scholarly journals What are the chances? How descriptions of probability affect risky decisions

2021 ◽  
Author(s):  
◽  
Jared Pickett
Keyword(s):  
Risk Preference ◽  
Expected Value ◽  
Past Experience ◽  
Response Patterns ◽  
Reinforcer Magnitude ◽  
Potential Outcome ◽  
Decisions From Experience ◽  
Risk Seeking ◽  
Risky Option ◽  
Increase In Risk

<p>People make different decisions when they know the odds of an event occurring, (e.g. told 10% chance of an earthquake that year) than when they draw on only their own experience (e.g. living in a city with, on average, one earthquake every 10 years). It may be that when we make decisions based on our past experience (decisions from experience) we are more likely to choose a risky option when it can lead to the biggest win and avoid it when it can lead to the biggest loss, this effect is called the Extreme-Outcome rule. Across three Experiments we tested the Extreme-Outcome rule by having participants make repeated choices between either safe or risky options which had the same expected value. In each experiment, we varied the magnitude of the reinforcer’s participants could win in both an Experience condition and a condition that had both description and experience information. In Experiment 1 where we had two reinforcer sizes (small and large) we found an Extreme-Outcome effect in the Experience condition, but not the Description-Experience condition. In Experiment 2 we tested a prediction of the Extreme-Outcome rule that participants would be sensitive to the best and worst outcome by adding another reinforcer size (reinforcers were small, medium and large) and therefore on some trials neither alternative included an extreme outcome. We also removed zero as a potential outcome to investigate whether zero aversion might be driving the effect of reinforcer magnitude in the Experience condition. We did not find response patterns consistent with an Extreme-Outcome rule in the Experience condition. Instead, participants were least risk seeking when the reinforcer was small, but there was no difference in levels of risk seeking between the medium and large reinforcer trials. In other words, there was an effect of the low-extreme outcome but not the high-extreme outcome. Like Experiment 1, in the Description-Experience condition risk preference was not influenced by reinforcer size, but the absolute levels were higher. To investigate whether this increase in risk preference was due to removing the zero, in Experiment 3 we manipulated whether zero was present or absent. When zero was absent, risk preference was not influenced by the size of the reinforcer in the Description-Experience condition, but there was an effect of the low-extreme outcome when zero was present. We also found an effect of the low extreme outcome in the Experience condition regardless of whether zero was present or absent. Overall, these findings suggest the Extreme-Outcome rule needs to be modified to take into account the effect of the low extreme but not the high extreme outcome.</p>

scholarly journals What are the chances? How descriptions of probability affect risky decisions

2021 ◽  
Author(s):  
◽  
Jared Pickett
Keyword(s):  
Risk Preference ◽  
Expected Value ◽  
Past Experience ◽  
Response Patterns ◽  
Reinforcer Magnitude ◽  
Potential Outcome ◽  
Decisions From Experience ◽  
Risk Seeking ◽  
Risky Option ◽  
Increase In Risk

<p>People make different decisions when they know the odds of an event occurring, (e.g. told 10% chance of an earthquake that year) than when they draw on only their own experience (e.g. living in a city with, on average, one earthquake every 10 years). It may be that when we make decisions based on our past experience (decisions from experience) we are more likely to choose a risky option when it can lead to the biggest win and avoid it when it can lead to the biggest loss, this effect is called the Extreme-Outcome rule. Across three Experiments we tested the Extreme-Outcome rule by having participants make repeated choices between either safe or risky options which had the same expected value. In each experiment, we varied the magnitude of the reinforcer’s participants could win in both an Experience condition and a condition that had both description and experience information. In Experiment 1 where we had two reinforcer sizes (small and large) we found an Extreme-Outcome effect in the Experience condition, but not the Description-Experience condition. In Experiment 2 we tested a prediction of the Extreme-Outcome rule that participants would be sensitive to the best and worst outcome by adding another reinforcer size (reinforcers were small, medium and large) and therefore on some trials neither alternative included an extreme outcome. We also removed zero as a potential outcome to investigate whether zero aversion might be driving the effect of reinforcer magnitude in the Experience condition. We did not find response patterns consistent with an Extreme-Outcome rule in the Experience condition. Instead, participants were least risk seeking when the reinforcer was small, but there was no difference in levels of risk seeking between the medium and large reinforcer trials. In other words, there was an effect of the low-extreme outcome but not the high-extreme outcome. Like Experiment 1, in the Description-Experience condition risk preference was not influenced by reinforcer size, but the absolute levels were higher. To investigate whether this increase in risk preference was due to removing the zero, in Experiment 3 we manipulated whether zero was present or absent. When zero was absent, risk preference was not influenced by the size of the reinforcer in the Description-Experience condition, but there was an effect of the low-extreme outcome when zero was present. We also found an effect of the low extreme outcome in the Experience condition regardless of whether zero was present or absent. Overall, these findings suggest the Extreme-Outcome rule needs to be modified to take into account the effect of the low extreme but not the high extreme outcome.</p>

scholarly journals Anti-social motives explain risk aversion for others in decisions from experience

2017 ◽  
Author(s):  
Sebastian Olschewski ◽  
Marius Dietsch ◽  
Elliot Andrew Ludvig
Keyword(s):  
Social Behavior ◽  
Risk Aversion ◽  
Risk Taking ◽  
Risk Preferences ◽  
Risk Preference ◽  
Expected Value ◽  
Risk Averse ◽  
Social Motives ◽  
Decisions From Experience ◽  
Risky Option

When deciding for others based on explicitly described odds and outcomes, people often havedifferent risk preferences for others than for themselves. In two pre-registered experiments, we examine risk preference for others where people learn about the odds and outcomes by experiencing them through sampling. In both experiments, on average, people were more risk averse for others than for themselves, but only when the risky option had a higher expected value. Furthermore, based on a separate set of choices, we classified people as pro- or anti- social. Only those people classified as anti-social were more risk averse for others, whereas those classified as prosocial chose similarly for themselves and others. When the uncertainty was removed, however, all participants exhibited less anti-social behavior. Together, these results suggest that anti-social motives contribute to the observed limited risk-taking for others and that outcome uncertainty facilitates the expression of these motives.

scholarly journals The Role of Memory in Distinguishing Risky Decisions from Experience and Description

2017 ◽  
Vol 70 (10) ◽  
pp. 2048-2059 ◽  
Author(s):  
Christopher R. Madan ◽  
Elliot A. Ludvig ◽  
Marcia L. Spetch
Keyword(s):  
Risk Preferences ◽  
Risk Preference ◽  
Risky Choice ◽  
Risk Averse ◽  
Memory Biases ◽  
Opposite Pattern ◽  
Decisions From Experience ◽  
Risk Seeking ◽  
Subject Design

People's risk preferences differ for choices based on described probabilities versus those based on information learned through experience. For decisions from description, people are typically more risk averse for gains than for losses. In contrast, for decisions from experience, people are sometimes more risk seeking for gains than losses, especially for choices with the possibility of extreme outcomes (big wins or big losses), which are systematically overweighed in memory. Using a within-subject design, this study evaluated whether this memory bias plays a role in the differences in risky choice between description and experience. As in previous studies, people were more risk seeking for losses than for gains in description but showed the opposite pattern in experience. People also more readily remembered the extreme outcomes and judged them as having occurred more frequently. These memory biases correlated with risk preferences in decisions from experience but not in decisions from description. These results suggest that systematic memory biases may be responsible for some of the differences in risk preference across description and experience.

scholarly journals Decision-Making Deficits in ADHD Are Not Related to Risk Seeking But to Suboptimal Decision-Making: Meta-Analytical and Novel Experimental Evidence

2018 ◽  
Vol 25 (4) ◽  
pp. 486-501 ◽  
Author(s):  
Tycho J. Dekkers ◽  
Joost A. Agelink van Rentergem ◽  
Hilde M. Huizenga ◽  
Hamutal Raber ◽  
Rachel Shoham ◽  
...  
Keyword(s):  
Decision Making ◽  
Substance Abuse ◽  
Regression Analysis ◽  
Real Life ◽  
Expected Value ◽  
Risk Seeking ◽  
Growing Body ◽  
Meta Regression ◽  
Meta Regression Analysis ◽  
Risky Option

Objective: ADHD is related to decision-making deficits in real-life (e.g., substance abuse) and on experimental tasks (increased preference for risky options). In most tasks, risk and expected value are confounded (risky options have lowest expected value), making it impossible to disentangle risky from suboptimal (i.e., not choosing highest expected value) decision-making. We differentiated between risky and suboptimal decision-making in ADHD in two studies. Method and Results: First, on a multilevel meta-regression analysis ( k = 48, n_ADHD = 1,144, n_Control = 1,108), ADHD and controls differed if the risky option was suboptimal (ADHD choosing more risky/suboptimal), whereas groups performed similar if the risky option was not suboptimal. Second, an empirical study showed that adults with ADHD ( n = 40) made more suboptimal, but not more risky choices than controls ( n = 40). Conclusion: These results contribute to a growing body of evidence that decision-making deficits in ADHD are driven by suboptimal decision-making and not by risk seeking.

scholarly journals The power of nothing: Risk preference in pigeons, but not people, is driven primarily by avoidance of zero outcomes

2018 ◽  
Author(s):  
Jeffrey Matthew Pisklak ◽  
Christopher R Madan ◽  
Elliot Andrew Ludvig ◽  
Marcia L Spetch
Keyword(s):  
Homo Sapiens ◽  
Risk Preference ◽  
Columba Livia ◽  
Risky Choice ◽  
Repeated Exposure ◽  
Decision Context ◽  
Risk Seeking ◽  
Risky Choices ◽  
Risky Option ◽  
Risky Decisions

When making risky decisions, people and pigeons often show similar choice patterns. When people learn the reward probabilities through repeated exposure to the outcomes, their preference is disproportionately influenced by the extreme (highest and lowest) outcomes occurring in the decision context. Overweighting of these extremes increases preference for risky alternatives that lead to the highest outcome and decreases preference for risky alternatives that lead to the lowest outcome, termed the extreme-outcome rule. This rule predicts greater risk seeking for choices between safe and risky high-value outcomes than for choices between safe and risky low-value outcomes, when both choices occur in the same context. In a series of studies, we examine how this extreme-outcome rule generalizes within and across two evolutionary distant species: pigeons (Columba livia) and humans (Homo sapiens). Both species showed risky choices consistent with the extreme-outcome rule when a low-value risky option could yield an outcome of zero. When all outcome values were increased such that none of the options could lead to zero, people but not pigeons were still consistent with the extreme-outcome rule. Unlike people, pigeons no longer avoided a low-value risky option when it yielded a non-zero food outcome. These results suggest that, despite some similarities, different mechanisms underlie risky choice in pigeons and people.

The Price of Predictability: Estimating Inconsistency Premiums in Social Interactions

2021 ◽  
pp. 014616722199853
Author(s):  
Judith Gerten ◽  
Michael K. Zürn ◽  
Sascha Topolinski
Keyword(s):  
Risk Premium ◽  
Psychological Research ◽  
Expected Value ◽  
Decision Makers ◽  
Expected Returns ◽  
Expected Return ◽  
Total N ◽  
Financial Decision ◽  
Variance Risk ◽  
Risky Option

For financial decision-making, people trade off the expected value (return) and the variance (risk) of an option, preferring higher returns to lower ones and lower risks to higher ones. To make decision-makers indifferent between a risky and risk-free option, the expected value of the risky option must exceed the value of the risk-free option by a certain amount—the risk premium. Previous psychological research suggests that similar to risk aversion, people dislike inconsistency in an interaction partner’s behavior. In eight experiments (total N = 2,412) we pitted this inconsistency aversion against the expected returns from interacting with an inconsistent partner. We identified the additional expected return of interacting with an inconsistent partner that must be granted to make decision-makers prefer a more profitable, but inconsistent partner to a consistent, but less profitable one. We locate this inconsistency premium at around 31% of the expected value of the risk-free option.

Frequency of enforcement is more important than the severity of punishment in reducing violation behaviors

2021 ◽  
Vol 118 (42) ◽  
pp. e2108507118
Author(s):  
Kinneret Teodorescu ◽  
Ori Plonsky ◽  
Shahar Ayal ◽  
Rachel Barkan
Keyword(s):  
High Probability ◽  
Real Life ◽  
Expected Value ◽  
Relative Importance ◽  
Decisions From Experience ◽  
High Severity ◽  
Low Probability ◽  
Violation Rate ◽  
Severity Of Punishment ◽  
Enforcement Policies

External enforcement policies aimed to reduce violations differ on two key components: the probability of inspection and the severity of the punishment. Different lines of research offer different insights regarding the relative importance of each component. In four studies, students and Prolific crowdsourcing participants (Ntotal = 816) repeatedly faced temptations to commit violations under two enforcement policies. Controlling for expected value, we found that a policy combining a high probability of inspection with a low severity of fines (HILS) was more effective than an economically equivalent policy that combined a low probability of inspection with a high severity of fines (LIHS). The advantage of prioritizing inspection frequency over punishment severity (HILS over LIHS) was greater for participants who, in the absence of enforcement, started out with a higher violation rate. Consistent with studies of decisions from experience, frequent enforcement with small fines was more effective than rare severe fines even when we announced the severity of the fine in advance to boost deterrence. In addition, in line with the phenomenon of underweighting of rare events, the effect was stronger when the probability of inspection was rarer (as in most real-life inspection probabilities) and was eliminated under moderate inspection probabilities. We thus recommend that policymakers looking to effectively reduce recurring violations among noncriminal populations should consider increasing inspection rates rather than punishment severity.

Respondents in Asian Cultures (e.g., Chinese) are More Risk-Seeking and More Overconfident than Respondents in Other Cultures (e.g., in United States) but the Reciprocal Predictions are in Total Opposition: How and Why?

2004 ◽  
Vol 4 (2) ◽  
pp. 263-292 ◽  
Author(s):  
Shu Li ◽  
Yongqing Fang
Keyword(s):  
United States ◽  
Social Network ◽  
Risk Taking ◽  
Risk Preferences ◽  
Risk Preference ◽  
Cross Cultural ◽  
Cultural Variations ◽  
Risk Seeking ◽  
The Social ◽  
Predicted Risk

AbstractTriggered by rather surprising findings that respondents in Asian cultures (e.g., Chinese) are more risk-seeking and more overconfident than respondents in other cultures (e.g., in United States) and that the reciprocal predictions are in total opposition, four experiments were designed to extend previous collective-culture oriented researches. Results revealed that (1) Singapore 21, which is a vision of Singapore in the 21st century and has highlighted the promotion of a collective culture, did not advocate greater risk-seeking but led to weaker overconfidence; (2) the knowledge of "financial help from social network" did not permit prediction of risk preference but the knowledge of "the value difference between possible outcomes" did; (3) the social network could be viewed not only as a positive "cushion" but also as a negative "burden" in both gain and loss domains of risky choices; (4) the predictions of the risk-as-value, risk-as-feelings and stereotype hypotheses were not consistent with the predicted risk preferences of others but the predictions of the economic-performance hypothesis were consistent with the predicted risk preferences as well as the predicted overconfidence of others. The implications for cross-cultural variations in overconfidence and for cross-cultural variations in risk-taking were discussed.

scholarly journals Risk aversion and risk seeking in multicriteria forest management: a Markov decision process approach

2017 ◽  
Vol 47 (6) ◽  
pp. 800-807 ◽  
Author(s):  
Joseph Buongiorno ◽  
Mo Zhou ◽  
Craig Johnston
Keyword(s):  
Risk Aversion ◽  
Markov Decision Process ◽  
Decision Process ◽  
Weighted Average ◽  
Basal Area ◽  
Risk Attitude ◽  
Expected Value ◽  
Process Models ◽  
Risk Seeking ◽  
Markov Decision

Markov decision process models were extended to reflect some consequences of the risk attitude of forestry decision makers. One approach consisted of maximizing the expected value of a criterion subject to an upper bound on the variance or, symmetrically, minimizing the variance subject to a lower bound on the expected value. The other method used the certainty equivalent criterion, a weighted average of the expected value and variance. The two approaches were applied to data for mixed softwood–hardwood forests in the southern United States with multiple financial and ecological criteria. Compared with risk neutrality or risk seeking, financial risk aversion reduced expected annual financial returns and production and led to shorter cutting cycles that lowered the expected diversity of tree species and size, stand basal area, stored CO2e, and old-growth area.

scholarly journals The Effect of Time Pressure on Risky Financial Decisions from Description and Decisions from Experience

2021 ◽  
Author(s):  
Pete Wegier ◽  
Julia Spaniol
Keyword(s):  
Decision Making ◽  
Opposite Direction ◽  
Risk Taking ◽  
Time Pressure ◽  
Time Constraints ◽  
Decisions From Experience ◽  
Financial Decisions ◽  
Risk Seeking ◽  
Gain And Loss ◽  
Decision Tasks

Time pressure has been found to impact decision making in various ways, but studies on the effects time pressure in risky financial gambles have been largely limited to description-based decision tasks and to the gain domain. We present two experiments that investigated the effect of time pressure on decisions from description and decisions from experience, across both gain and loss domains. In description-based choice, time pressure decreased risk seeking for losses, whereas for gains there was a trend in the opposite direction. In experience-based choice, no impact of time pressure was observed on risk-taking, suggesting that time constraints may not alter attitudes towards risk when outcomes are learned through experience.

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