Using the Spatial Error Model to Study The Effect of Location on Rainfall in Iraq

Abstract

This study focuses on the utilization of spatial regression, which is a spatial analysis model that has garnered significant attention from researchers. In the past, statistical analysis has focused mostly on temporal data, ignoring the significance of studying the impact of location on the data. However, it has been discovered that disregarding the issue of spatial dependence might cause errors in research, leading to ineffective results when analyzing data. Unlike traditional regression models, spatial regression does not make the assumption that there is no self-correlation. It has been used to assess and investigate the relationship between the dependent and independent variables while considering the presence of spatial dependence, which is an inherent characteristic of spatial data. The spatial error model is a particular kind of parametric spatial regression model that will be the subject of this study. This model is concerned with investigating the spatial effects among the observed units of the phenomenon under study. We shall apply Moran's criterion to determine the existence of spatial effects.