Diffusion in complex social networks

This paper studies how a behavior spreads in a population. We consider a network of interacting agents whose actions are determined by the actions of their neighbors, according to a simple diffusion rule. We find, using a mean-field approach, the threshold for the spreading rate above which the behavior spreads and becomes persistent in the population. This threshold crucially depends on the connectivity distribution of the social network and on specific features of the diffusion rule.     

Dynamic coordination with timing frictions: Theory and applications

We present a general framework of dynamic coordination with timing frictions. A continuum of agents receive random chances to choose between two actions and remain locked in the selected action until their next opportunity to reoptimize. The instantaneous utility from each action depends on an exogenous fundamental that moves stochastically and on the mass of agents currently playing each action. Agents' decisions are strategic complements and history matters. We review some key theoretical results and show a general method to solve the social planner's problem. We then review applications of this framework to different economic problems: network externalities, statistical discrimination, and business cycles. The positive implications of these models are very similar, but the social planner's solution points to very different results for efficiency in each case. Last, we review extensions of the framework that allow for endogenous hazard rates and ex ante heterogeneous agents.     

Learning from Neighbours

When payoffs from different actions are unknown, agents use their own past experience as well as the experience of their neighbours to guide their decision making. In this paper, we develop a general framework to study the relationship between the structure of these neighbourhoods and the process of social learning.
We show that, in a connected society, local learning ensures that all agents obtain the same payoffs in the long run. Thus, if actions have different payoffs, then all agents choose the same action, and social conformism obtains. We develop conditions on the distribution of prior beliefs, the structure of neighbourhoods and the informativeness of actions under which this action is optimal. In particular, we identify a property of neighbourhood structures—local independence—which greatly facilitates social learning. Simulations of the model generate spatial and temporal patterns of adoption that are consistent with empirical work.     

Social welfare for an economy of angelic agents

This paper analyzes an economy in which all agents are pursuing the common good (or social welfare) but choices are decentralized, i.e., each agent can choose his/her action in the set of the actions that he/she can perform. One wonders if it is enough the common goal of maximizing social welfare to their will be achieved. The paper examines both the cases in which the choice made by each agent does not directly influence those of other agents, as in the competitive equilibrium analysis, and the case in which there is a direct influence, as in the game theory analyses. In the first case, we get that the common goal of maximizing social welfare is not enough to reach it, but it is necessary to coordinate the actions of individual agents by extending information to redistribute initial endowments and by introducing an appropriate social organization. We get the maximum social welfare without further intervention for the cases describable with the theory of games, but only for games of complete information. If the information is incomplete, some further coordination is generally required.     

Patterns of multi-agent land conservation: Crowding in/out,agglomeration, and policy

Private agents make large contributions to networks of conserved land, but little is known about how private agents’ decisions might be altered by government actions. This paper explores the impact of public conservation and public policy on the quantity and configuration of private land conservation and the extent to which the social optimum is reached. Because land conservation benefits often have thresholds and spatial characteristics, we consider the impact of different land conservation benefit functions on the patterns of conservation created by the interaction of private and public agents. We find that public conservation crowds private conservation in or out depending on whether marginal conservation benefits increase or decrease with total acreage, and crowding out is mitigated by the presence of budget constraints. We show how land conservation agents might interact strategically in space depending on preferences over fragmentation, and we explore that spatial strategic interaction in a case with a regional land trust and a case with hot-spot parcels. We identify when government policies, such as agglomeration bonuses and mitigating coordination costs, are most likely to increase the social benefits provided by private land conservation agents.     

Should the Good and the Selfish be Taxed Differently?*

In this paper, we consider an environment where individual actions have externalities and two types of agents exist: agents with social preferences (the good) and selfish agents. Selfish agents have pay‐off functions that do not take into account social welfare. The pay‐off of an agent is a linear combination of social welfare and the pay‐off of a selfish agent. We demonstrate that the corrective tax rates that maximize social welfare do not depend on the degree of social preferences. Hence, the good and the selfish should not be taxed differently.     

Information-sharing in social networks

We present a new model for reasoning about the way information is shared among friends in a social network and the resulting ways in which the social network fragments. Our model formalizes the intuition that revealing personal information in social settings involves a trade-off between the benefits of sharing information with friends, and the risks that additional gossiping will propagate it to someone with whom one is not on friendly terms but who is within oneʼs community. We study the behavior of rational agents in such a situation, and we characterize the existence and computability of stable information-sharing configurations, in which agents do not have an incentive to change the set of partners with whom they share information. We analyze the implications of these stable configurations for social welfare and the resulting fragmentation of the social network.     

Negative Externalities and Evolutionary Implementation

We model externality abatement as an implementation problem. A social planner would like to ensure efficient behaviour among a group of agents whose actions are sources of externalities. However, the planner has limited information about the agents' preferences, and is unable to distinguish individual agents except through their action choices. We prove that if a concavity condition on aggregate payoffs is satisfied, the planner can guarantee that efficient behaviour is globally stable under a wide range of behaviour adjustment processes by administering a variable pricing scheme. Through a series of applications, we show that the concavity condition is naturally satisfied in settings involving negative externalities. We conclude by contrasting the performance of the pricing mechanism with that of a mechanism based on direct revelation and announcement dependent forcing contracts.     

Influential listeners: An experiment on persuasion bias in social networks

This paper presents an experimental investigation of persuasion bias, a form of bounded rationality whereby agents communicating through a social network are unable to account for repetitions in the information they receive. We find that, after repeated communication within a social network, social influence depends not only on being listened to by many others, but also on listening to many others. We show that persuasion bias can be viewed as an extreme case of a generalized boundedly rational updating rule in which agents receive more or less attention depending on how many other agents they listen to. The results indicate that behavior in the experiment is consistent with an updating rule according to which agents' social influence is proportional to their indegree.     

规划理论和实践中的空间观念辨析

规划理论和实践中的空间观念塑造着我们周围的人造环境。空间观念的发展呈现出从绝对到相对、从时空分离转向时空关联、从一元到多元的变化趋势。20世纪以来规划理论逐渐吸纳相对空间观念,但迄今为止规划实践仍以绝对空间观念为主导。绝对空间观念成为规划实践低效性的深层原因,但是完全放弃绝对空间观念而将相对空间观念引入规划理论和实践不仅存在很多困难,而且会造成认识和实践上的混乱,科学的空间观念应该将绝对和相对结合起来形成多元空间观。我国规划理论研究和实践仍以绝对空间观念为主导,了解绝对空间观念的不足和吸纳相对空间观念的合理性具有重要的理论和实践意义。     

Efficiency of continuous double auctions under individual evolutionary learning with full or limited information

In this paper we explore how specific aspects of market transparency and agents’ behavior affect the efficiency of the market outcome. In particular, we are interested whether learning behavior with and without information about actions of other participants improves market efficiency. We consider a simple market for a homogeneous good populated by buyers and sellers. The valuations of the buyers and the costs of the sellers are given exogenously. Agents are involved in consecutive trading sessions, which are organized as a continuous double auction with order book. Using Individual Evolutionary Learning agents submit price bids and offers, trying to learn the most profitable strategy by looking at their realized and counterfactual or “foregone” payoffs. We find that learning outcomes heavily depend on information treatments. Under full information about actions of others, agents’ orders tend to be similar, while under limited information agents tend to submit their valuations/costs. This behavioral outcome results in higher price volatility for the latter treatment. We also find that learning improves allocative efficiency when compared to outcomes with Zero-Intelligent traders.     

An experimental study of persuasion bias and social influence in networks

In many areas of social life, individuals receive information about a particular issue of interest from multiple sources. When these sources are connected through a network, then proper aggregation of this information by an individual involves taking into account the structure of this network. The inability to aggregate properly may lead to various types of distortions. In our experiment, four agents all want to find out the value of a particular parameter unknown to all. Agents receive private signals about the parameter and can communicate their estimates of the parameter repeatedly through a network, the structure of which is known by all players. We present results from experiments with three different networks. We find that the information of agents who have more outgoing links in a network gets more weight in the information aggregation of the other agents than under optimal updating. Our results are consistent with the model of “persuasion bias” of DeMarzo et al. (2013. Q. J. Econ., 909) and at odds with an alternative heuristic according to which the most influential agents are those with more incoming links.     

Social media networks,fake news,and polarization

We study how the structure of social media networks and the presence of fake news affects the degree of misinformation and polarization in a society. For that, we analyze a dynamic model of opinion exchange in which individuals have imperfect information about the true state of the world and exhibit bounded rationality. Key to the analysis is the presence of internet bots: agents in the network that spread fake news (e.g., a constant flow of biased information). We characterize how agents’ opinions evolve over time and evaluate the determinants of long-run misinformation and polarization in the network. To that end, we construct a synthetic network calibrated to Twitter and simulate the information exchange process over a long horizon to quantify the bots’ ability to spread fake news. A key insight is that significant misinformation and polarization arise in networks in which only 15% of agents believe fake news to be true, indicating that network externality effects are quantitatively important. Higher bot centrality typically increases polarization and lowers misinformation. When one bot is more influential than the other (asymmetric centrality), polarization is reduced but misinformation grows, as opinions become closer the more influential bot’s preferred point. Finally, we show that threshold rules tend to reduce polarization and misinformation. This is because, as long as agents also have access to unbiased sources of information, threshold rules actually limit the influence of bots.     

It’s a match! Simulating compatibility-based learning in a network of networks

In this article, we develop a new way to capture knowledge diffusion and assimilation in innovation networks by means of an agent-based simulation model. The model incorporates three essential characteristics of knowledge that have not been covered entirely by previous diffusion models: the network character of knowledge, compatibility of new knowledge with already existing knowledge, and the fact that transmission of knowledge requires some form of attention. We employ a network-of- networks approach, where agents are located within an innovation network and each agent itself contains another network composed of knowledge units (KUs). Since social learning is a path-dependent process, in our model, KUs are exchanged among agents and integrated into their respective knowledge networks depending on the received KUs’ compatibility with the currently focused ones. Thereby, we are also able to endogenize attributes such as absorptive capacity that have been treated as an exogenous parameter in some of the previous diffusion models. We use our model to simulate and analyze various scenarios, including cases for different degrees of knowledge diversity and cognitive distance among agents as well as knowledge exploitation vs. exploration strategies. Here, the model is able to distinguish between two levels of knowledge diversity: heterogeneity within and between agents. Additionally, our simulation results give fresh impetus to debates about the interplay of innovation network structure and knowledge diffusion. In summary, our article proposes a novel way of modeling knowledge diffusion, thereby contributing to an advancement of the economics of innovation and knowledge.     

Resource availability in the social cloud: An economics perspective

Social cloud has emerged as a case of sharing economy, where socially connected agents share their computing resources within the community. This paper considers the social cloud as an endogenous resource-sharing network, where agents are involved in closeness-based conditional resource sharing. This study focuses on (1) the impact of agents' decisions of link addition and deletion on their own local and global resource availability as well as on others' global resource availability (as spillover effects), (2) the role of agents' closeness in determining spillover effects, (3) agents' link addition behavior, and (4) stability and efficiency of the social cloud. The findings include the following: (i) Agents' decision of link addition (deletion) increases (decreases) their local resource availability. However, these observations do not hold in the case of global resource availability. (ii) In a connected network, agents experience either a positive or a negative spillover effect and there is no case with no spillover effects. Agents observe no spillover effects if and only if the network is disconnected with three or more components. Furthermore, an agent experiences negative spillover if there is no change in its closeness. Although an increase in the closeness of agents is necessary to experience positive spillover effects, the condition is not sufficient. (iii) We study the relation between agents' distance from each other, and their local as well as global resource availabilities. We prove that the local resource availability of an agent from another agent increases with decrease in the distance between them and that maximum local resource availability is obtained from the agent with the least closeness. Using these results, we discuss which agent to add a link to, so as to maximize the local resource availability. We discuss why such results are difficult to establish for global resource availability. However, in a two-diameter network, we show that for an agent, link formation always increases the global resource availability. (iv) We also study resource-sharing network formation and its efficiency in a strategic setting. We prove the existence of a pairwise stable network. Furthermore, we provide a set of conditions for a few prominent network structures (star, complete, wheel, and bipartite networks) to be pairwise stable. We show that the “connected in pairs, otherwise disconnected” network is better than a connected network, in terms of social welfare.     

Individual accountability in teams

We consider a model of team production in which the principal observes only the team output, but agents can monitor one another (at a cost) and provide reports to the principal. We consider the problem faced by a principal who is prevented from penalizing an agent without evidence showing that the agent failed to complete his assigned actions. We show the first-best (high effort but no monitoring) can be achieved, but only if the principal assigns second-best actions. The principal requires monitoring, but agents do not monitor, and as long as output is high, the principal does not penalize agents who fail to monitor. If the principal has the responsibility for monitoring, the first-best outcome cannot be achieved, thus we identify an incentive for delegated monitoring even when agents have no informational advantage.     

On the formation of interaction networks in social coordination games

There are many situations where two interacting individuals can benefit from coordinating their actions. We examine the endogenous choice of partners in such social coordination games and the implications for resulting play. We model the interaction pattern as a network where individuals periodically have the discretion to add or sever links to other players. With such endogenous interaction patterns we see multiple stochastically stable states of play, including some that involve play of equilibria in the coordination game that are neither efficient nor risk-dominant. Thus the endogenous network structure not only has implications for the interaction pattern that emerges, but it also has a significant impact on the play in the coordination game relative to what would arise if the same interaction network were exogenous.     

Coordination in evolving networks with endogenous decay

This paper studies an evolutionary model of network formation with endogenous decay, in which agents benefit both from direct and indirect connections. In addition to forming (costly) links, agents choose actions for a coordination game that determines the level of decay of each link. We address the issues of coordination (long-run equilibrium selection) and network formation by means of stochastic stability techniques. We find that the long-run behavior of the system depends on a fine interplay of the link cost and the trade-off between efficiency and risk-dominance.     

Social network and private provision of public goods

Using a simple model with interdependent utilities, we study how social networks influence individual voluntary contributions to the provision of a public good. Departing from the standard model of public good provision, we assume that an agent’s utility has two terms: (a) ‘ego’-utility derived from the agent’s consumption of public and private goods, and (b) a social utility which is the sum of utility spillovers from other agents with whom the agent has social relationships. We establish conditions for the existence of a unique interior Nash equilibrium and describe the equilibrium in terms of network characteristics. We show that social network always has a positive effect on the provision of the public good. We also find that, in networks with “small world”-like modular structures, ‘bridging’ ties connecting distant parts of social network play an important role inducing an agent’s contribution to public good. Assumptions and results of the model are discussed in relation to the role of social capital in community-level development projects and to the effect of innovation networks on firms’ R&D investments.