate, and keep track of financial activities. Mental accounting proposes that people utilize a set of cognitive labels to evaluate their financial activities, each of which is associated with different preferences to consume(Levav McGraw, 2009; Kahneman Tversky 1984; Thaler 1985, 1990). Mental accounting researchers have shown that windfall gains are spent more readily and frivolously than ordinary income. Consumers prefer to spend their windfall gains on hedonic consumptions but spend their ordinary incomes on utilitarian consumptions. Levav and McGraw(2009) suggested that emotional accounting, including people's feelings about money, also influences consumer choices. When people have negative feelings toward windfall, they opt to make utilitarian expenditures. However, the process of how cognitive(windfall or ordinary income) and affective(positive or negative emotion) tags interact in consumer behavior was not explored. This study proposes that both cognitive tag and affective tags in mental accounting affect consumer decision making. The objective of this study is to explore the interactive effect of cognitive and affective tags in mental accounting on consumer decision through four studies.In studies 1a and 1b, the effect of cognitive and affective tags in mental accounting on consumer decision making behavior was measured. Study 1a showed that the positive tag of windfall income is preferred for hedonic consumption, whereas the negative tag of windfall income is preferred for utilitarian consumption. Both positive and negative tags of ordinary income are preferred for utilitarian consumption. Study1 b utilized a field study to examine actual consumption behavior. The results showed that when people received 15 Yuan RMB as ordinary income, they prefer to spend it on utilitarian consumption regardless of the positive or negative emotion they feel. However, they receive 15 Yuan RMB as windfall income, they prefer to use it for hedonic consumption in the positive emotion and for utilitarian consumption in the negative emotion. Studies 2a and 2b attempted to explore the reason of negative emotion can make windfall income turn from hedonic to utilitarian consumption. Study2 a found that when people expect to feel guilty about spending windfall income on hedonic consumption, they would avoid hedonic consumption. Study2 b found that when people felt guilty about windfall income, they tend to avoid hedonic consumption. Compared with the low guilt level group, the high guilt level group prefers to use windfall income for utilitarian consumption. These results suggest that cognitive and affective tags influence consumer behavior. The influence of cognitive tag on consumer decision presents the "cognition match effect", whereas the influence of affective tag on consumer decision presents the "affect match effect". Both tags also have an interaction effect on consumer decision. Guilt may be a mechanism that results in the negative tag of windfall being preferred for utilitarian consumption.

Cumulative prospect theory challenges traditional expected utility theory

The Cumulative Prospect Theory (CPT) uses piecewise value functions instead of consumer utility and provides alternative assumptions for investment behaviour approximated by power value function. In this study, our aim to find a generalized value function that will make the value function introduced by Kahneman–Tversky (1992) a special case. This functional form of the value function determine the appropriate parameter of the values function. We believe that if one can approximate the original CPT value function by other types of functions, the optimization problem and the many other implications can be compared to choose the best model depending on the focus of the problems. This, eventually, could result in improving the theory in both theoretical and empirical points of views.

Psychophysics of the probability weighting function

A probability weighting function w(p) for an objective probability p in decision under risk plays a pivotal role in Kahneman–Tversky prospect theory. Although recent studies in econophysics and neuroeconomics widely utilized probability weighting functions, psychophysical foundations of the probability weighting functions have been unknown. Notably, a behavioral economist Prelec (1998) [4] axiomatically derived the probability weighting function w(p)=exp(−(−lnp)α) (0<α<1 and w(0)=1,w(1e)=1e,w(1)=1), which has extensively been studied in behavioral neuroeconomics. The present study utilizes psychophysical theory to derive Prelec’s probability weighting function from psychophysical laws of perceived waiting time in probabilistic choices. Also, the relations between the parameters in the probability weighting function and the probability discounting function in behavioral psychology are derived. Future directions in the application of the psychophysical theory of the probability weighting function in econophysics and neuroeconomics are discussed.

The Effects of Emotions and Task Frames on Risk Preferences in Self Decision Making and Anticipating Others' Decisions

Although many researchers explore the effects of decision process emotions and task frames on risk preferences in self decision making (e.g., Clore Schwarz, 1983; Slovic, 2002; Mayer, Gaschke, Braverman Evans, 1992; Loewenstein, Weber Hsee, 2001; Isen Patrick, 1983; Kahneman Tversky, 1979), few researchers examine their impacts on risk preferences in anticipating others’ decisions (e.g., Hsee Weber, 1997; Wallach Wing, 1968)). In this study, two experiments are presented to compare the effects of emotions and task frames in self decision making and anticipating others’ decisions. Experiment 1 used two film clips as materials to induce 80 undergraduate subjects’ happiness or sadness emotions, then asked subjects to either make choices for themselves or anticipate others’ choices on a risk preference questionnaire including ten items. In experiment 2, task frame variables were introduced to examine the complex relations among emotions, the decision maker’ roles and task frames. The 96 undergraduate subjects were asked to either make choices for themselves or anticipate others’ choices on a risk preference questionnaire including seven items under happiness or sadness emotion, and gain or loss frame conditions. The results of the two experiments showed that (1) In gain frames, the sadness emotion produces stronger risk preferences than the happiness emotion, and making choices for themselves shows stronger risk preferences than anticipating others’ choices. (2) In loss frames, the happiness emotion produces stronger risk preferences than the sadness emotion, and anticipating others’ choices produces stronger risk preferences than making choices for themselves; (3) In making decisions for themselves, the happiness emotion produces stronger risk preferences under the loss frame than under the gain frame, but the sadness emotion produces stronger risk preferences under the gain frame than under the loss frame. In contrast, in anticipating others’ decisions, the loss frame always produces stronger risk preferences than the gain frame, regardless of happiness emotion or sadness emotion. These results do not concur with the general findings about framing effects (Kahneman Tversky, 1979) and self-other decision bias (Hsee Weber, 1997; Wallach Wing, 1968), and suggest that there are complicated interaction among emotions, task frames and the decision maker’ roles. Rather, the effects of emotions and task frames on risk preferences depend on the decision maker’ roles.

Behavioral models of decision making under risk and/or uncertainty with application to public sectors

In this paper, some behavioral (or descriptive) models of individual decision making under risk and/or uncertainty are discussed. Firstly, a model to explain the violations of expected utility hypothesis is described. In this model outcome-dependent, non-additive probabilities are introduced in a measurable value function under risk where probability of each event occurring is known. The effective application of this approach to the public sector is shown in modeling risks of extreme events with low probability and high outcome. Next, a measurable value function under uncertainty is also described where basic probability of a set of event is known but occurrence probability of each event is not known. Potential applicability to evaluating a global warming problem is mentioned. As a special case of the measurable value function under uncertainty an extended Kahneman–Tversky model of prospect theory under uncertainty (PTU) is described. An application of PTU in evaluating the sense of security provided by nursing care robots is described.

Behavioral models for complex decision analysis

The focus of this paper is to propose some behavioral (or descriptive) models of individual decision making and group decision making under risk/uncertainty as follows: models to explain the violations of expected utility models for the individual decision making; and a model to describe the ethical consensus formation process among multi-agent conflicting decision makers. The former models extend Kahneman–Tversky model of prospect theory and resolve Allais and Ellsburg paradoxes. The later model extends additive/utility independence in consensus formation process to get more flexible preference structure among conflicting decision makers.