Theoretical and empirical literature show that the geographic concentration of industry induces firms to vertically disintegrate their production, due to the lowering of transport and governance costs as well as to the reduction of opportunism in managing (complex) transactions. However, the evidence is primarily based on manufacturing firms, whereas little or no attention is given to service firms. In this paper we try to fill this gap by assessing the effects of different measures of spatial concentration on knowledge-intensive business service (KIBS) firms’ vertical disintegration within the local labour system (LLS) of Milan. Data are drawn from AIDA, a commercial database collected by Bureau Van Dijck and gathering information on balance sheets data as well as longitude and latitude of Italian joint stock companies. Relying on this rich firm-level dataset, we build a sample of almost 12.000 KIBS firms located in the LLS of Milan in year 2008. Operationally, we first geo-referenciate our data by employing a GIS routine. In this way, we identify the exact geographical position of each firm in the LLS. Then, we define a set of rings moving out of increments of 250 metres, and we count the number of firms located within each ring. For each firm, we compute, ring by ring, the number of neighbouring firms that are in the same three-digit industry, and the number of firms that are in all the three-digit industries except for the one in which the firm operates. In this way, we estimate the impact of proximity-based specialization Vs diversification economies on KIBS firms’ vertical disintegration, exploiting information on the actual distance between each pair of firms in the sample. As additional regressors, we also include firm age, size and squared size. Our dependent variable, instead, is calculated as the share of purchased business services over total production costs. This purchased-inputs variable allows accounting for the fact that “many business services are likely to be exactly the kind of locally produced intermediate input that producers in localized areas will have greater access to than producers in isolated areas” (Holmes 1999, p. 316).
KIBS and the city: vertical disintegration and urban density in Milan
ANTONIETTI, ROBERTO;CAINELLI, GIULIO
2011
Abstract
Theoretical and empirical literature show that the geographic concentration of industry induces firms to vertically disintegrate their production, due to the lowering of transport and governance costs as well as to the reduction of opportunism in managing (complex) transactions. However, the evidence is primarily based on manufacturing firms, whereas little or no attention is given to service firms. In this paper we try to fill this gap by assessing the effects of different measures of spatial concentration on knowledge-intensive business service (KIBS) firms’ vertical disintegration within the local labour system (LLS) of Milan. Data are drawn from AIDA, a commercial database collected by Bureau Van Dijck and gathering information on balance sheets data as well as longitude and latitude of Italian joint stock companies. Relying on this rich firm-level dataset, we build a sample of almost 12.000 KIBS firms located in the LLS of Milan in year 2008. Operationally, we first geo-referenciate our data by employing a GIS routine. In this way, we identify the exact geographical position of each firm in the LLS. Then, we define a set of rings moving out of increments of 250 metres, and we count the number of firms located within each ring. For each firm, we compute, ring by ring, the number of neighbouring firms that are in the same three-digit industry, and the number of firms that are in all the three-digit industries except for the one in which the firm operates. In this way, we estimate the impact of proximity-based specialization Vs diversification economies on KIBS firms’ vertical disintegration, exploiting information on the actual distance between each pair of firms in the sample. As additional regressors, we also include firm age, size and squared size. Our dependent variable, instead, is calculated as the share of purchased business services over total production costs. This purchased-inputs variable allows accounting for the fact that “many business services are likely to be exactly the kind of locally produced intermediate input that producers in localized areas will have greater access to than producers in isolated areas” (Holmes 1999, p. 316).Pubblicazioni consigliate
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