We propose a spatial autoregressive stochastic frontier model, which allows for the endogeneity in both the frontier and environmental variables (i.e., endogeneity due to correlation of inefficiency term and the two-sided error term). The model parameters are estimated using a single-stage control function approach. Monte Carlo simulations show that our proposed model and approach perform well in finite samples. We employed our methodology to the Chinese chemicals firm data and found evidence for both spatial effects and endogeneity.
Kutlu, Levent, Kien C. Tran, and Mike G. Tsionas. “A Spatial Stochastic Frontier Model with Endogenous Frontier and Environmental Variables.” European Journal of Operational Research 286, no. 1 (October 2020): 389–99. https://doi.org/10.1016/j.ejor.2020.03.020.
European Journal of Operational Research