This review brings together current advances in spatial economics, focusing on quantitative models and statistical approaches for assessing the distribution of economic activity in urban and regional systems. The essay combines classical theory with modern empirical methodologies, such as spatial econometrics, GIS-based research, and machine learning, to highlight advances in assessing agglomeration, market access, and infrastructural benefits. Significant methodological obstacles, such as geographic autocorrelation and high-dimensional data, are addressed using new strategies. The review looks at policy applications relevant to urban planners, geographers, and economists, including place-based interventions, transportation investments, and regional development strategies. This article aims to be a comprehensive resource for scholars and practitioners studying spatial patterns and processes in the built environment via the lens of economics, geography, and data science.
Mahshid Gorjian (Wed,) studied this question.