Semiparametric Dynamic Logit Model with Endogenous Networks (opens in new tab)

This paper develops identification and estimation methods for dynamic partially linear logit models when social networks are endogenous and evolve over time. The outcome equation includes a lagged dependent variable and an unknown function of time-varying unobserved social characteristics that also govern link formation. Standard panel logit approaches, including those augmented with network controls, produce biased estimates when these latent t...