Letters in Economic Research Updates
Spatial Econometrics Models Applied to Environmental Pollution. A Systematic Review
Abstract
Manuel Canaveral, Juliano Marangoni, Leonardo Emmendorfer and Cassius Oliveira
The interest in spatial analysis has been growing in recent years, mainly due to communication technology advances, economic globalization, and the development of new statistical methods and computational tools. This article aims to contribute to the dissemination of spatial statistical models applied in econometrics, by presenting some basic theoretical aspects and a literature review of articles that address the socio-economic drivers that lead to environmental pollution. Three spatial regression models are reviewed here: the spatial lag model (SLM) also known in the literature as SAR, the spatial error model (SEM), and the spatial Durbin model (SDM). A literature search was conducted using specific terms of interest in eight databases, from 1996 to February 2021, where 22 articles were considered for analysis. The results showed that most articles studied environmental problems in China. The most used exploratory spatial analysis model was Moran Index and the most used explanatory spatial analysis models were SDM and SLM.