What does Risk Feel Like? Insights from Behavioural Economics Part II (original) (raw)

People's perception of others' risk preferences

2019

Our everyday decisions are driven by costs, risk, and reward. How do people take these factors into account when they predict and explain the decisions of others? In a two-part experiment, we assessed people’s perceptions of other people’s risk preferences, relative to their own. In Part 1, participants reported their relative preference between a guaranteed payout and lotteries with various probabilities and payouts, and made predictions about other people’s preferences. In Part 2, participants estimated the lottery payout that generated a given relative preference between a guaranteed payout and a lottery, both for themselves and others. We found considerable individual variability in how people perceive the risk preferences of others relative to their own, and consistency in people’s perceptions across our two measures. Future directions include formal computational models and developmental studies of how we think about our own and each other’s decision-making.

Dealing with risk: Gender, stakes, and probability effects

2015

This paper investigates how subjects deal with financial risk, both "upside" (with a small chance of a high payoff) and "downside" (with a small chance of a low payoff). We find that the same people who avoid risk in the downside setting tend to make more risky choices in the upside one. The experiment is designed to disentangle the probability-weighting and utility-curvature components of risk attitudes, and to differentiate settings in which gender differences arise from those in which they do not. Women are more risk averse for downside risks, but gender differences are diminished for upside risks.

The Psychology of Risk: A Brief Primer

SSRN Electronic Journal, 1999

Risk is commonly defined in negative terms-the probability of suffering loss, or factors and actions involving uncertain dangers or hazards. In contrast, the definition used in the social sciences relies on simply the degree of uncertainty-how much variance exists among the possible outcomes associated with a particular choice or action. Counter to intuition, an investment that will lose 5forcertainwouldthereforebeclassifiedaslessriskythanonethathasanequalchanceofyieldingeitheragainof5 for certain would therefore be classified as less risky than one that has an equal chance of yielding either a gain of 5forcertainwouldthereforebeclassifiedaslessriskythanonethathasanequalchanceofyieldingeitheragainof10 or a gain of $15. Uncertainty and value are treated as separable entities because expanding the notion of risk to include gains as well as losses adds considerable conceptual power. For example, depending on how a pair of options is described, a choice can appear as if between two losses or between two gains. Consider the following: Problem I: Imagine that you are faced with a life or death choice. The U.S. has safely quarantined all 600 people infected with an unusual virus, but is now certain that they will all die without some treatment. Resources are severely limited and the choice mast be made between two scienttjk programs. Program A: If adopted, 2cO people will be saved for certain. Program B: If adopted, there is a IN probability that 600 people will be saved and a 2/3 probability that no people will be saved. People choose A over B by a ratio of three to one, showing a preference for the certain outcome. Now consider the same scenario with a different set of choices. Program C: if adopted, 400 people will die for certain. Program D: If adopted, there is a l/3 probability that no people will die and a 213 probability that 600 people will die. People choose D over C by a ratio of four to one, showing a preference for risk. However, note that the end results of A and C are exactly the same-200 people alive, 400 dead-as are those of B and D. According to classical theories of rationality, one cannot both prefer A to B and D to C. This paper will discuss why most people do. Economic theories based on "perfect" rationality are undoubtedly powerful. If one wanted to describe or predict human behavior in the simplest possible manner, one would certainly want to begin by assuming (1) that people are motivated by their own self interests, and (2) that they can be extremely calculating when valuable opportunities arise, learning quickly from the success of others. Research on the psychology of risk does not begin by assuming that all human behavior is irrational, random, or thoughtless. Rather this research has centered on how people may be biased by

Personality and domain-specific risk taking

Journal of Risk Research, 2005

The concept of risk propensity has been the subject of both theoretical and empirical investigation, but with little consensus about its definition and measurement. To address this need, a new scale assessing overall risk propensity in terms of reported frequency of risk behaviours in six domains was developed and applied: recreation, health, career, finance, safety and social. The paper describes the properties of the scale and its correlates: demographic variables, biographical self-reports, and the NEO PI-R, a Five Factor personality inventory (N52041). There are three main results. First, risk propensity has clear links with age and sex, and with objective measures of career-related risk taking (changing jobs and setting up a business). Second, the data show risk propensity to be strongly rooted in personality. A clear Big Five pattern emerges for overall risk propensity, combining high extraversion and openness with low neuroticism, agreeableness, and conscientiousness. At the subscale level, sensation-seeking surfaces as a key important component of risk propensity. Third, risk propensity differs markedly in its distribution across job types and business sectors. These findings are interpreted as indicating that risk takers are of three nonexclusive types: stimulation seekers, goal achievers, and risk adapters. Only the first group is truly risk seeking, the others are more correctly viewed as risk bearers. The implications for risk research and management are discussed.

How people know their risk preference

People differ in their willingness to take risks. Recent work found that a dominant class of measures, revealed preference tasks (e.g., laboratory lotteries), appear not to tap into stable individual differences, whereas survey-based stated preferences are stable and predict real-world risk taking across different domains. How can stated preferences, often criticised as inconsequential (“cheap talk”), be more valid and predictive than controlled, incentivized lotteries? In our multi-method study, over 3,000 respondents from population samples answered a single widely used and predictive risk preference question. Respondents then explained the reasoning behind their answer. They tended to recount diagnostic behaviours and experiences, focusing on voluntary, consequential acts and experiences from which they seemed to infer their risk preference. We found that third-party readers of respondents’ brief memories and explanations reached similar inferences about respondents' preferen...

Risk Preference Predictions and Gender Stereotypes

Organizational Behavior and Human Decision Processes, 2002

This article reports a study examining biases in predicting the risk preferences of other people. Results showed that both women and men overestimated males' risk preferences, but accurately predicted women's risk preferences. The same effect was observed for options with positive outcomes and for options with negative outcomes. Results of our research suggest that participants' predictions were influenced by knowledge about risk preferences incorporated in gender stereotypes and by their own feelings. People are especially prone to make biased predictions when they compare themselves with other men. Previous findings that people are less risk averse for losses than for gains were successfully replicated. Practical and theoretical implications of the findings are discussed. ᭧ 2001 Elsevier Science

Measuring Risk Attitudes Controlling for Personality Traits * January 2008

2008

This study measures risk attitudes using two paid experiments: the Holt and Laury (2002) procedure and a variation of the game show Deal or No Deal. The participants also completed a series of personality questionnaires developed in the psychology literature including the risk domains of Weber, Blais, and Betz (2002). As in previous studies risk attitudes vary within subjects across elicitation methods. However, this variation can be explained by individual personality traits. Specifically, subjects behave as though the Holt and Laury task is an investment decision while the Deal or No Deal task is a gambling decision. JEL Codes: C9, D8