Local knowledge spillovers and the effects of related and unrelated variety on the novelty of innovation

ABSTRACT

Knowledge spillovers have been identified as a factor affecting the unequal distribution of innovation in space. In this paper we aim to understand how territorial factors shape the novelty degree of innovations. Thus, we perform an empirical analysis that relates territorial factors to innovative performance at the firm level. Our results show that local knowledge spillovers from research and development expenditures are positively associated with upper-level innovation, while local knowledge spillovers from total innovation expenditures are not related to the degree of novelty of innovation. Furthermore, the impacts on innovation are also moderated by related and unrelated varieties since firms in regions with higher regional-related variety are less likely to generate upper-level innovation.

KEYWORDS:

• degree of novelty of innovation
• geography of innovation
• local knowledge spillovers
• related and unrelated variety

JEL:

• O31
• R11
• R12

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the authors.

Notes

1. Time references are made in different ways for the different variables. In general, the variables that do not involve recording values are accounted for in three consecutive years, that is, from 2006 to 2008 for PINTEC 2008, and from 2009 to 2011 for PINTEC 2011. Variables with values are measured in the last year of reference for the survey.

2. Degree of novelty of innovation can be expressed as follows: $\begin{array}{r}Degree=y\\ \begin{array}{c}\mathrm{i}\mathrm{f}\mathrm{P}\mathrm{R}\mathrm{O}\mathrm{D}\mathrm{N}\mathrm{O}\mathrm{V}=\mathrm{y}\mathrm{A}\mathrm{N}\mathrm{D}\mathrm{P}\mathrm{R}\mathrm{O}\mathrm{C}\mathrm{N}\mathrm{O}\mathrm{V}\le \mathrm{y}\mathrm{O}\mathrm{R}\\ \mathrm{i}\mathrm{f}\mathrm{P}\mathrm{R}\mathrm{O}\mathrm{D}\mathrm{N}\mathrm{O}\mathrm{V}\le \mathrm{y}\mathrm{A}\mathrm{N}\mathrm{D}\mathrm{P}\mathrm{R}\mathrm{O}\mathrm{C}\mathrm{N}\mathrm{O}\mathrm{V}=\mathrm{y};\end{array}\\ \mathrm{y}=0,1,2,3.\end{array}$

3. Since our empirical analysis is based on 310 classes (five-digit industries – D) within 32 macro-domains (two-digit industries – G), the maximum limit for related variety is ${\log }_2\left(D\right)-{\log }_2\left(G\right)$.

4. Since the maximum limit for unrelated variety is ${\log }_{2}G$ and G = 32.

Additional information

Funding

This study was supported by the FAPESP [grant number 2013/21348-5]; CAPES [grant number 99999.006723/2015-02]; and Borsa di studio di ricerca (Identificativo Borsa Economia e Statistica) bandita dall' Universita degli Studi di Torino nell' ambito del progetto I@UNITO con Decreto Dirigenziale Prot. N. 143902 del 20/07/2016.