This paper derives the LIML estimator for a spatial autoregressive model with endogenous regressors in the presence of many instruments. The LIML estimator is consistent when the number of instruments increases at a slower rate relative to the sample size. Due to spatial correlation, the LIML...

This work considers the estimation of a network model with sampled networks. Chandrasekhar and Lewis (2011) show that the estimation with sampled networks could be biased due to measurement error induced by sampling and propose a bias correction by restricting the estimation to sampled nodes to...