A striking feature of economic geography is the large variation in productivity across regions. Moretti (2011) documents that after adjusting for skill composition, average wages in the highest and lowest paying US metropolitan areas differ by approximately a factor of three. Such dispersion is also evident when one compares innovation outcomes across regions. Silicon Valley and Boston are popular examples of outlier regions, significantly more productive than others in terms of innovation.
In Figure 1, we illustrate such variation using US patent data on computers and communications technologies in 1995. Even metropolitan statistical areas (MSAs) of similar size in terms of the number of local inventors often differ substantially in terms of their innovation productivity (number of citation-weighted patented inventions per inventor). For example, Rochester, NY and Portland, OR had a similar number of innovators working in the computer and communications industry in 1995, but Portland inventors generated almost twice the number of citation-weighted patents.
Figure 1 Variation in regional innovation: Computers and communication patenting in 1995
Regional productivity disparities have led to a variety of policies focused on enhancing local innovation. In cities like San Diego, CA, or St. Louis, MO such initiatives have mainly focused on encouraging entrepreneurship. Conversely, cities like Flint, MI, or Greenville, SC have invested heavily on attracting large corporations.
In recent research, we study how local innovation is affected by the organisation of R&D manpower (Agrawal et al. 2013). In other words, for a region with a given number of inventors, does the manner in which those inventors are organised influence their productivity? We argue that innovation productivity is greater in ‘diverse’ regions, which we define as regions where large and small labs coexist.
Large labs and small labs
The presence of large labs is beneficial because they have an advantage in idea production due to within-firm knowledge spillovers as well as spreading fixed costs of research over more projects (Schumpeter 1942). At the same time large labs only commercialise innovations that ‘fit’ with their established research activities. For example, in 2001 only five out of more than 2,000 new product proposals by General Electric employees were accepted for product development (Cassiman and Ueda 2006).
Spin-outs may commercialise ‘misfit’ inventions that are not consistent with the assets, capabilities, or strategy of the parent firm. We expect the cost of spin-out formation to be reduced when a large number of small labs are present in the region. Intuitively, the presence of many small labs generates a thick local market for ancillary services, and may also spur a culture of entrepreneurship that lowers the risk and cognitive cost for employees of large labs to leave their employer and start their own firm or join another entrepreneurial venture (Chinitz 1961).
The complementary externality effects of co-located large and small labs imply that innovation is maximised in regions displaying firm size diversity.
Firm size diversity and innovation
We test the empirical validity of our theory using US regional innovation data for the period 1975 to 2000. First, we report two case studies from 1995 that are consistent with our theory to illustrate our main point:
- Portland, OR compared to Rochester, NY (lack of small firms); and
- Atlanta, GA compared to Seattle, WA (lack of a large firm).
In terms of Portland and Rochester, the number of inventors patenting in the computers and communications technology class is similar in the two cities (roughly 1,000 inventors). However, Portland significantly outperforms Rochester, obtaining about twice the number of quality-adjusted patents as Rochester. While both cities register a similar presence of large labs, the number of small labs is substantially different: Portland has more than five times as many small labs as Rochester.
On the other hand, in the chemicals technology class, Seattle and Atlanta have a similar number of small labs (38 and 36, respectively) and also a similar number of overall inventors (457 and 484, respectively), but only Atlanta has a large lab (Kimberly Clark). Atlanta also has 37% more quality-adjusted patents.
The majority of our paper is focused on providing a detailed econometric analysis of this relationship using panel data organised by region-sector-year (e.g., Boston-chemicals-1990). We report results that strongly support our theory. We find that in periods where at least one large lab and numerous small labs co-exist, regions experience a 17% increase in innovation. Furthermore, consistent with the proposed mechanism, we find that diversity is associated with a 28% increase in the probability of spin-out formation. Moreover, we present additional analyses indicating that the data are consistent with our causal interpretation but not the main competing hypotheses.
Differentiated policy solutions
Our findings suggest important policy implications. Regional productivity disparities have led to a variety of policies focused on enhancing local innovation. Such initiatives often focus on either promoting entrepreneurship or attracting large corporate labs. Our results indicate that policies focused exclusively on attracting ‘anchor tenants’ or cultivating new ventures may not be as effective as promoting firm size diversity, leading to an appropriate mix of large and small firms. In other words, our results suggest that there is no universal ‘best’ policy, but rather that the optimal policy depends on the organisational structure of R&D labour in a region at a given point in time. In simplistic terms, a region with large firms but few young entrepreneurial firms may benefit more from policies designed to cultivate new ventures rather than to attract more large firms, whereas regions without local large firms may benefit most from attracting these.
Agrawal, A, I Cockburn, A Galasso and A Oettl (2013), “Why are some regions more innovative than others? The role of firm size diversity,” CEPR Discussion Paper No. 9766.
Cassiman, B and M Ueda (2006), “Optimal project rejection and new firm start-ups,” Management Science 52, 262-75.
Chinitz, B (1961), “Contrasts in agglomeration: New York and Pittsburgh,” American Economic Review 51, 279-289.
Moretti, E (2011), “Local Labor Markets,” in D Card and O Ashenfelter (eds), Handbook of Labor Economics, Volume 4b, New York: Elsevier, pp. 1237-1313.
Schumpeter, J (1942), Capitalism, Socialism, and Democracy, New York: Harper.