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

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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)

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.

Suggested Citation

  • Cary Frydman & Ian Krajbich, 2022. "Using Response Times to Infer Others’ Private Information: An Application to Information Cascades," Management Science, INFORMS, vol. 68(4), pages 2970-2986, April.
    • Handle: RePEc:inm:ormnsc:v:68:y:2022:i:4:p:2970-2986
    DOI: 10.1287/mnsc.2021.3994
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