Estimation of Fixed Effects Partially Linear Varying Coefficient Panel Data Regression Model with Nonseparable Space-Time Filters

Space-time panel data widely exist in many research fields such as economics, management, geography and environmental science. It is of interest to study the relationship between response variable regressors which come from above by establishing regression models. This paper introduces a new fixed effects partially linear varying coefficient model with nonseparable space-time filters. On basis approximating functions powerful B-spline method, profile quasi-maximum likelihood estimators parameters are constructed. Under some regular conditions, we derive their consistency asymptotic normality. Monte Carlo simulation shows that our estimates have good finite performance ignoring spatial serial correlations may lead inefficiency estimates. Finally, driving forces Chinese resident consumption rate studied using estimation method.