---
type: claim
domain: mechanisms
description: "When agents rationally weight public information over private signals, the group loses its private information permanently -- producing bubbles without requiring any individual irrationality"
confidence: likely
source: "Bikhchandani, Hirshleifer, Welch (1992), Banerjee (1992), Anderson and Holt (1997)"
created: 2026-04-21
secondary_domains: [internet-finance, collective-intelligence]
related_claims:
  - "the-efficient-market-hypothesis-fails-because-its-three-core-assumptions-rational-investors-independence-and-normal-distributions-all-fail-empirically"
  - "hayeks-knowledge-problem-reveals-that-economic-planning-requires-both-local-and-global-information-which-are-never-simultaneously-available-to-decision-makers"
---

# Information cascades produce rational bubbles where every individual acts reasonably but the group outcome is catastrophic

An information cascade occurs when sequential decision-makers rationally choose to follow the actions of predecessors rather than act on their own private information. Each individual is making the correct Bayesian decision given what they observe. But the collective outcome is catastrophic: the group's decision becomes decoupled from the group's total information.

The mechanism is precise. Suppose agents choose sequentially whether to adopt or reject something, each with a private signal that's slightly informative. Agent 1 follows their signal. Agent 2 sees Agent 1's choice and weighs it against their own signal. If both signals agree, Agent 2 follows. Once two agents have chosen the same way, Agent 3's private signal -- even if it disagrees -- is outweighed by the public evidence of two preceding choices. Agent 3 rationally ignores their private information and follows the crowd. Every subsequent agent does the same. The cascade has started.

The critical feature: once the cascade begins, no new private information enters the public record. Agents 3 through 1,000 are all copying the same two early signals. The group of 1,000 has the information of 2. This is why cascades are fragile -- a single piece of credible public counter-evidence can shatter the entire cascade instantly, because it was never grounded in accumulated evidence to begin with.

This explains phenomena that irrationality-based theories cannot. Bubbles form among sophisticated investors. Bank runs happen among depositors who individually have no reason to panic. Technology adoption follows fads that reverse overnight. Fashion cycles. The common thread: sequential observation + private signals + rational Bayesian updating = systematic information loss.

The implication for mechanism design is that any system where agents observe each other's actions before making their own choice is vulnerable to cascades. Prediction markets partially solve this by forcing agents to put money behind their private signals (making signals public through prices), but they're still vulnerable when early liquidity providers set a price that subsequent traders anchor on.

## Evidence
- Bikhchandani, Hirshleifer, Welch (1992) -- formal model showing cascades arise from rational Bayesian updating with sequential observation
- Anderson and Holt (1997) -- laboratory experiments confirming cascade formation: subjects rationally ignored private signals after observing 2-3 predecessors
- Banerjee (1992) -- parallel model showing herding as rational behavior under uncertainty
- Dot-com bubble (1995-2000) -- sophisticated VCs funded companies they privately doubted because public signals (other VC investments) outweighed private analysis
- Bank runs (Diamond-Dybvig 1983) -- depositors rationally withdraw when they observe others withdrawing, regardless of bank solvency

## Challenges
- In practice, cascades often involve genuinely irrational behavior too -- separating rational herding from irrationality is empirically difficult
- Diverse information sources and simultaneous (rather than sequential) decisions reduce cascade vulnerability
