Information Cascades/Herding: Experimental Evidence, by Dominitz and Hung

On Monday, Angela Hurd presented an interesting paper at the Heinz School seminar series. It’s on “herding” or “Information Cascades”. In the most clear-cut version, each person has some private information and has to make a binary choice with some payoffs resulting from that choice: information helps make the higher payoff choice. They can see what decision previous people have made before making their own choice, but don’t know the other people’s private information. Through Bayesian updating, you can infer something about other people’s information from their observed choices, and thus update your own priors about which is the better choice to make. If enough people make the same choice, then the “public” information from those choice swamps your own private information, and you just go along with the crowd. But that means that you don’t reveal any of your private information through your choice, because your choice does not depend on what your private information is.

As usual, in experimental settings people are found not to behave in accordance with a perfect Bayesian equilibrium in this kind of setting. Some people seem to ignore or discount severely information revealed by other people’s choices. Other people seem to think that other people’s choices continue to be informative even beyond the point where their choices should be determiend by the public information that has already been revealed.

In this experiment, Hung and Dominitz gathered some extra information from subjects: they asked them after each revealed choice to assess what the other person’s private signal was and to assign a probability to which is the best choice. They found that even after a cascade had started, people tended to think that people choosing consistent with the cascade were revealing information about their private signals, suggesting that they thought people would have broken the cascade if they had contrary signals. They also found that people were not updating their beliefs about the more profitable action sufficiently, given what they thought others’ actions revealed about their signals.

Future work will have to reveal a theory of how people are interpreting others’ choices and revising their own beliefs. Seminar participants proposed many possible elements of such a theory. One plausible element is certainly that there are multiple types, some of whom simply reveal their signals and some of whom overinterpret others’ signals. Some sophisticated types may be taking account of the existence of those other types in making their own choices.


About Paul Resnick

Professor, University of Michigan School of Information Personal home page
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