Production structure, infrastructures, and knowledge spillovers: What drives FDI inflows?

Although Foreign Direct Investment (FDI) inflows into Europe have substantially grown over the last decade, Italian regions account for a very small portion of such increase; moreover, the distribution of the few inward FDI in the Country is highly uneven across Northern, Central and Southern regions (Imbriani and Reganati, 2004). Recent empirical studies attempted to understand the reasons for such a sluggish performance and pointed out the relevance of some “country-specific” characteristics such as the (in)efficiency of the bureaucratic system and the (mal)functioning of the judicial system (Basile et al., 2008; Bronzini, 2004; Guerin and Manzocchi, 2007). Along with country-specific characteristics and the availability of tangible resources, recent literature seeking to examine inward FDI attractiveness has begun to focus on the importance of knowledge spillovers and agglomeration economies.

The focus of this study is on the specific characteristics of municipalities, which might attract Multinational Enterprises (MNEs). These include both institutional characteristics and location-specific factors – often intangible in their nature – which shape the local production system. With reference to this latter aspect, the immobile and embedded nature of tacit or uncodified knowledge (that requires proximity in order to be disseminated) is considered as a key factor in the attraction of FDI.

The aim of this research is, therefore, to explain the location patterns of foreign firms at the municipality level. In order to address this research question, we define an economically motivated statistical model, building on Coughlin and Segev (2000) and attempt to single out the key municipal characteristics that might attract/hinder the localisation of FDI. Our baseline model is estimated using a negative binomial estimation model. The amount of FDI in a specific municipality (i.e. our dependent variable) primarily depends on the levels of the municipality’s characteristics that affect profits relative to the levels of these characteristics in other municipalities. These can be classified as those related to the production structure and the geographical and infrastructural characteristics of the municipality. Along these variables, we include in our analysis a set of knowledge spillovers related variables. Specifically, we consider R&D knowledge spillover (i.e. knowledge spilled-over by R&D activities conducted by local firms situated in the municipality area), university-related knowledge spillovers (i.e. possible knowledge flows from university located in the municipality) and district-related knowledge spillovers (i.e. informal knowledge flows within an industrial district operating in the municipal area). These additional variables should capture the immobile and embedded nature of tacit or uncodified knowledge mentioned above.

We consider in our empirical investigation three Italian regions, namely: Lombardia, Emilia Romagna and Campania. These three regions are located respectively in the North, the Centre and the South of the Country and display significant differences as for production structure, infrastructural characteristics and knowledge spillovers. A fact that will allow us to make cross comparison in a country traditionally characterized by large differences as for the level of economic development and FDI inflows.