A Tale of Many Cities : Industrial Networks and Urban Productivity

This paper examines how changes in urban industrial network structures explain the growth rates of labor productivity in cities. I formulate a multi-sector general equilibrium model with input-output networks of firms within a city and trade across cities. A key input to this framework is an entropy-style city network sparsity index. It serves as a concise summary of urban industrial structures and describes the concentration level of inputs for an average firm in a given city. The major theoretical result is that the improvement of urban industrial structures, indicated by an increase in city network sparsity, leads to an increase in the urban labor productivity growth rate. This is because changes in city network sparsity are results of both city-specific technological shocks and the evolution of the nationwide input-output structure. When these two forces align in a way that increases city network sparsity, production activities in a city become better organized, and its labor productivity grows faster. In MSA-level data from BEA, I verify the theory by showing that changes in network sparsity are positively correlated with a city's productivity growth. In two sets of counterfactuals, I demonstrate how the interaction between technology changes and urban industrial networks determine urban labor productivity. First, I find that the presence of urban industrial networks explains 54.7% of the variance in changes in urban labor productivity caused by local sectoral shocks. Second, I demonstrate that the variance in city network sparsity can explain 45.3% of the variance in growth rates of urban labor productivity caused by shifts in the national I-O structure