Control of the socio-economic systems using herding interactions

2005

Abstract We study the role of social preferences in explaining herding behavior in anonymous risky environments. In an experiment similar to information cascade settings, but with no private information, we find no evidence that inequality aversion causes herding. On the contrary, we observe a significant amount of non-conform behavior, which cannot be attributed to errors. Keywords: herding, information cascades, non-conformity, inequality aversion, laboratory experiments JEL Classification: C92, D31, D81

We derive a system of stochastic differential equations simulating the dynamics of the three agent groups with herding interaction. Proposed approach can be valuable in the modeling of the complex socio-economic systems with similar composition of the agents. We demonstrate how the sophisticated statistical features of the absolute return in the financial markets can be reproduced by extending the herding interaction of the agents and introducing the third agent state. As well we consider possible extension of proposed herding model introducing additional exogenous noise. Such consistent microscopic and macroscopic model precisely reproduces empirical power law statistics of the return in the financial markets.

Theoretical Economics Letters, 2018

Present study is an attempt to analyse the presence of herding in different economic conditions. A mix of developed and developing countries is selected from different corners of the word. Our sample comprises 35 world markets, out of which 18 are emerging markets while 17 are developed markets. Daily data of all constituents stocks of the representative indices of these markets are extracted over most recent period ranging from Jan. 2000 to Apr. 2018. Applying different methodologies static and time varying, we find that only 11 markets out of 35 exhibit significant herding behaviour. These markets majorly belong to Asia, Africa and Middle East. We also try to relate herding with region, culture and state of economy and do not find any significant relation of these variables with herding.

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.

Nonlinear Analysis: Real World Applications, 2011

In this paper, we show that under suitable simple assumptions the classical two populations system may exhibit unexpected behaviors. Considering a more elaborated social model, in which the individuals of one population gather together in herds, while the other one shows a more individualistic behavior, we model the fact that interactions among the two occur mainly through the perimeter of the herd. We account for all types of populations' interactions, symbiosis, competition and the predator-prey interactions. There is a situation in which competitive exclusion does not hold: the socialized herd behavior prevents the competing individualistic population from becoming extinct. For the predator-prey case, sustained limit cycles are possible, the existence of Hopf bifurcations representing a distinctive feature of this model compared with other classical predator-prey models. The system's behavior is fully captured by just one suitably introduced new threshold parameter, defined in terms of the original model parameters.

Queueing Systems, 2014

The system mentioned in the title belongs to the family of the so-called massively multi-player online social games. It features a scoring system for the elements of the game that is prone to herding effects. We analyze in detail its stationary regime in the thermodynamic limit, when the number of players tends to infinity. In particular, for some classes of input sequences and selection policies, we provide necessary and sufficient conditions for the existence of a complete meanfield-like measure, showing off an interesting condensation phenomenon.

Trends in Cognitive Sciences, 2005

Computational models of human collective behavior offer promise in providing quantitative and empirically verifiable accounts of how individual decisions lead to the emergence of group-level organizations. Agentbased models (ABMs) describe interactions among individual agents and their environment, and provide a process-oriented alternative to descriptive mathematical models. Recent ABMs provide compelling accounts of group pattern formation, contagion and cooperation, and can be used to predict, manipulate and improve upon collective behavior. ABMs overcome an assumption that underlies much of cognitive science -that the individual is the crucial unit of cognition. The alternative advocated here is that individuals participate in collective organizations that they might not understand or even perceive, and that these organizations affect and are affected by individual behavior.

Advances in Complex Systems, 2013

We study a system in which N agents have to decide between two strategies θi(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 ai(θi, fi) received from the strategic interaction with their n counterparts, (ii) the fraction fi 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 fi 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 evoluti...

2010

This study investigates how and under what conditions networks and dyadic social control rationalize participation in collective action. Social control mechanisms, such as behavioral confirmation and social selective incentives, do not necessarily help mobilization in collective action, but they might also act against it. In certain in certain network configurations, not only an increase in the strength of conformity, but also an increase in selective incentives could turn out to be inefficient to establish mass collective action. This contradiction is captured by an integrative model that combines the n-person social dilemma model of collective action with local interaction games. Predictions of the integrated model reveal non-monotonic effects of the strength of social control on full contribution. For structural effects, the model predicts that cohesion is the most important catalyst of full contribution; besides, modularity of the network facilitates partial contribution equilibria.

Collective behavior is a form of action that is neither conforming (in which actors follow prevailing norms) nor deviant (in which actors violate those norms). It is a spontaneous manifestation of the ensemble and it results from the complex interaction mechanism between the actors. In societies usually it takes place when norms are absent or unclear, or when they contradict each other. Puzzling collective behavior can be observed in different societies including human social life and wildlife as well. It is also present in lifeless systems from physics, chemistry and engineering. Based on such well-known emerging behavior novel bio-inspired systems can be developed aimed for flexible manufacturing, systems control, traffic planning and several other advanced field of engineering. This paper deals with the theoretical background of the phenomena and offers a wide overlook of diverse forms of collective behavior in history, philosophy, psychology, sociology, biology, physics, chemistry and technology.