ABSTRACT. Spatial models whose weighting matrices have blocks of equal elements might be considered if units are viewed as equally distant within certain neighborhoods, but unrelated between neighborhoods. We give exact small sample results for such models that contain a spatially lagged-dependent variable. We consider cases in which the data relate to one or more panels, for example, villages, schools, etc. Our results are consistent with large sample results given in Kelejian and Prucha (2002) but indicate a variety of issues they did not consider. 1
First draft, do not quote! In this paper we argue that the Spatial Durbin Model (SDM) is an appropri...
Linear mixed models underpin many small area estimation (SAE) methods. In this paper we investigate ...
International audienceSpatial regression models rely on simultaneous autoregressive processes that m...
Although each variable in a spatial econometric model can have its own spatial weight matrix, practi...
This paper discusses estimation methods for models including an endogenous spatial lag, additional e...
The spatial lag specification is often used in spatial econometrics. The choice of an appropriate sp...
In this paper we study a family of linear regression models with spatial dependence in the errors an...
We propose an empirical application of lattice models to actual household-level data based on the ge...
While estimates of models with spatial interaction are very sensitive to the choice of spatial weigh...
This study investigates and quantifies the effect of different specifications of the spatial weights...
Spatial autocorrelation (more generally, spatial dependence) occurs when a regression's error term a...
We evaluate by means of Monte Carlo simulations the W-based spatial autoregressive model and the str...
We evaluate by means of Monte Carlo simulations the W-based spatial autoregressive model and the str...
This paper investigates the quasi-maximum likelihood (QML) estimation of spatial panel data models w...
A focus on location and spatial interaction has recently gained a more central place not only in ap...
First draft, do not quote! In this paper we argue that the Spatial Durbin Model (SDM) is an appropri...
Linear mixed models underpin many small area estimation (SAE) methods. In this paper we investigate ...
International audienceSpatial regression models rely on simultaneous autoregressive processes that m...
Although each variable in a spatial econometric model can have its own spatial weight matrix, practi...
This paper discusses estimation methods for models including an endogenous spatial lag, additional e...
The spatial lag specification is often used in spatial econometrics. The choice of an appropriate sp...
In this paper we study a family of linear regression models with spatial dependence in the errors an...
We propose an empirical application of lattice models to actual household-level data based on the ge...
While estimates of models with spatial interaction are very sensitive to the choice of spatial weigh...
This study investigates and quantifies the effect of different specifications of the spatial weights...
Spatial autocorrelation (more generally, spatial dependence) occurs when a regression's error term a...
We evaluate by means of Monte Carlo simulations the W-based spatial autoregressive model and the str...
We evaluate by means of Monte Carlo simulations the W-based spatial autoregressive model and the str...
This paper investigates the quasi-maximum likelihood (QML) estimation of spatial panel data models w...
A focus on location and spatial interaction has recently gained a more central place not only in ap...
First draft, do not quote! In this paper we argue that the Spatial Durbin Model (SDM) is an appropri...
Linear mixed models underpin many small area estimation (SAE) methods. In this paper we investigate ...
International audienceSpatial regression models rely on simultaneous autoregressive processes that m...