We propose profile quasi-maximum likelihood estimation of spatial autoregressive models that are partially linear. The rate of convergence of the spatial parameter estimator depends on some general features of the spatial weight matrix of the model. The estimators of other finite-dimensional parameters in the model have the regular root n-rate of convergence and the estimator of the nonparametric component is consistent but with different restrictions on the choice of bandwidth parameter associated with different natures of the spatial weights. Monte Carlo simulations verify our theory and indicate that our estimators perform reasonably well in finite samples. (C) 2009 Elsevier B.V. All rights reserved.http://gateway.webofknowledge.com/gate...
The quasi-maximum likelihood estimator for the autoregressive parameter in a spatial autoregression...
Efficient semiparametric and parametric estimates are developed for a spatial autoregressive model, ...
This paper considers the problem of estimating a simultaneous spatial autoregressive model (SSAR). ...
We propose profile quasi-maximum likelihood estimation of spatial autoregressive models that are par...
We propose profile quasi-maximum likelihood estimation of spatial autoregressive models that are par...
This paper investigates asymptotic properties of the maximum likelihood estimator and the quasi-maxi...
Abstract The (quasi-) maximum likelihood estimator (MLE) for the autoregressive parameter in a spati...
In this paper, we address a class of heterogeneous spatial autoregressive models with all n(n−1) spa...
The (quasi-) maximum likelihood estimator (QMLE) for the autoregres-sive parameter in a spatial auto...
Su and Jin (2010) develop for partially linear spatial autoregressive (PL-SAR) model a profile quasi...
The (quasi-) maximum likelihood estimator (MLE) for the autoregressive parameter in a spatial autore...
This article deals with asymmetrical spatial data which can be modeled by a partially linear varying...
One simple, and often very effective, way to attenuate the impact of nuisance parameters on maximum ...
One simple, and often very effective, way to attenuate the impact of nuisance parameters on maximum ...
E ¢ cient semiparametric and parametric estimates are developed for a spatial autoregressive model, ...
The quasi-maximum likelihood estimator for the autoregressive parameter in a spatial autoregression...
Efficient semiparametric and parametric estimates are developed for a spatial autoregressive model, ...
This paper considers the problem of estimating a simultaneous spatial autoregressive model (SSAR). ...
We propose profile quasi-maximum likelihood estimation of spatial autoregressive models that are par...
We propose profile quasi-maximum likelihood estimation of spatial autoregressive models that are par...
This paper investigates asymptotic properties of the maximum likelihood estimator and the quasi-maxi...
Abstract The (quasi-) maximum likelihood estimator (MLE) for the autoregressive parameter in a spati...
In this paper, we address a class of heterogeneous spatial autoregressive models with all n(n−1) spa...
The (quasi-) maximum likelihood estimator (QMLE) for the autoregres-sive parameter in a spatial auto...
Su and Jin (2010) develop for partially linear spatial autoregressive (PL-SAR) model a profile quasi...
The (quasi-) maximum likelihood estimator (MLE) for the autoregressive parameter in a spatial autore...
This article deals with asymmetrical spatial data which can be modeled by a partially linear varying...
One simple, and often very effective, way to attenuate the impact of nuisance parameters on maximum ...
One simple, and often very effective, way to attenuate the impact of nuisance parameters on maximum ...
E ¢ cient semiparametric and parametric estimates are developed for a spatial autoregressive model, ...
The quasi-maximum likelihood estimator for the autoregressive parameter in a spatial autoregression...
Efficient semiparametric and parametric estimates are developed for a spatial autoregressive model, ...
This paper considers the problem of estimating a simultaneous spatial autoregressive model (SSAR). ...