|LEM Working Paper Series
Modeling Industrial Evolution in Geographical Space
Giulio Bottazzi, Giovanni Dosi, Giorgio Fagiolo, Angelo Secchi
Industrial Location, Agglomeration, Dynamic Increasing Returns, Markov Chains, Polya Urns.
C1, L6, R1
In this paper we study a class of evolutionary models of industrial agglomeration with local positive feedbacks, which allow for a wide set of empirically-testable implications. Their roots rest in the Generalized Polya Urn framework. Here, however, we build on a birth-death process over a finite number of locations and a finite population of firms. The process of selection among production sites that are heterogeneous in their ?intrinsic attractiveness? occurs under a regime of dynamic increasing returns depending on the number of firms already present in each location. The general model is presented together with a few examples of small economies which help to illustrate the properties of the model and characterize its asymptotic behavior. Finally, we discuss a number of empirical applications of our theoretical framework. The basic model, once taken to the data, is able to empirically disentangle the relative strength of technologically-specific agglomeration drivers (affecting differently firms belonging to different industrial sectors in each location) from site-specific geographical forces (horizontally acting upon all sectors in each location).