The observed uneven distribution of economic activity across space is influenced by variation in exogenous geographical characteristics and endogenous interactions between agents in goods and factor markets. Until the past decade, the theoretical literature on economic geography had focused on stylized settings that could not easily be taken to the data. This article reviews more recent research that has developed quantitative models of economic geography. These models are rich enough to speak to first-order features of the data, such as many heterogeneous locations and gravity equation relationships for trade and commuting. At the same time, these models are sufficiently tractable to undertake realistic counterfactual exercises to study the effect of changes in amenities, productivity, and public policy interventions such as transport infrastructure investments. We provide an extensive taxonomy of the different building blocks of these quantitative spatial models and discuss their main properties and quantification.


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