Spatial Econometrics is a branch of econometrics that focuses on the analysis of spatial data. It examines how economic activities and outcomes are influenced by their geographical locations and the relationships between different spatial units. This field helps researchers understand patterns and dependencies that arise due to proximity, such as how the economic performance of one region can affect neighboring areas. The methods used in Spatial Econometrics include spatial regression models and spatial autocorrelation techniques. These tools allow economists to account for the spatial structure in data, leading to more accurate predictions and insights. By incorporating spatial relationships, researchers can better analyze issues like regional development, urban planning, and environmental impacts.