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.

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