Optimal Stopping in a Dynamic Salience Model

We study dynamic choice under risk through the lens of salience theory. We derive predictions on salient thinkers’ gambling decisions and strategy choices. We test our model experimentally and find support for all of our predictions. We also detect a strong correlation between static and dynamic choices, suggesting that salience theory can coherently explain risky choice in both static and dynamic contexts. Our results help to understand when people sell assets, stop gambling, enter the job market or retire.