In this paper we consider a simultaneous system of spatially interrelated cross sectional equations. Our specification incorporates spatial lags in the endoge-nous and exogenous variables. In modelling the disturbance process we allow for both spatial correlation as well as correlation across equations. The data set is taken to be a single cross section of observations. The model may be viewed as an extension of the widely used single equation Cliff-Ord model. We suggest computationally simple limited and full information instrumental variable estimators for the parameters of the system and give formal large sample results. 1 Introduction1 Spatial models have attracted considerable interest in the recent economics and econometrics literatur...
In this paper, we consider a spatial-autoregressive model with autoregressive disturbances, where we...
Inherent to a spatial variable is the unit of support at which it is measured. In many studies, vari...
Abstract. Dynamic models have been studied intensively during the last decade, particularly in the f...
This paper develops estimators for simultaneous equations with spatial autoregressive or spatial mov...
Spatial dependence is one of the main problems in stochastic processes and can be caused by a variet...
We describe econometric techniques to treat spatial autocorrelation in multiequationcross-section mo...
We introduce the class of structural equation models (SEMs) and corresponding estimation procedures ...
This dissertation consists of two essays on the estimation and inference for spatial economic models...
Abstract. In spatial econometric models, autocorrelation among error terms is usually incorporated b...
This paper proposes a new spatial lag regression model which addresses global spatial autocorrelatio...
The first part of the dissertation introduces a new class of limited and full information GMM estima...
This thesis considers a dynamic panel data model with error components that are correlated both spat...
In this paper, we demonstrate the econometric consequences of different specification and estimation...
This paper develops estimators for simultaneous equations with spatial autoregressive or spatial mov...
This study develops a methodology of inference for a widely used Cliff-Ord type spatial model contai...
In this paper, we consider a spatial-autoregressive model with autoregressive disturbances, where we...
Inherent to a spatial variable is the unit of support at which it is measured. In many studies, vari...
Abstract. Dynamic models have been studied intensively during the last decade, particularly in the f...
This paper develops estimators for simultaneous equations with spatial autoregressive or spatial mov...
Spatial dependence is one of the main problems in stochastic processes and can be caused by a variet...
We describe econometric techniques to treat spatial autocorrelation in multiequationcross-section mo...
We introduce the class of structural equation models (SEMs) and corresponding estimation procedures ...
This dissertation consists of two essays on the estimation and inference for spatial economic models...
Abstract. In spatial econometric models, autocorrelation among error terms is usually incorporated b...
This paper proposes a new spatial lag regression model which addresses global spatial autocorrelatio...
The first part of the dissertation introduces a new class of limited and full information GMM estima...
This thesis considers a dynamic panel data model with error components that are correlated both spat...
In this paper, we demonstrate the econometric consequences of different specification and estimation...
This paper develops estimators for simultaneous equations with spatial autoregressive or spatial mov...
This study develops a methodology of inference for a widely used Cliff-Ord type spatial model contai...
In this paper, we consider a spatial-autoregressive model with autoregressive disturbances, where we...
Inherent to a spatial variable is the unit of support at which it is measured. In many studies, vari...
Abstract. Dynamic models have been studied intensively during the last decade, particularly in the f...