Endogenous Peer Effects Research Articles

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 (2007) to estimate peer effects in a linear-in-means model. This approach allows to control for group-level unobservables and to solve the reflection problem. We investigate peer effects in student achievement in Mathematics, Science, French and History in Quebec secondary schools. We estimate the model using maximum likelihood and instrumental variables methods. We find evidence of peer effects. The endogenous peer effect is positive, when significant, and some contextual peer effects matter. Using calibrated Monte Carlo simulations, we find that high dispersion in group sizes helps with potential issues of weak identification.

Creating Social Contagion Through Viral Product Design: A Randomized Trial of Peer Influence in Networks

We examine how firms can create word-of-mouth peer influence and social contagion by designing viral features into their products and marketing campaigns. Word-of-mouth (WOM) is generally considered to be more effective at promoting product contagion when it is personalized and active. Unfortunately, the relative effectiveness of different viral features has not been quantified, nor has their effectiveness been definitively established, largely because of difficulties surrounding econometric identification of endogenous peer effects. We therefore designed a randomized field experiment on a popular social networking website to test the effectiveness of a range of viral messaging capabilities in creating peer influence and social contagion among the 1.4 million friends of 9,687 experimental users. Overall, we find that viral product design features can indeed generate econometrically identifiable peer influence and social contagion effects. More surprisingly, we find that passive-broadcast viral messaging generates a 246% increase in local peer influence and social contagion effects, while adding active-personalized viral messaging only generates an additional 98% increase in contagion. Although active-personalized messaging is more effective in encouraging adoption per message and is correlated with more user engagement and sustained product use, passive-broadcast messaging is used more often enough to eclipse those benefits, generating more total peer adoption in the network. In addition to estimating the effects of viral product design on social contagion and product diffusion, our work also provides a model for how randomized trials can be used to identify peer influence effects in networks.

How Important Are Endogenous Peer Effects in Group Lending? Estimating a Static Game of Incomplete Information

We quantify the importance of endogenous peer effects in group lending programs by estimating a static game of incomplete information. Endogenous peer effects describe how one's behavior is affected by the behavior of her peers. Using a rich data set from a group lending program in India, our empirical analysis presents a robust finding of large peer effects. The benchmark model suggests that the probability of a member making a full repayment would be 11 percentage points higher if all the fellow members were to make full repayment compared with a scenario in which none of the other members repay in full. We find that peer effects would be overestimated without controlling for unobserved group heterogeneity and that inconsistencies exist in the estimated effects of other variables without modeling peer effects and unobserved heterogeneity.

Weight gain in adolescents and their peers

Despite the urgent public health implications, relatively little is yet known about the effect of peers on adolescent weight gain. We describe trends and features of adolescent BMI in a nationally representative dataset and document correlations in weight gain among peers. We find strong correlations between own body mass index (BMI) and peers’ BMI's. Though the correlations are especially strong in the upper ends of the BMI distribution, the relationship is smooth and holds over almost the entire range of adolescent BMI. Furthermore, the results are robust to the inclusion of school fixed effects and basic controls for other confounding factors such as race, sex, and age. Some recent research in this area considers whether or not adolescent weight gain is caused by peers. We discuss the econometric issues in plausibly estimating such effects while accounting for growth spurts and difficulties in defining adolescent obesity. While our work identifies correlations between adolescent BMI and peers’ BMI, it is not intended to and cannot fully address the existence of endogenous peer effects.

Teenage dropouts and drug use: Does the specification of peer group structure matter?

Four alternative structures of peer groups are compared in an empirical analysis of teenage dropouts and recent drug use. In general, individual-specific covariates remain robust regardless of group structure specification in dropout models, but lose significance in models of drug-use. Estimates of correlated school effects depend on the specification of group structure. Contextual group effects have no influence on the probability that an individual uses drugs, but demonstrate some statistical significance, albeit ambiguous and strongly dependent on the specification of group structure. Endogenous peer effects do not influence the probability of dropping-out of school, but exhibit positive complementarities with respect to recent drug-use. Modeling the probabilities of leaving school and recent drug-use within a jointly distributed empirical framework indicates that unobserved attributes bridging the two types of behavior demonstrate positive correlation.

Estimating peer effects on health in social networks: A response to Cohen-Cole and Fletcher; and Trogdon, Nonnemaker, and Pais

In July of 2007, we published a paper in the New England Journal of Medicine that used dynamic data over 32 years from the Framingham Heart Study Social Network (FHS-Net) to study the conditions under which obesity might spread from person to person (Christakis and Fowler 2007, hereafter, CF). We found that obese persons formed clusters in the network at all time points and that these clusters extended to three degrees of separation (e.g., to a person’s friend’s friend’s friend). Moreover, statistical analyses suggested that the clusters were not solely attributable to the selective formation of social ties among obese persons. A person’s chances of becoming obese increased if he or she had a friend who became obese in a given time period. Our analyses were restricted to adults, so a natural question to ask is whether or not the results would generalize to a population of adolescents. The existence of social norms regarding weight in both adults and adolescents should not be surprising,(Chang and Christakis 2003) but, of course, causal inference in dyads, let alone in broader social networks, is difficult (Manski 1993). These questions are addressed by two papers in this issue, “Is Obesity Contagious? Social Networks versus Environmental Factors in the Obesity Epidemic,” by Ethan Cohen-Cole and Jason Fletcher (hereafter CCF) and “Peer Effects in Adolescent Overweight,” by Justin Trogdon, James Nonnemaker, and Joanne Pais (hereafter TNP), and by a third working paper “Identifying Endogenous Peer Effects in the Spread of Obesity” by Timothy J. Halliday and Sally Kwak (hereafter HK). All three of these papers analyze the same dataset and population, the National Longitudinal Study of Adolescent Health (Add Health), albeit with different methods and assumptions. Unlike the FHS-Net, which followed adults over a 32-year period (average age 38 in 1971), AddHealth followed adolescents over a 7-year period (average age 16 in 1995). All three sets of authors take the possibility of peer effects seriously, advancing the study of this important area. HK summarize their results by noting that they are able to replicate the pattern of results in our study, although their results are sensitive to specification of the dependent variable. If weight is characterized by a dichotomous variable indicating overweight (BMI>25), then an association between friends is significant, but the association in the continuous measure of BMI is not. Similarly, TNP use a variety of econometric strategies to conclude that there are peer effects for obesity in the Add Health sample, especially among females and among adolescents with high BMI. For example, they use an instrumental variables approach and a variety of definitions of endogenous peer groups to control for contextual effects. Here, we particularly address the CCF paper since it is the only one of the three papers that claims to reject the hypothesis that weight status can spread from person to person. To their credit, CCF exploit longitudinal data in a way that TNP and HK do not, but there are important problems in both their analysis and their interpretation of the results.

Peer Effects in Academic Cheating

Using self-reported academic honor violations from the classes of 1959 through 2002 at the three major U.S. military service academies (Air Force, Army, and Navy), we measure how peer honesty influences individual cheating behavior. All else equal, we find higher levels of peer cheating result in a substantially increased probability that an individual will cheat. We identify through separate estimation procedures an exogenous (contextual or pre-treatment) peer effect and an endogenous (during treatment) peer effect. Results for the (first-order) exogenous peer effect indicate that one additional high school cheater creates 0.33 to 0.48 new college cheaters. Results for the (first-order) endogenous peer effect indicate that one additional college cheater creates 0.55 to 0.80 new college cheaters. These results imply, in equilibrium, the social multiplier for academic cheating ranges between 2.20 to 4.90. We also find evidence that the peer effect should be thought of as an evolving social norm of toleration versus congestion in enforcement of honor codes.

What is a Peer? The Role of Network Definitions in Estimation of Endogenous Peer Effects

What is a Peer? The Role of Network Definitions in Estimation of Endogenous Peer Effects