Estimation of a SAR model with endogenous spatial weights constructed by bilateral variables

This paper studies the estimation of a cross-sectional spatial autoregressive (SAR) model with spatial weights constructed by bilateral variables like the trade or investment between regions. We model the possible endogeneity in spatial weights due to the correlation between the error term in the SAR model and unobserved interactive fixed effects in bilateral variables. Using a control function approach, we propose two-stage estimation methods and establish their consistency and asymptotic normality. Finite sample properties are investigated by a Monte Carlo study. We further apply our method to an empirical study of interactions among different US industries through production networks. (c) 2020 Elsevier B.V. All rights reserved.

Automated summary

This paper examines the estimation of a cross-sectional spatial autoregressive model using spatial weights constructed by bilateral variables, tackling potential endogeneity issues through a control function approach. Two-stage estimation methods are proposed and their consistency and asymptotic normality are established, with finite sample properties explored through Monte Carlo studies. The method is further applied to an empirical study of interactions among different US industries through production networks.