Heteroskedasticity-robust semi-parametric GMM estimation of a spatial model with space-
varying coefficients. Spatial Economic Analysis. The spatial model with space-varying …

ABSTRACT Raising the bar (5). Spatial Economic Analysis. This editorial summarizes and
comments on the papers published in this issue 12 (1) so as to raise the bar in applied …

We consider a spatial econometric model containing a spatial lag in the dependent variable
and the disturbance term with an unknown form of heteroskedasticity in innovations. We first …

In this study, we investigate the finite sample properties of the optimal generalized method of
moments estimator (OGMME) for a spatial econometric model with a first-order spatial …

We apply local linear regression and sieve estimation technique to estimate functional
coefficients and an unknown spatial weighting function, respectively, via a nonparametric …

Spatial data are widely used in various scenarios of life and are highly valued, and their
analysis and research have achieved remarkable results. Spatial data have spatial effects …

We propose semiparametric GMM estimation of semiparametric spatial autoregressive
(SAR) models under weak moment conditions. In comparison with the quasi-maximum …

Using approximations of the score of the log-likelihood function, we derive moment
conditions for estimating spatial regression models, starting with the spatial error model. Our …

This paper considers a flexible semiparametric spatial autoregressive (mixed-regressive)
model in which unknown coefficients are permitted to be nonparametric functions of some …

This paper proposes a semiparametric generalized method of moments estimator (GMM)
estimator for a partially parametric spatial model with endogenous spatially dependent …