The Role of Regional Labour Flow Networks for MNEs: The Made in Italy Case

Friday, June 24, 2016: 4:15 PM-5:45 PM
83 Dwinelle (Dwinelle Hall)
Mario Volpe, UniversitÓ di Venezia Ca' Foscari, Venice, Italy
Giancarlo Cor˛, Department of Economics, University of Venice, Venice, Italy
Shamnaaz Sufrauj, Department of Economics, University of Venice, Venice, Italy
Host-country and home-country effects of multinational entreprises (MNEs) are still on the agenda of both academics and policy-makers. The wage spillover effect and the foreign productivity spillover effects of MNEs on domestic firms has produced mixed results but overall productivity tends to improve around foreign-owned firms (Lipsey, 2004). Nevertheless, little emphasis has been paid on the reverse effect, in other words, the knowledge flowing from the industrial base of the host country to the MNEs.

One of the reason for the spatial configuration of economic activities is knowledge spillovers. As Keilbach (2012) argues, the process of knowledge spillover has a spatial dimension and lies behind the formation of industrial districts and clusters. The organisational learning literature, starting with the seminal work of Cohen and Levinthal (1990), stresses the capacity of units to absorb knowledge through investment in R&D. However, little research has been done on the conductor of such knowledge (Tsai, 2001).

The present research builds on the tenets that knowledge spills across firms through labour mobility in a network structure (Malmberg & Power, 2005). Knowledge gets embedded in workers through their qualifications and experience and when they transfer from one firm to another, they bring along their knowledge-base that may or may not be transferred to the firm. As such, workers are one of the main conduit of knowledge spillovers between firms. The aim of this research is to investigate whether access to a local labour pool of resources has a positive impact on firms’ performance (productivity) and whether MNEs access to such a knowledge pool contribute to their productivity. Similarly, it aims to assess whether MNEs are incubators of productive labour or not.

In order to achieve these aims, this research makes use of an intuitive model to analyse flow data, that is, a network model, already used to investigate international trade networks (Borgatti, Mehra, Brass, & Labianca, 2009). Understanding the structural properties of the labour flow network is useful to assess whether and which firms in a certain region have effective access to local resources and to assess the presence of hubs in a network. These network measures will be used in regression analysis to investigate the effects of the characteristics of the labour market on firms’ performance.

The Made in Italy sector will be the unit of analysis. This research uses recent data on labour movements inside the Venetian region that was drawn from the Osservatorio & Ricerca unit of the Veneto Lavoro Institute together with other publicly available data.

From a policy perspective, this research aims to shed light on the fluidity of the Venetian labour market. Debunking the topology of the labour network is important to understand how adaptive and resilient the system is: an issue that has been back on the agenda since the advent of the recent financial crisis that led to a number of structural reform. Moreover, understanding the role of MNEs in a such a system can better inform policy.