Do Peers Affect Student Achievement? Evidence from Canada Using Group Size Variation

By V. Boucher, Yann Bramoullé, H. Djebbari, B. Fortin. Social Science Research Network, 2010

158 citations recorded by the source corpus.

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 Quebec (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.

Subfields: Education, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/429d63b890edfd8db14ae72dec3143637794087c

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Citations in the corpus

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Identification of Social Interactions (2011, methodology): “Brock and Durlauf (2006) additionally provide analogous results for general density functions for , i l ε ; as in the binary choice case the results are less precise. This Theorem and its generalization in Brock and Durlauf (2006) explain various simulation results in Bayer and Timmins (2005).”
The Economic Consequences of Social Network Structure (2017, unknown): “One way that this problem has been addressed in the literature (Bramoullé, Djebbari, and Fortin (2009); Calvó-Armengol, Patacchini and Zenou (2009); Boucher and Fortin (2016)) is to exploit the architecture of network contacts to construct instrumental variables for the social interaction effect. Si”
Young Adults Living with Their Parents and the Influence of Peers (2018, unknown): “8 See, for example, Hoxby (2000), Sacerdote (2001), Calvó-Armengol, Patacchini and Zenou (2009), Ohinata, and Van Ours (2013), and Boucher et al. (2014) for peer effects in educational outcomes, and Gaviria and Raphael (2001), Powell et al. (2005), Lundborg (2006), Clark and Lohéac (2007),…”