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ABSTRACT We test whether the display of information causally affects investor behavior in a high‐stakes trading environment. Using investor‐level brokerage data from China and a natural experiment, we estimate the impact of a shock that increased the salience of a stock's purchase price but did not change the investor's information set. We employ a difference‐in‐differences approach and find that the salience shock causally increased the disposition effect by 17%. We use microdata to document substantial heterogeneity across investors in the treatment effect. A previously documented trading pattern, the “rank effect,” explains heterogeneity in the change in the disposition effect. 

The standard assumption in social learning environments is that agents learn from others through choice outcomes. We argue that in many settings, agents can also infer information from others’ response times (RT), which can increase efficiency. To investigate this, we conduct a standard information cascade experiment and find that RTs do contain information that is not revealed by choice outcomes alone. When RTs are observable, subjects extract this private information and are more likely to break from incorrect cascades. Our results suggest that in environments where RTs are publicly available, the information structure may be richer than previously thought. 

Abstract We experimentally test a theory of risky choice in which the perception of a lottery payoff is noisy due to information processing constraints in the brain. We model perception using the principle of efficient coding, which implies that perception is most accurate for those payoffs that occur most frequently. Across two preregistered laboratory experiments, we manipulate the distribution from which payoffs in the choice set are drawn. In our first experiment, we find that risk taking is more sensitive to payoffs that are presented more frequently. In a follow-up task, we incentivize subjects to classify which of two symbolic numbers is larger. Subjects exhibit higher accuracy and faster response times for numbers they have observed more frequently. In our second experiment, we manipulate the payoff distribution so that efficient coding modulates the strength of valuation biases. As we experimentally increase the frequency of large payoffs, we find that subjects perceive the upside of a risky lottery more accurately and take greater risk. Together, our experimental results suggest that risk taking depends systematically on the payoff distribution to which the decision maker’s perceptual system has recently adapted. More broadly, our findings highlight the importance of imprecise and efficient coding in economic decision making.