Optimistic belief updating despite inclusion of positive events

Marks, Joseph; Baines, Stephanie

doi:10.1016/j.lmot.2017.05.001

“…Beginning with Kuzmanovic, Jefferson, and Vogeley (2015), some recent work in psychology and neuroscience overcomes this limitation by randomly assigning bogus baserate information (e.g., Marks and Baines, 2017). For example, Kuzmanovic et al followed the same basic design as Sharot et al…”

Section: B Evidence and Modelsmentioning

confidence: 99%

Errors in probabilistic reasoning and judgment biases

Benjamin

¹

2019

Handbook of Behavioral Economics: Applications and Foundations 1

View full text Add to dashboard Cite

Errors in probabilistic reasoning have been the focus of much psychology research and are among the original topics of modern behavioral economics. This chapter reviews theory and evidence on this topic, with the goal of facilitating more systematic study of belief biases and their integration into economics. The chapter discusses biases in beliefs about random processes, biases in belief updating, the representativeness heuristic as a possible unifying theory, and interactions between biased belief updating and other features of the updating situation. Throughout, I aim to convey how much evidence there is for (and against) each putative bias, and I highlight when and how different biases may be related to each other. The chapter ends by drawing general lessons for when people update too much or too little, reflecting on modeling challenges, pointing to areas of economics to which the biases are relevant, and highlighting some possible directions for future work.

show abstract

“…Beginning with Kuzmanovic, Jefferson, and Vogeley (2015), some recent work in psychology and neuroscience overcomes this limitation by randomly assigning bogus baserate information (e.g., Marks and Baines, 2017 Taken all together, the evidence on preference-biased inference is confusing. In the economics literature, there are many bookbag-and-poker-chip experiments that reach 74 Within experimental economics, providing bogus information is viewed as deceptive, and deceiving experimental participants is generally considered unacceptable (or at least unethical), especially if nondeceptive methods could be used instead.…”

Section: B Evidence and Modelsmentioning

confidence: 99%

Errors in Probabilistic Reasoning and Judgment Biases

Benjamin

¹

2018

View full text Add to dashboard Cite

Errors in probabilistic reasoning have been the focus of much psychology research and are among the original topics of modern behavioral economics. This chapter reviews theory and evidence on this topic, with the goal of facilitating more systematic study of belief biases and their integration into economics. The chapter discusses biases in beliefs about random processes, biases in belief updating, the representativeness heuristic as a possible unifying theory, and interactions between biased belief updating and other features of the updating situation. Throughout, I aim to convey how much evidence there is for (and against) each putative bias, and I highlight when and how different biases may be related to each other. The chapter ends by drawing general lessons for when people update too much or too little, reflecting on modeling challenges, pointing to areas of economics to which the biases are relevant, and highlighting some possible directions for future work.

show abstract

“…Furthermore, there is neurological and behavioral evidence that subjects react more strongly to successes than to failures in sequential learning problems (Lefebvre et al 2017 ), and update asymmetrically about the possibility of negative life events happening to them (Sharot et al 2011 ). These papers are part of a wider discussion about the existence of a general “optimism bias” (Shah et al 2016 ; Marks and Baines 2017 ).…”

Section: Literaturementioning

confidence: 99%

Responsiveness to feedback as a personal trait

Buser

¹

,

Gerhards

²

,

Weele

³

2018

View full text Add to dashboard Cite

We investigate individual heterogeneity in the tendency to under-respond to feedback (“conservatism”) and to respond more strongly to positive compared to negative feedback (“asymmetry”). We elicit beliefs about relative performance after repeated rounds of feedback across a series of cognitive tests. Relative to a Bayesian benchmark, we find that subjects update on average conservatively but not asymmetrically. We define individual measures of conservatism and asymmetry relative to the average subject, and show that these measures explain an important part of the variation in beliefs and competition entry decisions. Relative conservatism is correlated across tasks and predicts competition entry both independently of beliefs and by influencing beliefs, suggesting it can be considered a personal trait. Relative asymmetry is less stable across tasks, but predicts competition entry by increasing self-confidence. Ego-relevance of the task correlates with relative conservatism but not relative asymmetry. Electronic supplementary material The online version of this article (10.1007/s11166-018-9277-3) contains supplementary material, which is available to authorized users.

show abstract

Optimistic belief updating despite inclusion of positive events

Cited by 20 publications

References 36 publications

Errors in probabilistic reasoning and judgment biases

Errors in probabilistic reasoning and judgment biases

Errors in Probabilistic Reasoning and Judgment Biases

Responsiveness to feedback as a personal trait

Contact Info

Product

Resources

About