Semiparametric Spatial Autoregressive Panel Data Model with Fixed Effects and Time-Varying Coefficients

This article considers a semiparametric spatial autoregressive (SAR) panel data model with fixed effects and time-varying coefficients. The coefficients are allowed to follow unknown functions of time, while the other parameters assumed be constants. We propose local linear quasi-maximum likelihood estimation method obtain consistent estimators for SAR coefficient, variance error term, nonparametric asymptotic properties proposed also established. Monte Carlo simulations conducted evaluate finite sample performance our method. apply study labor compensation in Chinese cities. results show significant dependence among cities impacts capital, investment, economy’s structure on change over time.