Abstract:
In this paper, we model network formation and network interactions under a unified framework.
The key feature of our model is to allow individuals to respond to incentives stemming
from interaction benefits on certain activities when they are choosing friends (network links).
There are two advantages of this modeling approach: first, one can evaluate whether incentives
from certain interactions are important factors for friendship formation or not. Second,
possible friendship selection bias on network interactions can be corrected as the network
formation is explicitly modeled. The proposed model is estimated by the Bayesian method.
In the empirical study, we apply the model to American high school students' friendship
networks in the Add Health dataset. From two activity variables which are considered in the
paper -- GPA and smoking frequency, we find a significant incentive effect from GPA, but not
from smoking, on friendship formation. These results suggest that the benefit of interactions
in academic learning is an important factor for forming friendships, while the pleasure of
smoking together is not. However, from the perspective of network interactions, both GPA
and smoking frequency are subject to significant positive interaction (peer) effects.
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