Understanding Mechanisms Underlying Peer Effects: Evidence From a Field Experiment on Financial Decisions

Using a high‐stakes field experiment conducted with a financial brokerage, we implement a novel design to separately identify two channels of social influence in financial decisions, both widely studied theoretically. When someone purchases an asset, his peers may also want to purchase it, both because they learn from his choice (“social learning”) and because his possession of the asset directly affects others' utility of owning the same asset (“social utility”). We randomize whether one member of a peer pair who chose to purchase an asset has that choice implemented, thus randomizing his ability to possess the asset. Then, we randomize whether the second member of the pair: (i) receives no information about the first member, or (ii) is informed of the first member's desire to purchase the asset and the result of the randomization that determined possession. This allows us to estimate the effects of learning plus possession, and learning alone, relative to a (no information) control group. We find that both social learning and social utility channels have statistically and economically significant effects on investment decisions. Evidence from a follow‐up survey reveals that social learning effects are greatest when the first (second) investor is financially sophisticated (financially unsophisticated); investors report updating their beliefs about asset quality after learning about their peer's revealed preference; and, they report motivations consistent with “keeping up with the Joneses” when learning about their peer's possession of the asset. These results can help shed light on the mechanisms underlying herding behavior in financial markets and peer effects in consumption and investment decisions.     

Peer Pressure

We present a model where agents care about their neighbors' actions and can pressure them to take certain actions. Exerting pressure is costly for the exerting agent and it can impact the pressured agents by either lowering the cost of taking the action (which we call “positive pressure”) or else by raising the cost of not taking the action (which we call “negative pressure”). We show that when actions are strategic complements, agents with lower costs for taking an action pressure agents with higher costs, and that positive pressure can improve societal welfare. More generally, we detail who gains and who loses from peer pressure, and identify some circumstances under which pressure results in fully (Pareto) optimal outcomes as well as circumstances where it does not. We also point out differences between positive and negative pressure. (JEL: Z13, D62, C72, D85)     

Enhancing Self‐Protective Behavior: Efficacy Beliefs and Peer Feedback in Risk Communication

In times of a high‐impact safety incident citizens may have a variety of sources available to help them cope with the situation. This research focuses on the interplay of efficacy information in risk communication messages and peer feedback, such as responses on social network sites (SNSs) in the context of a high‐impact risk on the intention to engage in self‐protective behavior. The study pitted high and low efficacy information messages against supporting and opposing peer feedback (N = 242). Results show a significant interaction effect between efficacy information in a news article and peer feedback from SNS messages on both the intention to engage in self‐protective behavior and levels of involvement. Participants who received the article with more efficacy information and also received supportive peer feedback via SNS messages were more likely to express higher levels of involvement and greater intentions to engage in protective behavior. When confronted with a low efficacious news article, the effect of peer feedback on these two variables was significantly stronger. Finally, implications for theory and government risk communication are discussed.     

Matching and Network Effects

The matching of individuals in teams is a key element in the functioning of an economy. The network of social ties can potentially transmit important information on abilities and reputations and also help mitigate matching frictions by facilitating interactions among “screened” individuals. We conjecture that the probability of two individuals forming a team falls in the distance between the two individuals in the network of existing social ties. The objective of this paper is to empirically test this conjecture. We examine the formation of coauthor relations among economists over a twenty‐year period. Our principal finding is that a new collaboration emerges faster among two researchers if they are “closer” in the existing coauthor network among economists. This proximity effect on collaboration is strong: Being at a network distance of 2 instead of 3, for instance, raises the probability of initiating a collaboration by 27%. (JEL: C78, D83, D85)     

TRUST,COORDINATION, AND THE INDUSTRIAL ORGANIZATION OF POLITICAL ACTIVISM

We study political activism by several interest groups with private signals. When their ideological distance to the policymaker is small, a “low‐trust” regime prevails: agents frequently lobby even when it is unwarranted, taking advantage of the confirmation provided by others' activism; conversely, the policymaker responds only to generalized pressure. When ideological distance is large, a “high‐trust” regime prevails: lobbying behavior is disciplined by the potential contradiction from abstainers, and the policymaker's response threshold is correspondingly lower. Within some intermediate range, both equilibria coexist. We then study the optimal organization of influence activities, contrasting welfare levels when interest groups act independently and when they coordinate. (JEL: D72, D78, D82)     

From Natural Variation to Optimal Policy? The Importance of Endogenous Peer Group Formation

We take cohorts of entering freshmen at the United States Air Force Academy and assign half to peer groups designed to maximize the academic performance of the lowest ability students. Our assignment algorithm uses nonlinear peer effects estimates from the historical pre‐treatment data, in which students were randomly assigned to peer groups. We find a negative and significant treatment effect for the students we intended to help. We provide evidence that within our “optimally” designed peer groups, students avoided the peers with whom we intended them to interact and instead formed more homogeneous subgroups. These results illustrate how policies that manipulate peer groups for a desired social outcome can be confounded by changes in the endogenous patterns of social interactions within the group.     

DISCRETE CHOICE WITH SOCIAL INTERACTIONS AND ENDOGENOUS MEMBERSHIPS

This paper is about selection of neighbors in models of social interactions. I study a general equilibrium model of behavior subject to endogenous social influences when heterogeneous individuals can choose whom to associate with, buying associations on a “memberships market”. Social effects in behavior turn out to be a stratifying force: The desire for valuable interactions induces inefficient sorting and may lead to the endogenous emergence of “social traps”. The theory is then used to suggest identification strategies that may solve, in a micro‐founded way, identification and selection problems that typically affect empirical work on social interactions. Such strategies offer a viable alternative when valid instrumental variables or randomized experiments are not available. (JEL: C26, D85, Z13, Z19)     

The Dynamics of Inequality

The past forty years have seen a rapid rise in top income inequality in the United States. While there is a large number of existing theories of the Pareto tail of the long‐run income distributions, almost none of these address the fast rise in top inequality observed in the data. We show that standard theories, which build on a random growth mechanism, generate transition dynamics that are too slow relative to those observed in the data. We then suggest two parsimonious deviations from the canonical model that can explain such changes: “scale dependence” that may arise from changes in skill prices, and “type dependence,” that is, the presence of some “high‐growth types.” These deviations are consistent with theories in which the increase in top income inequality is driven by the rise of “superstar” entrepreneurs or managers.     

Optimal Pricing Strategies for Capacity Leasing Based on Time and Volume Usage in Telecommunication Networks

In this study, we examined optimal pricing strategies for “pay‐per‐time,” “pay‐per‐volume,” and “pay‐per‐both‐time‐and‐volume” based leasing of data networks in a monopoly environment. Conventionally, network capacity distribution includes short‐/long‐term bandwidth and/or usage time leasing. When customers choose connection‐time–based pricing, their rational behavior is to fully utilize the bandwidth capacity within a fixed time period, which may cause the network to burst (or overload). Conversely, when customers choose volume‐based strategies their rational behavior is to send only the minimum bytes necessary (even for time‐fixed tasks for real time applications), causing the quality of the task to decrease, which in turn creates an opportunity cost for the provider. Choosing a pay‐per time and volume hybridized pricing scheme allows customers to take advantage of both pricing strategies while lessening the disadvantages of each, because consumers generally have both time‐ and size‐fixed tasks such as batch data transactions. One of the key contributions of this study is to show that pay‐per both time and volume pricing is a viable and often preferable alternative to the offerings based on only time or volume, and that judicious use of such a pricing policy is profitable to the network provider.     

Keeping up with the Neighbors: Social Interaction in a Market Economy

We consider a world in which individuals have private endowments and trade in markets while their utility is negatively affected by the consumption of their neighbors. Our interest is in understanding how the social structure of comparisons, taken together with the familiar fundamentals of the economy (endowments, technology, and preferences), shapes equilibrium prices, allocations, and welfare. We show that equilibrium prices and consumption are a function of a single network statistic: centrality. An individual's “centrality” is given by the weighted sum of paths of different lengths to all others in a social network. In particular, prices are proportional to the sum of centralities, and an individual's consumption depends on how central she is relative to others in the network. Inequalities in wealth and connections reinforce each other in markets: A transfer of resources from less to more central agents raises prices. As segregated communities become integrated, the poor lose while the rich gain in utility! (JEL: D5, D6, D85)     

Consistency of Higher Order Risk Preferences

Risk aversion (a second‐order risk preference) is a time‐proven concept in economic models of choice under risk. More recently, the higher order risk preferences of prudence (third‐order) and temperance (fourth‐order) also have been shown to be quite important. While a majority of the population seems to exhibit both risk aversion and these higher order risk preferences, a significant minority does not. We show how both risk‐averse and risk‐loving behaviors might be generated by a simple type of basic lottery preference for either (1) combining “good” outcomes with “bad” ones, or (2) combining “good with good” and “bad with bad,” respectively. We further show that this dichotomy is fairly robust at explaining higher order risk attitudes in the laboratory. In addition to our own experimental evidence, we take a second look at the extant laboratory experiments that measure higher order risk preferences and we find a fair amount of support for this dichotomy. Our own experiment also is the first to look beyond fourth‐order risk preferences, and we examine risk attitudes at even higher orders.     

Strategic Learning and the Topology of Social Networks

We consider a group of strategic agents who must each repeatedly take one of two possible actions. They learn which of the two actions is preferable from initial private signals and by observing the actions of their neighbors in a social network. We show that the question of whether or not the agents learn efficiently depends on the topology of the social network. In particular, we identify a geometric “egalitarianism” condition on the social network that guarantees learning in infinite networks, or learning with high probability in large finite networks, in any equilibrium. We also give examples of nonegalitarian networks with equilibria in which learning fails.     

Coordination in Games with Strategic Complementarities: An Experiment on Fixed vs. Random Matching

In this article, we study behavior in a series of two‐player supply chain game experiments. Each player simultaneously chooses a capacity before demand is realized, and sales are given by the minimum of realized demand and chosen capacities. We focus on the differences in behavior under fixed pairs and random rematching. Intuition suggests that long‐run relations should lead to more profitable outcomes. However, our results go against this intuition. While subjects' capacity choices are better aligned (i.e., closer together) under fixed pairs, average profits are more variable. Moreover, learning is slower under fixed pairs—so much so that over the last five periods, average profits are actually higher under random rematching. The underlying cause for this finding appears to be a “first‐impressions” bias, present only under fixed matching, in which the greater the misalignment in initial choices, the lower are average profits.     

BIASES IN MACROECONOMIC FORECASTS: IRRATIONALITY OR ASYMMETRIC LOSS?

Empirical studies using survey data on expectations have frequently observed that forecasts are biased and have concluded that agents are not rational. We establish that existing rationality tests are not robust to even small deviations from symmetric loss and hence have little ability to tell whether the forecaster is irrational or the loss function is asymmetric. We quantify the trade‐off between forecast inefficiency and asymmetric loss leading to identical outcomes of standard rationality tests and explore new and more general methods for testing forecast rationality jointly with flexible families of loss functions that embed squared loss as a special case. Empirical applications to survey data on forecasts of real output growth and inflation suggest that rejections of rationality may largely have been driven by the assumption of squared loss. Moreover, our results suggest that agents are averse to “bad” outcomes such as lower‐than‐expected real output growth and higher‐than‐expected inflation and that they incorporate such loss aversion into their forecasts. (JEL: C22, C53, E37)     

Trick or Treat? An Examination of Marketing Relationships in a Nondeceptive Counterfeit Market

Who is most responsible for the proliferation of counterfeit goods—the illicit purveyor of such products or the consumer who procures them? This paper seeks to address this question by presenting a behavior analysis of counterfeit marketing firms in China and the interdependent relationships between legitimate retailers, consumers, and the authorities who populate these competitive environments. This is achieved via an operant interpretation of these key agents and the network of contingent relationships in operation. The results suggest that purveyors of pirate products function as “bad competitors” in the marketplace according to normative business behaviors—behaviors that are amenable to analysis in behavioral terms.     

Adaptive Local Polynomial Whittle Estimation of Long‐range Dependence

The local Whittle (or Gaussian semiparametric) estimator of long range dependence, proposed by Künsch (1987) and analyzed by Robinson (1995a), has a relatively slow rate of convergence and a finite sample bias that can be large. In this paper, we generalize the local Whittle estimator to circumvent these problems. Instead of approximating the short‐run component of the spectrum, ϕ(λ) , by a constant in a shrinking neighborhood of frequency zero, we approximate its logarithm by a polynomial. This leads to a “local polynomial Whittle” (LPW) estimator. We specify a data‐dependent adaptive procedure that adjusts the degree of the polynomial to the smoothness of ϕ(λ) at zero and selects the bandwidth. The resulting “adaptive LPW” estimator is shown to achieve the optimal rate of convergence, which depends on the smoothness of ϕ(λ) at zero, up to a logarithmic factor.     

Supply Networks as a Complex Adaptive System: Toward Simulation‐Based Theory Building on Evolutionary Decision Making

In this article, we examine how the firms embedded in supply networks engage in decision making over time. The supply networks as a complex adaptive system are simulated using cellular automata (CA) through a dynamic evolution of cooperation (i.e., “voice” decision) and defection (i.e., “exit” decision) among supply network agents (i.e., firms). Simple local rules of interaction among firms generate complex patterns of cooperation and defection decisions in the supply network. The incentive schemes underlying decision making are derived through different configurations of the payoff‐matrix based on the game theory argument. The prisoner's dilemma game allows capturing the localized decision‐making process by rational agents, and the CA model allows the self‐organizing outcome to emerge. By observing the evolution of decision making by cooperating and defecting agents, we offer testable propositions regarding relationship development and distributed nature of governance mechanisms for managing supply networks.     

Broadband Network Management and the Net Neutrality Debate

The debate of net neutrality and the potential regulation of net neutrality may fundamentally change the dynamics of data consumption and transmission through the Internet. The existing literature on economics of net neutrality focuses only on the supply side of the market, that is, a broadband service provider (BSP) may charge content providers for priority delivery of their content to consumers. In this article, we explore a complete spectrum of broadband network management options based on both the supply and demand sides of the market. We find that although the BSP always prefers the non‐neutral network management options, it does not always discriminate both sides of the market. From the social planner's perspective, we find that some network management options maximize the social welfare under certain market conditions while other options reduce the social welfare. Using the terminology from a recent Federal Communications Commission report and order, we categorize the social welfare maximizing options as “reasonable network management” and the social welfare reducing options as “unreasonable discrimination.” We also identify conditions under which the BSP's network management choices deviate from the social optimum. These conditions help establish the criteria under which the social planner might wish to regulate the BSP's actions.     

Quality of Service Based Pricing Schemes for Content Sharing in Peer‐to‐Peer Networks

In this paper, we study quality‐of‐service (QoS) based pricing schemes that serve as incentive mechanisms to induce sharing behaviors in Peer‐to‐Peer (P2P) networks. We incorporate operational QoS metrics into users’ utility functions and demonstrate how they affect individual users’ content sharing decisions. Using a game‐theoretic model, our study reveals how organizations respond to the changes of operational QoS metrics in their design of pricing schemes for various business objectives at different stages of network evolution. Our results show that a higher upload capacity can foster rational sharing to start when the network is small; however, it also discourages sharing behaviors when the network becomes large. In order to induce a socially optimal behavior, a pricing scheme will not charge users for requesting content while compensating them for sharing content. Such compensation is found to increase faster with the network size when the network is large. In order to maximize the profit of a monopolistic provider, however, a pricing scheme will charge content requests with a positive price while providing less compensation to sharing users compared to the socially optimal scheme. When the network size is small, such compensation can be even negative, which implies that a monopolistic provider discourages content sharing when the network is small, but encourages it when the network becomes larger. In addition, we find that more information about peer upload capacity discourages peers to share.     

企业数字化转型的同群效应及其影响因素研究

以2008~2019年中国A股制造业上市公司数据为基础,通过分析师跟踪网络识别同群群体,并利用面板固定效应模型等方法,考察企业数字化转型中的同群效应以及这种企业间行为互动的影响因素。研究发现:企业数字化转型过程中存在显著的同群效应;受模仿学习的主观动机与现实条件两方面因素共同影响,数字化转型的同群效应在资源基础和动态能力处于中间水平的企业中更为显著;网络嵌入、市场竞争以及环境不确定性均会强化企业数字化转型的同群效应;同群效应引发了群体成员数字化转型水平的向上趋同。