Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This paper extends the ML estimation of a spatial autoregressive Tobit model under normal disturbances in Xu and Lee (2015b, Journal of Econometrics) to distribution-free estimation. We examine the sieve MLE of the model, where the disturbances are i.i.d.with an unknown distribution. We show that the spatial autoregressive process with Tobit censoring and related variables are spatial near-epoch dependent (NED). A related contribution is that we develop some exponential inequalities for spatial NED random fields. With these inequalities, we establish the consistency of the estimator. Asymptotic distributions of structural parameters of the model are derived from a functional central limit theorem and projection.