Identification Of Peer Effects Research Articles

An examination of peer effects using high school competition realignments

This study reports improvements for high school swimmers reassigned to higher competitive classifications compared to swimmers remaining in the same classification in consecutive seasons as transmitted through changes in peer quality and ordinal ranking. The enrollment criterion adopted by high school athletic associations in the United States for the designation of competitive classifications provides plausibly exogenous assignments to environments of varying competition levels for better identification of peer effects. Evidence of responses that vary by stroke complexity may motivate future research to investigate the applicability of the findings to settings with similar levels of task heterogeneity.

Identification of Peer Effects using Panel Data

This paper provides new identification results for panel data models with contextual and endogenous peer effects, respectively operating through individual heterogeneity and outcomes. The results apply for general network structures governing peer interactions, and hinge on a conditional mean restriction requiring exogenous mobility of individuals between groups over time. Some networks preclude identification, in which case we propose additional conditional variance restrictions. We apply our method to surgeon-hospital-year data to study take-up of keyhole surgery, finding a positive effect of the average individual heterogeneity of peers. This effect is equally due to endogenous and contextual effects.

Peer Effects in Central Banking

We provide a new explanation for why central banks have become transparent over the last three decades. We apply recently developed social interaction panel regression models for the observational data, which allow the identification of peer effects. The identification is based on variations in the past monetary policy regime exogenously determined with respect to transparency. Previous literature has argued that domestic factors such as macroeconomic stability were behind the trend toward greater transparency. In contrast, our results indicate that transparency primarily increased because of a favorable global environment and, importantly, because of the peer effects among central bankers. Central bankers thus learned from each other’s experiences regarding transparency.

Identification of peer effects through social networks using variance restrictions

This paper presents a novel method to identify peer effects through exploiting fluctuations in the variances and covariances of outcomes over a social network. Endogenous and contextual peer effects can be disentangled by contrasting the covariances of the outcomes of peers with the covariances of the outcomes of peers of peers. Correlated effects are incorporated by allowing for unrestricted network level heterogeneity. The method is applied to the Project STAR data to study peer effects in academic attainment of first-year kindergarten students. Evidence is found of positive peer effects, which are statistically significant and consistent with the existing literature.

Identification of peer effects via a root estimator

By exploiting the correlation structure of individual outcomes in a network, we show that a carefully constructed root estimator can identify peer effects in linear social interaction models, when identification cannot be achieved via variation of group sizes or intransitivity of network connections. We establish the consistency and asymptotic normality of the root estimator under heteroskedasticity, and conduct Monte Carlo experiments to investigate its finite sample performance.

Avatars as Peers at Work: An Experimental Study in Virtual Reality

Identification of peer effects is often complicated by the reflection problem: Does agent i influence agent j, or vice versa? To be able to identify a clear causality, we embed a virtual human (avatar) as co-worker of a human subject into an immersive virtual environment. We observe that low productive human subjects increase their work performance more when they observe a low productive avatar – compared to a high productive avatar. This result is in line with the predictions of the social comparison theory, in as much as we observe stronger peer effects when the perceived similarity in abilities between the peers is high.

Peer Effects in Parental Leave Decisions

This paper analyzes to what extent parental leave decisions of mothers with young children depend on the decisions made by their coworkers. The identification of peer effects, which are defined as indirect effects of the behavior of a social reference group on individual outcomes, bears various challenges due to correlated characteristics within social groups and endogenous group membership. We overcome these challenges by exploiting quasi-random variation in the costs of parental leave during a narrow window around a cutoff date, induced by a parental leave benefit reform in Germany. The reform encourages mothers to remain at home during the first year following childbirth. Administrative linked employer-employee panel data enable us to assign a peer group to all individuals who work in the same establishment and occupational group. While there is a growing literature on peer effects, few studies look at peer effects in the context of parental leave decisions. We argue, however, that mothers with young children are particularly susceptible to peer behavior at the workplace due to preferences for conformity with peer group behavior as well as the career-related uncertainty that mothers face. Our results suggest that maternal decisions regarding the length of parental leave are significantly influenced by coworker decisions, in particular in situations with high uncertainty.

Peer effects in risk aversion.

We estimate peer effects in risk attitudes in a sample of high school students. Relative risk aversion is elicited from surveys administered at school. Identification of peer effects is based on parents not being able to choose the class within the school of their choice, and on the use of instrumental variables conditional on school-grade fixed effects. We find a significant and quantitatively large impact of peers' risk attitudes on a male individual's coefficient of risk aversion. Specifically, a one standard deviation increase in the group's coefficient of risk aversion increases an individual's risk aversion by 43%. Our findings shed light on the origin and stability of risk attitudes and, more generally, on the determinants of economic preferences.

Social Networks and the Identification of Peer Effects

There is a large and growing literature on peer effects in economics. In the current article, we focus on a Manski-type linear-in-means model that has proved to be popular in empirical work. We critically examine some aspects of the statistical model that may be restrictive in empirical analyses. Specifically, we focus on three aspects. First, we examine the endogeneity of the network or peer groups. Second, we investigate simultaneously alternative definitions of links and the possibility of peer effects arising through multiple networks. Third, we highlight the representation of the traditional linear-in-means model as an autoregressive model, and contrast it with an alternative moving-average model, where the correlation between unconnected individuals who are indirectly connected is limited. Using data on friendship networks from the Add Health dataset, we illustrate the empirical relevance of these ideas.

DO PEERS AFFECT STUDENT ACHIEVEMENT? EVIDENCE FROM CANADA USING GROUP SIZE VARIATION

We provide the first empirical application of a new approach proposed by Lee (Journal of Econometrics 2007; 140(2), 333–374) to estimate peer effects in a linear-in-means model when individuals interact in groups. Assumingsufficient group size variation, this approach allows to control for correlated effects at the group level and to solve the simultaneity (reflection) problem. We clarify the intuition behind identification of peer effects in the model. We investigate peer effects in student achievement in French, Science, Mathematics and History in secondary schools in the Province of Québec (Canada). We estimate the model using conditional maximum likelihood and instrumental variables methods. We find some evidence of peer effects. The endogenous peer effect is large and significant in Mathematics but imprecisely estimated in the other subjects. Some contextual peer effects are also significant. In particular, for most subjects, the average age of peers has a negative effect on own test score. Using calibrated Monte Carlo simulations, we find that high dispersion in group sizes helps with potential issues of weak identification. Copyright © 2012 John Wiley & Sons, Ltd.

Identification of Peer Effects with Missing Peer Data: Evidence from Project Star

This paper studies peer effects on student achievement among first graders randomly assigned to classrooms in Tennessee’s Project STAR. The analysis uses previously unexploited pre-assignment achievement measures available for 60 percent of students. Data are not missing at random, making identification challenging. The paper develops new ways, given random assignment of individuals to classes, to identify peer effects without imposing other missing-data assumptions. Estimates suggest positive effects of mean peer lagged achievement on average. Allowing heterogeneous effects, evidence suggests lower-achieving students benefit more than higher-achieving students do from increases in peer mean. Further, the bias in a widely used, poorly understood peer-effects estimator is analyzed, implying that caution is warranted in interpreting many peer-effects estimates extant in the literature.

Identification of peer effects using group size variation

Summary This paper studies the econometric properties of a linear-in-means model of social interactions. Under a slightly more restrictive framework than Lee (2007), we show that this model is generally identified when at least three different sizes of peer groups are observed in the sample at hand. While unnecessary in general, homoscedasticity may be required in special cases, for instance when endogenous and exogenous peer effects cancel each other. We extend this analysis to the case where only binary outcomes are observed. Once more, most parameters are semiparametrically identified under weak conditions. However, identifying all of them requires more stringent assumptions, including a homoscedasticity condition. We also develop a parametric estimator for the binary case, which relies on the Geweke-Hajivassiliou-Keane (GHK) simulator. Monte Carlo simulations illustrate the influence of group sizes on the accuracy of the estimation, in line with the results obtained by Lee (2007).

Identification of peer effects through social networks

We provide new results regarding the identification of peer effects. We consider an extended version of the linear-in-means model where interactions are structured through a social network. We assume that correlated unobservables are either absent, or treated as network fixed effects. We provide easy-to-check necessary and sufficient conditions for identification. We show that endogenous and exogenous effects are generally identified under network interaction, although identification may fail for some particular structures. We use data from the Add Health survey to provide an empirical application of our results on the consumption of recreational services ( e.g. , participation in artistic, sports and social activities) by secondary school students. Monte Carlo simulations calibrated on this application provide an analysis of the effects of some crucial characteristics of a network ( i.e., density, intransitivity) on the estimates of peer effects. Our approach generalizes a number of previous results due to Manski [Manski, C., 1993. Identification of endogenous social effects: The reflection problem. Review of Economic Studies 60 (3), 531–542], Moffitt [Moffitt, R., 2001. Policy interventions low-level equilibria, and social interactions. In: Durlauf, Steven, Young, Peyton (Eds.), Social Dynamics. MIT Press] and Lee [Lee, L.F., 2007. Identification and estimation of econometric models with group interactions, contextual factors and fixed effects. Journal of Econometrics 140 (2), 333–374].

Identification of Peer Effects through Social Networks

We provide new results regarding the identification of peer effects. We consider an extended version of the linear-in-means model where each individual has his own specific reference group. Interactions are thus structured through a social network. We assume that correlated unobservables are either absent, or treated as fixed effects at the component level. In both cases, we provide easy-to-check necessary and sufficient conditions for identification. We show that endogenous and exogenous effects are generally identified under network interaction, although identification may fail for some particular structures. Monte Carlo simulations provide an analysis of the effects of some crucial characteristics of a network (i.e., density, intransitivity) on the estimates of social effects. Our approach generalizes a number of previous results due to Manski (1993), Moffitt (2001), and Lee (2006).

Identification of Peer Effects Using Group Size Variation

This paper considers the semiparametric identification of endogenous and exogenous peer effects based on group size variation. We show that Lee (2006)’s linear-in-means model is generically identified, even when all members of the group are not observed. While unnecessary in general, homoskedasticity may be required in special cases to recover all parameters. Extensions to asymmetric responses to peers and binary outcomes are also considered. Once more, most parameters are semiparametrically identified under weak conditions. However, recovering all of them requires more stringent assumptions. Eventually, we bring theoretical evidence that the model is more adapted to small groups.