GMM estimators for binary spatial models in R

G Piras, M Sarrias - Journal of Statistical Software, 2023 - jstatsoft.org
Journal of Statistical Software, 2023jstatsoft.org
Despite the huge availability of software to estimate cross-sectional spatial models, there are
only few functions to estimate models dealing with spatial limited dependent variable. This
paper fills this gap introducing the new R package spldv. The package is based on
generalized methods of moment (GMM) estimators and includes a series of one-and two-
step estimators based on different choices of the weighting matrix for the moments
conditions in the first step, and different estimators for the variance-covariance matrix of the …
Abstract
Despite the huge availability of software to estimate cross-sectional spatial models, there are only few functions to estimate models dealing with spatial limited dependent variable. This paper fills this gap introducing the new R package spldv. The package is based on generalized methods of moment (GMM) estimators and includes a series of one-and two-step estimators based on different choices of the weighting matrix for the moments conditions in the first step, and different estimators for the variance-covariance matrix of the estimated coefficients. An important feature of spldv is that users can estimate the spatial Durbin model and compute the direct, indirect, and total effects in a friendly and flexible way.
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