Agglomeration: A Long-Run Panel Data Approach

PWP-CCPR-2016-018

Abstract

This paper studies the sources of agglomeration economies in cities. We begin by incorporating within and cross-industry spillovers into a dynamic spatial equilibrium model in order to obtain a panel data estimating equation. This gives us a framework for measuring a rich set of agglomeration forces while controlling for a variety of potentially confounding effects. We apply this es- timation strategy to detailed new data describing the industry composition of 31 English cities from 1851-1911. Our results show that industries grew more rapidly in cities where they had more local suppliers or other occupationally- similar industries. We find no evidence of dynamic within-industry effects, i.e., industries generally did not grow more rapidly in cities in which they were al- ready large. Once we control for these agglomeration forces, we find evidence of strong dynamic congestion forces related to city size. We also show how to construct estimates of the combined strength of the many agglomeration forces in our model. These results suggest a lower bound estimate of the strength of agglomeration forces equivalent to a city-size divergence rate of 1.0-2.3% per decade.