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ESTIMATION PROBLEMS IN MODELS WITH SPATIAL WEIGHTING MATRICES WHICH HAVE BLOCKS OF EQUAL ELEMENTS
SPATIAL WEIGHTING MATRICES HAVE BLOCKS EQUAL ELEMENTS
2015/9/24
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 g...
INSTRUMENTAL VARIABLE ESTIMATION OF A SPATIAL AUTOREGRESSIVE MODEL WITH AUTOREGRESSIVE DISTURBANCES:LARGE AND SMALL SAMPLE RESULTS
INSTRUMENTAL VARIABLE ESTIMATION SPATIAL AUTOREGRESSIVE MODEL AUTOREGRESSIVE DISTURBANCES LARGE AND SMALL SAMPLE
2015/9/24
The purpose of this paper is two-fold. First, on a theoretical level we introduce a series-type instrumental variable (IV) estimator of the parameters of a spatial first order autoregressive model wit...
Estimation of simultaneous systems of spatially interrelated cross sectional equations
Spatial dependence Simultaneous equation system Two-stage least squares Three-stage least squares Generalized moments estimation
2015/9/24
In this paper we consider a simultaneous system of spatially interrelated cross sectional equations. Our speci.cation incorporates spatial lags in the endogenous and exogenous variables. In modelling ...
Panel data models with spatially correlated error components
Panel data model Spatial model Error component model
2015/9/24
In this paper we consider a panel data model with error components that are both spatially andtime-wise correlated. The model blends specifications typically considered in the spatial literaturewith t...
HAC estimation in a spatial framework
Heteroscedasticity and autocorrelation consistent (HAC) estimator Instrumental variable estimator Spatial models
2015/9/24
We suggest a non-parametric heteroscedasticity and autocorrelation consistent (HAC) estimator of the variance–covariance (VC) matrix for a vector of sample moments within a spatial context. Wedemonstr...
A SPATIAL CLIFF-ORD-TYPE MODEL WITH HETEROSKEDASTIC INNOVATIONS: SMALL AND LARGE SAMPLE RESULTS
SPATIAL CLIFF-ORD-TYPE MODEL HETEROSKEDASTIC INNOVATIONS SMALL AND LARGE SAMPLE RESULTS
2015/9/24
In this paper, we specify a linear Cliff-and-Ord-type spatial model. The model allows for spatial lags in the dependent variable, the exogenous variables, and disturbances. The innovations in the dist...
Spatial models with spatially lagged dependent variables and incomplete data
Spatial models Missing data Instrumental variable estimation
2015/9/24
The purpose of this paper is to suggest estimators for the parameters of spatial models containing a spatially lagged dependent variable, as well as spatially lagged independent variables, and an inco...
The relative efficiencies of various predictors in spatial econometric models containing spatial lags
Spatial models with spatial lags Optimal and suboptimal prediction efficiencies BLUP Kriging
2015/9/24
The purpose of this paper is to describe prediction efficiencies of various suboptimal predictors relative to the efficient (kriging) minimum mean square error predictor in spatial models containing s...
Central limit theorems and uniform laws of large numbers for arrays of random fields
Random field Spatial process Central limit theorem Uniform law of large numbers Law of large numbers
2015/9/24
Over the last decades, spatial-interaction models have been increasingly used in economics. However, the development of a sufficiently general asymptotic theory for nonlinear spatial models has been h...
Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances
Spatial dependence Heteroskedasticity Cliff–Ord model Two-stage least squares Generalized moments estimation Asymptotics
2015/9/24
This study develops a methodology of inference for a widely used Cliff–Ord type spatial model containing spatial lags in the dependent variable, exogenous variables, and the disturbance terms, while a...
Finite sample properties of estimators of spatial autoregressive models with autoregressive disturbances
Spatial autoregressive models ordinary least squares two-stage least squares maximum likelihood finite sample distribution
2015/9/24
The article investigates the finite sample properties of estimators for spatial autoregressive models where the disturbance terms may follow a spatial autoregressive process. In particular we investig...
2SLS and OLS in a spatial autoregressive model with equal spatial weights
Spatial autoregressive models Row normalized and equal spatial weights Ordinary least squares Two stage least squares Panel data
2015/9/24
The paper considers a Cliff–Ord type spatial model with a spatially lagged dependentvariable and a row normalized weighting matrix with equal weights. We show that the 2SLSand OLS estimators are incon...
On spatial processes and asymptotic inference under near-epoch dependence
Random fields Near-epoch dependent processes Central limit theorem Law of large numbers GMM estimator
2015/9/24
The development of a general inferential theory for nonlinear models with cross-sectionally or spatially dependent data has been hampered by a lack of appropriate limit theorems. To facilitate a gener...
Spatial spillovers in the development of institutions
Institutions Spatial econometrics Governance Neighborhood effects Spatial spillovers
2015/9/22
We examine spatial spillovers in institutional development. Dependent variables are institutional measures reflecting politics, law, and governmental administration. The explanatory variable of intere...
Obtaining Analytic Derivatives for a Class of Discrete-Choice Dynamic Programming Models
Analytic Derivatives Discrete-Choice Dynamic Programming Models
2015/9/18
This paper shows how to recursively calculate analytic first and second derivatives of the likelihood function generated by a popular version of a discrete-choice, dynamic programming model, allowing ...