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Definition: An informational cascades is a situation in which every subsequent actor, based on the observations of others, makes the same choice independent of his/her private signal.

Erroneous Mass Behavior: In an informational cascades everyone is individually acting rationally. Still, even if all participants as a collective have overwhelming information in favor of the correct action, each and every participant may take the wrong action. The probability that everyone is taking the wrong action is less than 50%, but it is easy to construct examples in which everyone is wrong with 30-40% probability.

Fragility: A little bit of public information (or an unusual signal) can overturn a long-standing informational cascades. That is, even though a million people may have chosen one action, seemingly little information can induce the next million people to choose the opposite action. Fragility is an integral component of the Informational cascades theory!

A Simple Example: Let us presume that you and a lot of other people have to find your way to a new destination, and you come to a crossway where you can only either go left or right. Everyone has a private imperfect signal (call it "judgment" or "opinion"). For simplicity, let everyone have a private signal "left" ("right") with probability 2/3 if the true best choice is to go left (right). So, the signal helps but it is not perfect. Everyone's signal is equally good. Now, assume that you are the third person to choose, and you first saw a man and then a woman go left. I claim that it is optimal for you to go "left" even if your private signal/intuition says "right". Why? You know that the man must have had an "l" signal, because he went left. The woman saw the man go "left." She would have figured out that the first individual's signal was "left". If her private signal was "left", she would have surely walked left, too. If her signal was "right", she would have been aware of one right and one left signal. She might have walked either way. Now it is your turn. Having seen both the man and the woman walk "left," you know that the man had a "left" signal and the woman had a better than even chance of having had a "left" signal. Loosely speaking, the actions of your predecessors give you more than 1 "left" signal. Even if your private information is 1 "right" signal, net-in-net you should choose "left" if you are acting rationally---and so will everyone choosing after you. Now, everyone after you will know that what you did had nothing to do with your private information---but they will be in the same boat. The optimal decision will be to do the same thing and go left. One major consequence of informational cascades is that you may get a million rational individuals walking "left" just because the first two individuals walked "left", even if the true best choice was "right." (This will happen with more than 1/3*1/3=1/9 probability [first two individuals got incorrect "left" signals].)

So, what does this mean for society? Cascades predict that you can get massive social imitation, occasionally leading everyone (the "herd") to the incorrect choice. (Because everyone knows that there is very little information in a cascade, cascades are "fragile"; a little bit of new public information can make a big difference).

Distinguishing Informational Cascades from Herd Behavior in the Laboratory, Celen and Kariv, 2003
Two phenomena that have elicited particular interest are informational cascades and herd behavior, which can arise in a wide variety of economic circumstances. These phenomena have been deemed pathological because erroneous outcomes may occur despite individual rationality, and they may in fact be the norm in certain circumstances. While the terms informational cascade and herd behavior are used interchangeably in the literature, Smith and Sorensen (2000) emphasize that there is a significant difference between them. An informational cascade is said to occur when an infinite sequence of individuals ignore their private information when making a decision, whereas herd behavior occurs when an infinite sequence of individuals make an identical decision, not necessarily ignoring their private information. In other words, when acting in a herd, individuals choose the same action, but they may have acted differently from one another if the realization of their private signals had been different. In an informational cascade, an individual considers it optimal to follow the behavior of her predecessors without regard to her private signal since her belief is so strongly held that no signal can outweigh it. Thus, an informational cascade implies a herd but a herd is not necessarily the result of an informational cascade. The practical importance of the distinction between herds and cascades is that in a cascade social learning ceases since individual behavior becomes purely imitative and hence is uninformative. In a herd, in contrast, individuals become more and more likely to imitate but their actions still may provide information.
Information Cascades, SKERRATT, 2000
"There is now substantial evidence that financial markets do not react to information exactly as suggested by the efficient market hypothesis. Consequently, a number of papers have asked the question "how can this be explained?" Initially, one of the main explanations was that exogenous institutional imperfections, such as transactions costs, are the cause. This type of explanation is now being replaced by behavioural ones, which focus on exactly how agents process information. The idea in this paper is that agents respond not only to their own private information, but also to the information which they infer other agents have. The inference is made on the basis of the actions which other agents are seen to take".
Market Crashes without External Shocks, Hart and Tauman, 2002
Market crash is usually considered an indication that the fundamentals of the economy have changed and recession is around the corner. This however need not be so. For instance, in October 1987 Wall Street lost over 20% of its value in one day, but this was not followed by a recession. Moreover, in the days preceding the crash, there were no significant external events or bad news" that could justify the dramatic price fall. We argue here that market crashes (and, similarly, market bubbles) may well be the result of information processing by the participants|and nothing else. Moreover, in terms of market observables, it looks as if nothing is really changing. Still, underneath the surface, there is a gradual updating of information by the participants. Then, at a certain point in time, this causes a sudden change of behavior.
Information Cascades and Rational Conformity, Anderson and Holt
"An information cascade is a pattern of matching decisions. A cascade can occur when people observe and follow "the crowd"' which can be rational if the information revealed in other's earlier decisions outweights one's own private information".
Conversation, Observational Learning, and Informational Cascades, CAO, Henry and HIRSHLEIFER
"We offer a model to explain why groups of people sometimes converge upon poor decisions and are prone to fads, even though they can discuss the outcomes of their choices. Models of informational herding or cascades have examined how rational individuals learn by observing predecessors’ actions, and show that when individuals stop using their own private signals, improvements in decision quality cease. A literature on word-of-mouth learning shows how observation of outcomes as well as actions can cause convergence upon correct decisions. However, the assumptions of these models differ considerably from those of the cascades/herding literature. In a setting which adds ‘conversational’ learning about both the payoff outcomes of predecessors to a basic cascades model, we describe conditions under which (1) cascades/herding occurs with probability one; (2) once started there is a positive probability (generally less than one) that a cascade lasts forever; (3) cascades aggregate information ine±ciently and are fragile; (4) the ability to observe past payoffs can reduce average decision accuracy and welfare; and (5) delay in observation of payoffs can improve average accuracy and welfare".
Herd Behavior and Cascading in Capital Markets: A Review and Synthesis, Hirshleifer and Teoh, 2001
"We review theory and evidence relating to herd behavior, payoff and reputational interactions, social learning, and informational cascades in capital markets. We offer a simple taxonomy of effects, and evaluate how alternative theories may help explain evidence on the behavior of investors, firms, and analysts. We consider both incentives for parties to engage in herding or cascading, and the incentives for parties to protect against or take advantage of herding or cascading by others".
Stop-Loss Orders and Price Cascades in Currency Markets, OSLER
"In this paper, I provide evidence that currency stop-loss orders contribute to rapid, self-reinforcing price movements".
A Decomposition of Global Linkages in Financial Markets over Time, Forbes and Chinn, 2003
"This paper tests if real and financial linkages between countries can explain why movements in the world's largest markets often have such large effects on other financial markets, and how these cross-market linkages have changed over time. It estimates a factor model in which a country's market returns are determined by: global, sectoral, and cross-country factors (returns in large financial markets), and country-specific effects. Then it uses a new data set on bilateral linkages between the world's 5 largest economies and about 40 other markets to decompose the cross-country factor loadings into: direct trade flows, competition in third markets, bank lending, and foreign direct investment".