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A Domain-Specific Risk-Attitude Scale: Measuring Risk Perceptions and Risk Behaviors
TL;DR: This article presented a psychometric scale that assesses risk taking in various content domains: financial decisions, health/safety, recreational, ethical, and social decisions, and found that respondents' degree of risk taking was highly domain-specific, i.e. not consistently risk-averse or consistently riskseeking across all content domains.
Abstract: We present a psychometric scale that assesses risk taking in five content domains: financial decisions (separately for investing versus gambling), health/safety, recreational, ethical, and social decisions. Respondents rate the likelihood that they would engage in domain-specific risky activities (Part I). An optional Part II assesses respondents’ perceptions of the magnitude of the risks and expected benefits of the activities judged in Part I. The scale’s construct validity and consistency is evaluated for a sample of American undergraduate students. As expected, respondents’ degree of risk taking was highly domain-specific, i.e. not consistently risk-averse or consistently risk-seeking across all content domains. Women appeared to be more risk-averse in all domains except social risk. A regression of risk taking (likelihood of engaging in the risky activity) on expected benefits and perceived risks suggests that gender and content domain differences in apparent risk taking are associated with differences in the perception of the activities’ benefits and risk, rather than with differences in attitude towards perceived risk.
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TL;DR: It is shown that emotional reactions to risky situations often diverge from cognitive assessments of those risks, and when such divergence occurs, emotional reactions often drive behavior.
Abstract: Virtually all current theories of choice under risk or uncertainty are cognitive and consequentialist. They assume that people assess the desirability and likelihood of possible outcomes of choice alternatives and integrate this information through some type of expectation-based calculus to arrive at decision. The authors propose an alternative theoretical perspective, the risk-as-feelings hypothesis, that highlights the role of affect experienced at the moment of decision making. Drawing on research from clinical, physiological, and other subfield of psychology, they show that emotional reactions to risky situations often drive behavior. The risk-as-feelings hypothesis is shown to explain a wide range of phenomena that have resisted interpretation in cognitive-consequentialist terms.
4,901 citations
Cites background from "A Domain-Specific Risk-Attitude Sca..."
...In a study designed to investigate cross-cultural differences in risky decision making, Weber and Hsee (1998) asked participants to provide maximum buying prices for risky investment options that differed in the probabilities with which gains or losses of different magnitude would be realized....
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Posted Content•
TL;DR: The authors found that gender, age, height, and parental background have an economically significant impact on willingness to take risks, and the question about risk taking in general generates the best all-around predictor of risky behavior.
Abstract: This paper studies risk attitudes using a large representative survey and a complementary experiment conducted with a representative subject pool in subjects’ homes. Using a question asking people about their willingness to take risks “in general”, we find that gender, age, height, and parental background have an economically significant impacton willingness to take risks. The experiment confirms the behavioral validity of this measure, using paid lottery choices. Turning to other question about risk attitudes in specific contexts, we find similar results on the determinants of risk attitudes, and also shed light on the deeper question of stability of risk attitudes across contexts. We conduct a horse race of the ability of different measures to explain risky behaviors such as holdings stocks, occupational choice, and smoking. The question about risk taking in general generates the best all-around predictor of risky behavior
1,537 citations
TL;DR: This article explored the interface between personality psychology and economics and examined the predictive power of personality and the stability of personality traits over the life cycle, and developed simple analytical frameworks for interpreting the evidence in personality psychology.
Abstract: This paper explores the interface between personality psychology and economics. We examine the predictive power of personality and the stability of personality traits over the life cycle. We develop simple analytical frameworks for interpreting the evidence in personality psychology and suggest promising avenues for future research.
1,206 citations
TL;DR: This paper reviewed the results from experimental measures of risk aversion for evidence of systematic differences in the behavior of men and women, and found that women are more averse to risk than men.
Abstract: Publisher Summary This chapter reviews the results from experimental measures of risk aversion for evidence of systematic differences in the behavior of men and women. In most studies, women are found to be more averse to risk than men. Studies with contextual frames show less consistent results. Whether men and women systematically differ in their responses to risk is an important economic question. If women are more sensitive to risk than men, this will be reflected in all aspects of their decision making, including choice of profession (and so earnings), investment decisions, and what products to buy. Several recent studies investigate this difference directly. Most experiments that investigate preferences over risky choices deal with the question of whether people make choices that are consistent with expected utility maximization.
1,127 citations
TL;DR: The cognitive basis of cooperative decision-making in humans using a dual-process framework is explored and it is proposed that cooperation is intuitive because cooperative heuristics are developed in daily life where cooperation is typically advantageous.
Abstract: Economic games are used to investigate the cognitive mechanisms underlying cooperative behaviour, and show that intuition supports cooperation in social dilemmas, whereas reflection can undermine these cooperative impulses. Many people are willing to make sacrifices for the common good, but little is known about the cognitive mechanisms that underlie such cooperative behaviour. In economic experiments subjects often contribute cooperatively against what rational self-interest should dictate. This study uses a series of ten varied experimental designs, including both one-shot and repeated games, to establish whether we are intuitively predisposed to cooperate or to act selfishly. And it seems our gut response is to cooperate — but given more time to think the logic of self-interest undermines collective action and we become less generous. Cooperation is central to human social behaviour1,2,3,4,5,6,7,8,9. However, choosing to cooperate requires individuals to incur a personal cost to benefit others. Here we explore the cognitive basis of cooperative decision-making in humans using a dual-process framework10,11,12,13,14,15,16,17,18. We ask whether people are predisposed towards selfishness, behaving cooperatively only through active self-control; or whether they are intuitively cooperative, with reflection and prospective reasoning favouring ‘rational’ self-interest. To investigate this issue, we perform ten studies using economic games. We find that across a range of experimental designs, subjects who reach their decisions more quickly are more cooperative. Furthermore, forcing subjects to decide quickly increases contributions, whereas instructing them to reflect and forcing them to decide slowly decreases contributions. Finally, an induction that primes subjects to trust their intuitions increases contributions compared with an induction that promotes greater reflection. To explain these results, we propose that cooperation is intuitive because cooperative heuristics are developed in daily life where cooperation is typically advantageous. We then validate predictions generated by this proposed mechanism. Our results provide convergent evidence that intuition supports cooperation in social dilemmas, and that reflection can undermine these cooperative impulses.
1,105 citations
References
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TL;DR: Ajzen, 1985, 1987, this article reviewed the theory of planned behavior and some unresolved issues and concluded that the theory is well supported by empirical evidence and that intention to perform behaviors of different kinds can be predicted with high accuracy from attitudes toward the behavior, subjective norms, and perceived behavioral control; and these intentions, together with perceptions of behavioral control, account for considerable variance in actual behavior.
65,095 citations
"A Domain-Specific Risk-Attitude Sca..." refers background in this paper
...The best-known model of the relationship is the theory of reasoned action (Ajzen and Fishbein, 1977) and its elaboration in the theory of planned behavior (Ajzen, 1991)....
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...Respondents rate the likelihood that they would engage in domain-specific risky activities (Part I)....
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27,773 citations
"A Domain-Specific Risk-Attitude Sca..." refers background in this paper
...In the expected utility (EU) framework and its variants including prospect theory (Kahneman and Tversky, 1979), risk attitude is nothing more than a descriptive label for the shape of the utility function presumed to underlie a person’s choices....
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TL;DR: In this paper, two types of error involved in fitting a model are considered, error of approximation and error of fit, where the first involves the fit of the model, and the second involves the model's shape.
Abstract: This article is concerned with measures of fit of a model. Two types of error involved in fitting a model are considered. The first is error of approximation which involves the fit of the model, wi...
25,611 citations
"A Domain-Specific Risk-Attitude Sca..." refers background in this paper
...However, tests of fit and standard errors for OLS are not easily obtained and not well known (Browne and Cudeck, 1993)....
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TL;DR: In this article, a review of available empirical research supports the contention that strong attitude-behavior relations can be obtained only under high correspondence between at least the target and action elements of the attitudinal and behavioral entities.
Abstract: Research on the relation between attitude and behavior is examined in light of the correspondence between attitudinal and behavioral entities. Such entities are defined by their target, action, context, and time elements. A review of available empirical research supports the contention that strong attitude-behavior relations dre obtained only under high correspondence between at least the target and action elements of the attitudinal and behavioral entities. This conclusion is compared with the rather pessimistic assessment of the utility of the attitude concept found in much contemporary social psychological literature.
6,756 citations
"A Domain-Specific Risk-Attitude Sca..." refers background in this paper
...The best-known model of the relationship is the theory of reasoned action (Ajzen and Fishbein, 1977) and its elaboration in the theory of planned behavior (Ajzen, 1991)....
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Book•
01 Jan 1982
TL;DR: Within-subject and mixed designs of Factorial Design have been studied in this article, where the Principal Two-Factor Within-Factor Effects and Simple Effects have been used to estimate the effect size and power of interaction components.
Abstract: I. INTRODUCTION. 1. Experimental Design. II. SINGLE FACTOR EXPERIMENTS. 2. Sources of Variability and Sums of Squares. 3. Variance Estimates and F Ratio. 4. Analytical Comparisons Among Means. 5. Analysis of Trend. 6. Simultaneous Comparisons. 7. The Linear Model and Its Assumptions. 8. Effect Size and Power. 9. Using Statistical Software. III. FACTORIAL EXPERIMENTS WITH TWO FACTORS. 10. Introduction to the Factorial Design. 11. The Principal Two-Factor Effects. 12. Main Effects and Simple Effects. 13. The Analysis of Interaction Components. IV. NONORTHOGONALITY AND THE GENERAL LINEAR MODEL. 14. General Linear Model. 15. The Analysis of Covariance. V. WITHIN-SUBJECT DESIGNS. 16. The Single-Factor Within-Subject Design. 17. Further Within-Subject Topics. 18. The Two-Factor Within-Subject Design. 19. The Mixed Design: Overall Analysis. 20. The Mixed Design: Analytical Analyses. VI. HIGHER FACTORIAL DESIGNS AND OTHER EXTENSIONS. 21. The Overall Three-Factor Design. 22. The Three-Way Analytical Analysis. 23. Within-Subject and Mixed Designs. 24. Random Factors and Generalization. 25. Nested Factors. 26. Higher-Order Designs. Appendix A: Statistical Tables.
6,216 citations