Evolutionary Change and Resilience in Industrial Districts: An Empirical Investigation Using Italian Firm-Level Data

Abstract

The aim of this project is to propose a methodological framework to interpret the evolutionary paths taken by the Italian industrial districts in the recent past, following the stimulus of two relevant phenomena associated with globalization: the international relocation of productive activities and the increasing presence of migrant entrepreneurs. The empirical analysis provides evidence to evaluate whether local firm populations are effectively exploiting the potential of these two forces to increase their resilience, intended as the ability to withstand and overcome an economic or structural shock. Italian districts have recently experienced a period of severe decline: this downturn is in part motivated by a diffused tendency towards lock-in dynamics and hysteresis, due to inadequate responsiveness to external changes and inability to adapt to unexpected shifts in the markets. In this gloomy context, global forces play a potential key role in increasing the internal stability of industrial district networks: however, local firm populations are required to foster a steady integration process, exploiting the opportunities arising from constant interactions with both global value chains and migrant firms. The economic literature states that when robust links with outsiders are effectively established, the internal structure of a local network can be reinforced, thus increasing the degree of diversity and avoiding lock-in dynamics associated with over-embeddedness. Italy is a particularly suitable setting in which to study this phenomenon, considering the key role played by industrial districts in driving domestic development and economic growth until the last decade. The empirical analysis is implemented on an innovative and comprehensive firm-level database including the great majority of micro and small firms operating in three manufacturing industries where the role of industrial districts is particularly relevant. Although these firms are generally excluded from most firm-level databases, they represent the core of most industrial district populations. The use of this database allows to focus the investigation on this relevant shaded area which has been ignored by previous empirical research. The evolutionary dynamics are evaluated by accounting for the heterogeneity existing between industrial districts: indeed, local systems are expected to differ over several structural characteristics potentially influencing the adaptive strategies implemented by the local firm populations. In this project, Italian industrial districts are identified using a revised version of the methodology proposed by Sforzi (2009): this new empirical tool allows to overcome the most relevant limitations of the original algorithm, generating a taxonomy that accounts for the heterogeneity of industrial districts. The use of this empirical tool allows the preliminary selection and classification of the areas on which the analysis is implemented. The empirical results of the research suggest that industrial district populations are generally not exploiting the potential of both passive and active internationalization forces, thus showing a general lack of flexibility: however, advanced forms of industrial districts appear to be more capable to integrate themselves in the global chains while retaining their links with the local networks. The macro-level analysis shows that although some evidence of a migration process towards evolved organizational systems exists, the great majority of industrial districts still appear to be locked into the traditional structures. The scope for top-down policy measures is limited, considering the self-organizing nature of these socio-economic entities: in most cases, the governance structure needs to be rearranged from the bottom in order to accommodate this evolving pattern.