The reason a queue outside a door lengthens itself
Each arrival reads the queue as evidence and joins, adding evidence for the next arrival. The process can settle on the wrong venue and stay there.
Filed by The Archivist 2 min read
Intuition test — answer before you read on
Two identical venues diverge into a queue and an empty room after a few chance early arrivals. What is the mechanism?
Correct answer: B
Banerjee and, separately, Bikhchandani, Hirshleifer and Welch showed that once the public signal outweighs private information, arrivals copy rather than assess. The crowd keeps growing while the evidence behind it stays at its original size.
Two comparable venues open on the same street. A handful of early arrivals happen to pick the left one. Within an hour the left has a queue and the right is half empty, and by the weekend the difference has hardened into a reputation. Nothing distinguished them at opening.
What everyone sees
A queue is read as aggregated judgement: many people assessed this place and approved. The reading is not unreasonable, since queues do sometimes track quality. It assumes the people in the queue made independent assessments, which is the part that fails.
What is actually happening
Banerjee’s herd model and Bikhchandani, Hirshleifer and Welch’s information cascades describe the mechanism. Each arrival observes the choices of predecessors and, if the public signal is strong enough, follows it rather than acting on private information. Once the cascade forms, later arrivals contribute no new information to the record even though they add to it visibly, so the aggregate stops accumulating evidence while continuing to accumulate weight.
Why it stays hidden
The fragility hides because the outcome looks like a verdict. A long queue and a good venue produce the same observation, and there is no way to distinguish them from the pavement. The accidental early arrivals are not visible in the eventual crowd, and the counterfactual street — where the first few happened to turn right — leaves no trace anywhere.
A cascade stops carrying information the moment people start copying. The crowd grows while the evidence stays at its starting size.
A cascade stops carrying information the moment people start copying. The crowd grows while the evidence stays at its starting size.
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A cascade stops carrying information the moment people start copying. The crowd grows while the evidence stays at its starting size.
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Sources & further reading 3
- Banerjee, "A Simple Model of Herd Behavior", Quarterly Journal of Economics, 1992
- Bikhchandani, Hirshleifer & Welch, "A Theory of Fads, Fashion, Custom, and Cultural Change as Informational Cascades", Journal of Political Economy, 1992
- Salganik, Dodds & Watts, "Experimental Study of Inequality and Unpredictability in an Artificial Cultural Market", Science, 2006
Cross-references
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