Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This paper develops a nonlinear spatial autoregressive model. Of particular interest is a structural interaction model for share data. We consider possible instrumental variable (IV) and maximum likelihood estimation (MLE) for this model, and analyze asymptotic properties of the IV and MLE based on the notion of spatial near-epoch dependence. We also design a statistical test to compare the nonlinear transformation against alternatives. Monte Carlo experiments are designed to investigate finite sample performance of the proposed estimates and the sizes and powers of the test.