Edited by David B. Audretsch, Oliver Falck, Stephan Heblich and Adam Lederer
Chapter 11: Innovation in Cities: Classical and Random Urban Growth Models
Gilles Duranton It was an honour to have my paper ‘Nursery cities’ (Duranton and Puga, 2001), republished in a recent Edward Elgar Reference Collection, edited by the editors of this volume. That paper attempts to make a connection between the literature on growth and innovation and urban economics. More precisely, it uses a model of process innovation through experimentation to derive a number of implications about the urban landscape. The insights delivered by this model shed light on a variety of stylized facts about cities and how they link with economic growth. However, the approach taken in nursery cities and much of the ‘classical’ urban growth literature does not square well with a wellknown regularity about the size distribution of cities. Namely, the size of cities appears to be well approximated by a Pareto distribution with exponent minus one. Recently, another literature developed to generate this type of distribution from well-articulated economic models. This literature proposes a radically different modelling approach to urban growth. It highlights randomness and granularity in the urban growth process whereas the classical literature views urban growth as smooth and deterministic. The object of this chapter is first to clarify the tension between the classical urban growth literature vis-à-vis random growth models and, second, to explore to what extent these approaches are compatible. NURSERY CITIES AND CLASSICAL URBAN GROWTH MODELS The model of Duranton and Puga (2001) can be summarized as follows. Entrepreneurs can introduce new products by paying a fixed cost of entry. At...
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