Alternative GMM estimators for spatial regression models. Issue 2 (3rd April 2018)

• Record Type: Journal Article
• Authors: Breitung, Jörg; Wigger, Christoph
• Is Part Of: Spatial economic analysis. Volume 13:Issue 2(2018)
• Page Start: 148
• Page End: 170
• Publication Date: 2018-04-03
• Subjects: spatial econometrics -- spatial error correlation -- generalized method of moments (GMM) estimation; C01 -- C13 -- C31; Space in economics -- Periodicals; Economic geography -- Periodicals; Space in economics -- Econometric models -- Periodicals; Urbanization -- Periodicals; Espace (Économie politique) -- Périodiques; Économétrie -- Périodiques; Géographie économique -- Périodiques; Économie industrielle -- Périodiques; Économie du travail -- Périodiques; Économie urbaine -- Périodiques; Politique économique -- Périodiques; Relations économiques internationales -- Périodiques; 330.9
• DOI: 10.1080/17421772.2018.1403644
• Languages: English
• ISSNs: 1742-1772

Abstract

ABSTRACT: 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 approach results in computationally simple and robust estimators, such as a new moment estimator derived from the first-order approximation obtained by solving a quadratic moment equation, and performs similarly to existing generalized method of moments (GMM) estimators. Our estimator based on the second-order approximation resembles the GMM estimator proposed by Kelejian and Prucha in 1999. Hence, we provide an intuitive interpretation of their estimator. Additionally, we provide a convenient framework for computing the weighting matrix of the optimal GMM estimator. Heteroskedasticity robust versions of our estimators are also proposed. Furthermore, a first-order approximation for the spatial autoregressive model is considered, resulting in a computationally simple method of moment estimator. The performance of the considered estimators is compared in a Monte Carlo study.