Information cascades

What Is Information Cascades?

An information cascade occurs when individuals make decisions sequentially, observing the actions of those who came before them, and then disregard their own private information in favor of imitating the preceding choices. This phenomenon is a key concept within behavioral finance, which explores the psychological biases and heuristics influencing economic decision-making. Information cascades demonstrate how collective behavior can emerge even when individuals have incomplete or noisy information, leading to outcomes that may not reflect the aggregated private information of all participants. The core idea is that the public information conveyed by early decisions can overwhelm later individuals' private signals, leading them to conform to the observed pattern.

History and Origin

The concept of information cascades was formally introduced in a seminal 1992 paper by Sushil Bikhchandani, David Hirshleifer, and Ivo Welch, titled "A Theory of Fads, Fashion, Custom, and Cultural Change as Informational Cascades."¹⁰ This academic work posited that localized conformity and the fragility of mass behaviors could be explained by individuals optimally choosing to follow the actions of others, even if it meant disregarding their own private information.⁹ The authors argued that an information cascade begins when an individual, after observing the choices of predecessors, finds it optimal to follow the behavior of the preceding individuals without considering their own private signal.⁸ This original research highlighted how such cascades could lead to rapid and short-lived fluctuations, such as fads, fashions, booms, and market crashes.⁷

Key Takeaways

• An information cascade describes a situation where individuals disregard their private information and imitate the actions of others in a sequential decision-making process.
• This behavior falls under the umbrella of behavioral finance and can lead to collective actions that may not be optimal.
• Information cascades highlight the fragility of collective decisions, as initial choices, potentially based on limited information, can dictate subsequent behavior.
• They can manifest in various economic and social phenomena, including market bubbles, technology adoption, and consumer trends.
• The concept helps explain why herd behavior occurs, even among rational individuals.

Formula and Calculation

Information cascades do not involve a specific mathematical formula or calculation in the way that, for example, a discounted cash flow model does. Instead, they are conceptual models illustrating a decision-making process. The "calculation" is less about numbers and more about a rational agent's inference process, weighing their private signal against the public signal generated by the actions of others.

Consider a simplified scenario with two possible states, (A) or (B), and individuals (i = 1, 2, 3, \dots, n) making sequential decisions. Each individual (i) receives a private signal (S_i) about the true state (e.g., (S_i = A) or (S_i = B)) and observes the actions (a_1, a_2, \dots, a_{i-1}) of all previous individuals.

An information cascade begins when an individual (i) decides to take an action (a_i) that is contrary to their private signal (S_i), purely because the public information (derived from the actions of (a_1, \dots, a_{i-1})) is strong enough to outweigh their own signal. The "strength" of the public signal is determined by the number of preceding individuals who chose a particular action.

For example, if the first two individuals choose action A, the third individual might choose A, even if their private signal suggests B, because the public signal (two A's) outweighs their private signal. Once this happens, the third individual's action reveals no new private information to subsequent individuals, perpetuating the cascade. This can lead to a market inefficiency if the initial public signals were misleading.

Interpreting the Information Cascades

Interpreting information cascades involves understanding how the accumulation of observable actions can override independent judgment. When an information cascade forms, it suggests that individuals are prioritizing the public signal derived from others' behavior over their own private insights. This can be problematic because the public signal might be based on limited or even incorrect initial information. The absence of diverse viewpoints can lead to suboptimal outcomes, as new, potentially valuable private information is no longer incorporated into collective decisions. Understanding this mechanism is crucial for investors, policymakers, and anyone observing group dynamics in financial markets or broader society. The fragility of these cascades means they can suddenly reverse if new, strong public information emerges that challenges the prevailing trend. This is closely related to the concept of crowd psychology.

Hypothetical Example

Imagine a group of venture capitalists (VCs) evaluating a new startup, "InnovateTech." There are five VCs, A, B, C, D, and E, who will decide whether to invest sequentially. Each VC has conducted their own due diligence and has a private signal about the startup's potential, but they also observe the decisions of those before them.

1. VC A is the first to decide. Based solely on their rigorous due diligence, VC A chooses to invest in InnovateTech. Their private signal strongly indicated high potential.
2. VC B observes VC A's investment. VC B's private signal is somewhat positive, but not as strong as VC A's. However, seeing VC A, an experienced investor, commit capital, VC B decides to invest, reinforcing the public signal.
3. VC C observes both VC A and VC B investing. VC C's private signal is actually quite negative, indicating some red flags in the business model. Despite this, the public signal of two experienced VCs investing is powerful. Believing that A and B must have superior information or have uncovered something C missed, VC C decides to invest, overriding their own private signal. At this point, an information cascade has likely begun, as C's action adds to the public signal without reflecting C's true private information.
4. VC D observes A, B, and C all investing. VC D's private signal is neutral. The overwhelming public signal leads D to invest, convinced that so many experienced VCs cannot be wrong.
5. VC E observes all prior investments. Even if E's private signal is strongly negative, the cumulative public signal of four investments could lead E to invest, continuing the cascade.

In this scenario, VC C and VC E's decisions were influenced by the cascade, potentially leading to a collective investment in a less-than-ideal startup, simply because early positive actions snowballed. This illustrates how cognitive biases can influence investment decisions, leading to potentially inflated startup valuations.

Practical Applications

Information cascades manifest in various aspects of financial markets and economic behavior, influencing everything from individual investment decisions to broader market trends. One prominent application is in understanding stock market bubbles and crashes. During periods of irrational exuberance, investors may observe others buying certain assets and join in, driven by a fear of missing out (FOMO), even if their own analysis suggests overvaluation. This can lead to asset prices skyrocketing beyond their intrinsic value, as seen in historical events like the dot-com bubble.⁶ Conversely, in a market downturn, a cascade of selling can amplify losses as individuals panic and sell, seeing others do the same, even if fundamentals don't warrant such a drastic move.

Information cascades also play a role in the adoption of new technologies or investment products. If a few early adopters, particularly those perceived as knowledgeable or influential, embrace a new technology, others may follow suit without conducting extensive independent research. This can accelerate product diffusion but also means that a flawed product could gain widespread acceptance if initial signals were misleading.

Moreover, regulatory bodies and central banks, such as the Federal Reserve in the United States, observe behavioral phenomena like information cascades when assessing market stability and formulating monetary policy. Understanding how information propagates and influences investor behavior is critical for maintaining financial stability.⁵ For instance, the Federal Reserve Bank of San Francisco has published research discussing the impact of information on financial markets, highlighting its importance for economic analysis.⁴

Limitations and Criticisms

While information cascades provide a compelling explanation for certain collective behaviors, they have limitations and have faced criticisms. One key critique is that the model often assumes individuals are fully rational and perfectly observe previous actions and inferences. In reality, individuals may have varying degrees of rationality, imperfect observation, or differing private information precision. The seminal paper by Bikhchandani, Hirshleifer, and Welch, while foundational, acknowledges that cascades can be fragile, meaning they can be easily broken by the arrival of new public information or a sufficiently strong private signal from a latecomer.³

Another limitation is the "correctness" of the cascade. An information cascade can lead to a suboptimal outcome if the initial few decisions were based on flawed or insufficient information. Individuals following the cascade might converge on the wrong action, even if, collectively, their private signals would have led to a better decision.² This "error-prone" nature highlights a potential market failure where public information ceases to aggregate accurately.

Furthermore, some critics argue that the pure information cascade model, where private signals are completely ignored, might be too strong. In many real-world scenarios, individuals might still weigh their private information, albeit less heavily, even when a strong public signal exists. This blend of private and public information processing is often referred to as social learning. Experimental studies, including those involving financial market professionals, have shown that while cascades do occur, the behavior of experienced individuals might differ from that of less experienced subjects, suggesting that professional judgment and "quality" of public signals play a role.¹

Information Cascades vs. Herd Behavior

While often used interchangeably, "information cascades" and "herd behavior" describe distinct, though related, phenomena in behavioral finance.

In essence, an information cascade is a specific type of herding where the conformity is driven by rational (or seemingly rational) inference about information, rather than purely by irrational urges or social pressures. However, both can lead to similar outcomes, such as market bubbles or crashes, by amplifying initial trends.

FAQs

What causes information cascades in financial markets?

Information cascades in financial markets are primarily caused by sequential decision-making combined with limited or imperfect private information. When investors observe the choices of others, especially those perceived as well-informed, they may infer that these actions contain valuable information. This public signal can then overwhelm an individual's own private research or analysis, leading them to imitate the observed behavior, even if it contradicts their own initial assessment.

How do information cascades differ from rational expectations?

Information cascades differ from rational expectations in how information is processed and aggregated. Under rational expectations, it is assumed that all available information is fully incorporated into prices and decisions, and individuals use all information efficiently. In an information cascade, however, private information held by later individuals is often discarded or ignored in favor of the public signal, meaning that not all information is ultimately reflected in collective outcomes. This can lead to collective irrationality even if individual actors are behaving "rationally" given the observed public information.

Can information cascades be beneficial?

While often associated with negative outcomes like bubbles, information cascades can sometimes be beneficial. They can accelerate the adoption of genuinely valuable innovations or efficient practices by quickly disseminating information through observable actions. For example, if a superior technology is adopted by early, informed users, an information cascade can lead to its rapid widespread acceptance, promoting efficiency and progress. This rapid adoption can be seen in areas like the diffusion of innovation.

Are information cascades always harmful?

Information cascades are not always harmful, but they carry inherent risks. While they can facilitate the rapid spread of good ideas or technologies, they can just as easily lead to suboptimal outcomes if the initial information or decisions that start the cascade are flawed. The risk lies in the fact that private, potentially contradictory, information is suppressed, leading to collective decisions that may not reflect the full picture. This can contribute to systemic risk within financial systems.

How can investors avoid falling victim to information cascades?

To avoid falling victim to information cascades, investors should prioritize independent fundamental analysis and critical thinking. Rather than simply imitating the actions of others, individuals should rely on their own research, assess the intrinsic value of assets, and maintain a diversified investment portfolio. Diversifying strategies and considering contrarian viewpoints can help mitigate the influence of herd mentality and make more informed capital allocation decisions.