Regional knowledge spillovers: a firm-based analysis of non-linear effects

Abstract

This article revisits the question of the role of knowledge externalities in firm productivity.It also addresses the overlooked issue of a plausible nonlinear effect and differences among industries. Using a panel of Portuguese manufacturing firms, it finds that regional knowledge spillovers differ substantially across industries and they are nonlinear, which is critical issue to promoting more assertive regional policies.

Different Influence of Cooperation and Public Funding on Innovation Activities Within German Industries

“…This type of system usually combines three sets of entities: private (firms); public (government); knowledge (universities), and helps them to cooperate and create innovative outputs. Carreira and Lopes (2018) stated that regional (and local) innovation systems (RIS), the process of interactive learning and systemic innovation has a strong local dimension, as spatial, institutional and cultural proximity favours closer links, as well as stable knowledge partnering among different types of actors. The dense network of vertical and horizontal relations between actors is crucial for this type of networking.…”

“…And these subjects must be in collaboration. It should be noted that it is a long process; the results cannot be predicted in advance in any way (Carreira & Lopes, 2018). In the positive case the knowledge spill-over effects become a major determinant of innovation processes in firms (Prokop & Stejskal, 2017).…”

How are the potential gains from economic activity transmitted to the labour factor: more employment or more wages? Evidence from the Portuguese context

“…Furthermore, it was not possible to investigate whether there is an optimal regional density of economic activity of the different sources of agglomeration economies that could maximize employment and wage growth. Although some work has been done, namely by Carreira and Lopes (), on Portuguese productivity at the level of firms, plenty of research is carried out on whether such non‐linearities do exist across industries, much remains to be done. In particular, the use of spatial econometric techniques to study the existence of the referred non‐linearities.…”

“…For that purpose, it is necessary first to check whether the data has some spatial pattern, with the use of a distance weight matrix, a necessary condition for applying the referred techniques. Empirical studies show that spillovers are different across industries (Carreira & Lopes, ), so we might expect the transmission of knowledge through space to also be different across industries. As entries for the distance weight matrix, W, that define the spatial transmission of knowledge, we have tested the three most common solutions: the squared inverse distance matrix, the inverse distance matrix and the contiguity matrix, which were all normalized.…”

Knowledge Technology Transfer: A Spatial Analysis within the Triad

“…For a good assimilation of other firms' knowledge, it is important to exploit the proximity to the source of externalities, as suggested by many economists (Aldieri and Cincera, 2009;Carreira and Lopes, 2018;Jaffe, 1986;Jaffe et al, 1993;Orlando, 2004), which have explored knowledge technology flows taking into account the geographic proximity or technological linkages between the innovation producer and the recipients. In particular, Carreira and Lopes (2018) found that regional knowledge Spillovers differ substantially across industries. However, it has been recognized that both the technological and the geographical distance between firms affect knowledge flows from innovation.…”