which in turn positively affect the return of private investment in innovation. In this work, we refer to positive _spillovers_ on firms’ productivity that are originated by knowledge-related activities carried out by other organizations or individuals in their immediate context. These spillovers can be sectoral or regional/spatial.

# _a) Sectoral context_

The literature on _technological opportunities_ (TO) argues that the sectoral differences in the returns to R&D are explained by variations in TO. These are defined as the set of technological options that determine the distribution of the values of the production function or product attributes that can be achieved via R&D (Klevorick et al. (1995)). Although this concept is fundamentally technologically driven, the preoccupation with decreasing returns of investment in R&D pushes scholars to analyze systemic sources claimed to be able to renew the pool of TO. These are explained either by technological trajectories—as in the traditional literature arguing that technological specificities drive different patterns of innovation across sectors — (Malerba and Orsenigo 1995, Pavitt 1984)<sup>8</sup> or related to spillovers created either by –STI policy (particularly in supporting universities and research institutions that produce marketrelevant scientific knowledge) or by advancement in the industry. This has been assessed empirically in Klevorick et al. (1995) and later contributions, including Marín and Petralia (2018); Fung (2004); and Kafouros and Buckley (2008).<sup>9</sup>

# _b) Regional/spatial context_

Several contributions concerning the systemic approach come from regional innovation studies analyzing how socioeconomic factors present in the territory where the firm produces (such as the institutional capacity, the supply of human capital, and public support for the generation of knowledge) affect both the level and the effectiveness of their investment in R&D (Crescenzi and Rodríguez-Pose 2013). This literature is motivated by the stylized fact that innovation is not randomly distributed in the territory but tends to concentrate geographically (Audretsch 1998). As far back as 1890, Marshall (1890) identified three reasons that explain geographical concentration: availability of skilled workers; availability of specific inputs, such as natural resources; and technological spillovers. This rationale gave birth to the new economic geography and the study of economics of agglomeration, led by Krugman (1991). According to his studies, “geographic concentration of production is clear evidence of the pervasive influence of some kind of increasing returns” (page 6).

# _3.1.2. Science, Technology, and Innovation Policies_

Policy instruments are designed to strengthen several aspects needed to increase the rate of return of R&D, such as a supportive scientific system; providing infrastructure for interaction

> 8 Pavitt (1984) classifies industries according to the source of technology (such as inside/outside the firm, government/private-financed); users’ needs (such as price/performance); and methods used to appropriate benefits from innovation (such as secrecy, patents, time lags, and unique knowledge). Similarly, Malerba and Orsenigo (1995) explore the dynamics of technological change and define two different groups, labeled technological regimes, that are characterized by a specific combination of conditions of technological opportunity, appropriability of innovation, cumulativeness, and properties of the knowledge base defined at the sectoral level.

> 9 Another important related strand of literature summarized in Griliches (1994) and more recently in Bloom et al. (2017) focuses on the productivity of new ideas. This literature is more macro but has sector-specific implications because in some sectors ideas “are harder to get” and this will affect their returns to R&D investments to develop them.

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