This paper develops an estimator for higher-order spatial autoregressive panel data error component models with spatial autoregressive disturbances, SARAR(R,S). We derive the moment conditions and optimal weighting matrix without distributional assumptions for a generalized moments (GM) estimation procedure of the spatial autoregressive parameters of the disturbance process and define a generalized two-stage least squares estimator for the regression parameters of the model. We prove consistency of the proposed estimators, derive their joint asymptotic distribution, and provide Monte Carlo evidence on their small sample performance
This paper considers linear models with a spatial autoregressive error structure. Extending Arnold ...
This paper develops consistency and asymptotic normality of parameter estimates for a higher-order s...
One important goal of this study is to develop a methodology of inference for a widely used Cliff-Or...
This paper develops estimators for simultaneous equations with spatial autoregressive or spatial mov...
This thesis considers a dynamic panel data model with error components that are correlated both spat...
This paper considers a hierarchically spatial autoregressive and moving average error (HSEARMA) mode...
This dissertation consists of two essays on the estimation and inference for spatial economic models...
We develop refined inference for spatial regression models with predetermined regressors. The ordin...
This thesis considers a dynamic panel data model with error components that are correlated both spat...
This paper focuses on the estimation and predictive performance of several estimators for the dynami...
An electronic version of the paper may be downloaded • from the SSRN website: www.SSRN.com • ...
We examine a higher-order spatial autoregressive model with stochastic, but exogenous, spatial weigh...
I consider a panel vector-autoregressive model with cross-sectional dependence of the disturbances c...
This paper develops consistency and asymptotic normality of parameter estimates for a higher-order s...
We consider a spatial econometric model containing a spatial lag in the dependent variable and the d...
This paper considers linear models with a spatial autoregressive error structure. Extending Arnold ...
This paper develops consistency and asymptotic normality of parameter estimates for a higher-order s...
One important goal of this study is to develop a methodology of inference for a widely used Cliff-Or...
This paper develops estimators for simultaneous equations with spatial autoregressive or spatial mov...
This thesis considers a dynamic panel data model with error components that are correlated both spat...
This paper considers a hierarchically spatial autoregressive and moving average error (HSEARMA) mode...
This dissertation consists of two essays on the estimation and inference for spatial economic models...
We develop refined inference for spatial regression models with predetermined regressors. The ordin...
This thesis considers a dynamic panel data model with error components that are correlated both spat...
This paper focuses on the estimation and predictive performance of several estimators for the dynami...
An electronic version of the paper may be downloaded • from the SSRN website: www.SSRN.com • ...
We examine a higher-order spatial autoregressive model with stochastic, but exogenous, spatial weigh...
I consider a panel vector-autoregressive model with cross-sectional dependence of the disturbances c...
This paper develops consistency and asymptotic normality of parameter estimates for a higher-order s...
We consider a spatial econometric model containing a spatial lag in the dependent variable and the d...
This paper considers linear models with a spatial autoregressive error structure. Extending Arnold ...
This paper develops consistency and asymptotic normality of parameter estimates for a higher-order s...
One important goal of this study is to develop a methodology of inference for a widely used Cliff-Or...