  This handbook chapter provides an essential introduction to the field of
spatial econometrics, offering a comprehensive overview of techniques and
methodologies for analysing spatial data in the social sciences. Spatial
econometrics addresses the unique challenges posed by spatially dependent
observations, where spatial relationships among data points can significantly
impact statistical analyses. The chapter begins by exploring the fundamental
concepts of spatial dependence and spatial autocorrelation, and highlighting
their implications for traditional econometric models. It then introduces a
range of spatial econometric models, particularly spatial lag, spatial error,
and spatial lag of X models, illustrating how these models accommodate spatial
relationships and yield accurate and insightful results about the underlying
spatial processes. The chapter provides an intuitive understanding of these
models compare to each other. A practical example on London house prices
demonstrates the application of spatial econometrics, emphasising its relevance
in uncovering hidden spatial patterns, addressing endogeneity, and providing
robust estimates in the presence of spatial dependence.
