Using Response Times to Infer Others’ Private Information: An Application to Information Cascades

Cary Frydman () and Ian Krajbich ()
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Cary Frydman: Marshall School of Business, University of Southern California, Los Angeles, California 90089
Ian Krajbich: Department of Economics, The Ohio State University, Columbus, Ohio 43210; Department of Psychology, The Ohio State University, Columbus, Ohio 43210

Management Science, 2022, vol. 68, issue 4, 2970-2986

Abstract: 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.

Keywords: information cascade; herding; response time; reaction time; drift diffusion model; sequential sampling model; information aggregation; social learning (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:68:y:2022:i:4:p:2970-2986

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