Herding and Social Preferences

1997

When privately informed individuals sequentially solve identical finite action choice problems seeing prior choices, herding eventually arises: everyone chooses the same action, ignoring future gains from more information revelation. This paper analyzes the team equilibrium that internalizes this gain using insights from Bayesian experimentation. This equilibrium can be implemented by selfish individuals with a simple rule, and it entails contrarian behaviour: (i) While informational herding is still constrained efficient, it requires more extreme beliefs. (ii) A new log-concavity assumption on signals both precludes cascades, and ensures that individuals should lean more against their myopic preference for actions that become more popular.

2012

We investigate whether experimental participants follow their private information and contradict herds in situations where it is empirically optimal to do so. We consider two sequences of players, an observed and an unobserved sequence. Observed players sequentially predict which of two options has been randomly chosen with the help of a medium quality private signal. Unobserved players predict which of the two options has been randomly chosen knowing previous choices of observed and with the help of a low, medium or high quality signal. We use preprogrammed computers as observed players in half the experimental sessions. Our new evidence suggests that participants are prone to a 'social-confirmation' bias and it gives support to the argument that they naïvely believe that each observable choice reveals a substantial amount of that person's private information. Though both the 'overweighting-of-private-information' and the 'social-confirmation' bias coexist in our data, participants forgo much larger parts of earnings when herding naïvely than when relying too much on their private information. Unobserved participants make the empirically optimal choice in 77 and 84 percent of the cases in the human-human and computer-human treatment which suggests that social learning improves in the presence of lower behavioral uncertainty.

Experimental Economics, 2000

We carry out two experiments to test a model of herd behaviour based on the work of Banerjee 1992. He shows that herding occurs as a result of people observing the actions of others and using this information in their own decision rule. However, in our experiments herding does not occur as frequently as Banerjee predicts. Contrary to his results, the subjects' behaviour appears to depend on the probabilities of receiving a signal and of this signal being correct. Furthermore, he nds that the pattern of decision making ove r a n umber of rounds of the game is volatile whereas we nd that decision making is volatile within rounds.

SSRN Electronic Journal

We designed four observational learning experiments to identify the key channels that, along with Bayes-rational inferences, drive herd behavior. In Experiment 1, unobserved, whose actions remain private, learn from the public actions made in turn by subjects endowed with private signals of medium quality. We find that when unobserved face a handful of identical actions that contradict their high quality signals they herd more extensively than predicted by Bayes-rational herding. Deviations from the normative solution result in severe expected losses and unobserved would be better off without the chance to learn from others. When unobserved are endowed with medium quality signals they learn rather successfully from public actions, but they overweight their low quality signals relative to public information. Experiments 2-4 reveal that non-Bayesian updating and informational misinferences are the two channels that drive excessive herding, while the strong (resp. mild) overemphasis on low (resp. medium) quality signals is caused by wrong expectations about others' strategy. A model of intuitive observational learning accounts for the phenomenon of excessive herding, it captures well herd behavior with medium quality signals, but it fails to predict that the reluctance to contradict private signals is stronger for low than for medium quality.

Given the ubiquity of potentially adverse behavioural bias owing to myopic trial-and-error learning, it seems paradoxical that improvements in decision-making performance through conformist social learning, a process widely considered to be bias amplification, still prevail in animal collective behaviour. Here we show, through model analyses and large-scale interactive behavioural experiments with 585 human subjects, that conformist influence can indeed promote favourable risk taking in repeated experience-based decision making, even though many individuals are systematically biased towards adverse risk aversion. Although strong positive feedback conferred by copying the majority’s behaviour could result in unfavourable informational cascades, our differential equation model of collective behavioural dynamics identified a key role for increasing exploration by negative feedback arising when a weak minority influence undermines the inherent behavioural bias. This ‘collective behaviou...

2008

A theory is said to be fully absorbable whenever its own acceptance by all of the individuals belonging to a certain population does not question its predictive validity. This accounts for strategic equilibria and can be related to the logic underlying convergence of behaviour and intentional herding in sequential games. This paper discusses the absorbability of informational cascades' theory by bounded rational decision-makers and analyses whether providing individuals with theoretic information on informational cascades affects overall probability of herding phenomena to occur as well as whether an incorrect cascade can be reversed because of bounded rational adapting of the theory's prescriptive.

European Economic Review

We report on an experiment that distinguishes between rational social learning and behavioral information source bias. Subjects are asked to correctly guess the current binary state of the world. Differently from other social learning studies, subjects must choose between receiving a private, noisy signal about the current state or observing the past guesses of other subjects in the prior period. Our design varies the persistence of the state across time, which affects whether private or social information is optimal. Thus our design enables us to separate subjects who choose information optimally from those who excessively use either social information ("herd animals") or private information ("lone wolves"). We find sizable proportions of both behavioral types.

American Economic Review, 2001

Nature Communications

Social norms can help solve pressing societal challenges, from mitigating climate change to reducing the spread of infectious diseases. Despite their relevance, how norms shape cooperation among strangers remains insufficiently understood. Influential theories also suggest that the level of threat faced by different societies plays a key role in the strength of the norms that cultures evolve. Still little causal evidence has been collected. Here we deal with this dual challenge using a 30-day collective-risk social dilemma experiment to measure norm change in a controlled setting. We ask whether a looming risk of collective loss increases the strength of cooperative social norms that may avert it. We find that social norms predict cooperation, causally affect behavior, and that higher risk leads to stronger social norms that are more resistant to erosion when the risk changes. Taken together, our results demonstrate the causal effect of social norms in promoting cooperation and thei...

2016

We study a system in which N agents have to decide between two strategies θ i (i ∈ 1 . . . N ), for defection or cooperation, when interacting with other n agents (either spatial neighbors or randomly chosen ones). After each round, they update their strategy responding nonlinearly to two different information sources: (i) the payoff a i (θ i , f i ) received from the strategic interaction with their n counterparts, (ii) the fraction f i of cooperators in this interaction. For the latter response, we assume social herding, i.e. agents adopt their strategy based on the frequencies of the different strategies in their neighborhood, without taking into account the consequences of this decision. We note that f i already determines the payoff, so there is no additional information assumed. A parameter ζ defines to what level agents take the two different information sources into account. For the strategic interaction, we assume a Prisoner's Dilemma game, i.e. one in which defection is the evolutionary stable strategy. However, if the additional dimension of social herding is taken into account, we find instead a stable outcome where cooperators are the majority. By means of agent-based computer simulations and analytical investigations, we evaluate the critical conditions for this transition towards cooperation. We find that, in addition to a high degree of social herding, there has to be a nonlinear response to the fraction of cooperators. We argue that the transition to cooperation in our model is based on less information, i.e. on agents which are not informed about the payoff matrix, and therefore rely on just observing the strategy of others, to adopt it. By designing the right mechanisms to respond to this information, the transition to cooperation can be remarkably enhanced.