Innovation clusters: Examining the role of federal, state and local government
One of the last things state and local officials want to hear around election time is “It’s the economy, stupid.” To avoid that dread fate, officeholders generally strive to do pretty much anything they can to keep jobs in their districts. At the top of the list: Encouraging big employers to stay in town while persuading new ones to move in — “chasing smokestacks,” as it has been called. Governments end up bidding against each other to attract large firms, and as a 2010 study from MIT, Harvard and U.C. Berkeley shows, the result can be a zero-sum game, with winners and losers.
In such battles to attract employers, tax-based incentives are a favored tool, even as their use has been associated with higher rates of corruption. Once rare, tax-increment financing is often used to build infrastructure demanded by big firms — roads, rails, enlarged ports or new facilities. But such deals can be opaque and have the potential to leave local authorities with substantial debt if deals are too generous or projections overoptimistic.
Alternative strategies exist that are place-based or sector-focused. Federal empowerment zones focus on specific neighborhoods in need of jobs and housing. Regions and cities can also create “innovation districts” or “research parks” to attract small businesses, startups or even specific industries such as biotechnology. “Eds and meds” — higher education and pharmaceuticals — is a popular target these days. A 2012 report from the U.S. Census Bureau and the University of Maryland found that “young firms” can create substantial employment — in 2010 alone, 2.3 million jobs. A potential advantage of bringing in many small companies — particularly those that require analytic and social-intelligence skills — is that some research has shown that they benefit from proximity to each other, something known as a clustering effect. In turn, such business agglomerations can drive additional growth, or so the theory goes.
A 2013 study for the National Bureau of Economic Research, “Clusters of Entrepreneurship and Innovation,” looks at the validity of this premise. The researchers — Aaron Chatterji of Duke University, William R. Kerr of the Harvard Business School and Edward L. Glaeser of Harvard University — review existing research on entrepreneurial clusters, analyze policies intended to encourage them and look at their potential economic effects. “For these policies to make sense, these [cross-firm] spillovers must display increasing returns to scale (i.e., 200 entrepreneurs generate more than double the spillovers of 100 entrepreneurs) or accrue disproportionately to members of a particular industrial sector.”
Factors examined by the study include higher-education institutions in an area, the age of its inhabitants and percentage of immigrants, infrastructure and local entrepreneurial culture. Three specific cases are explored — Silicon Valley, Route 128 in Boston and the Research Triangle Park located near Durham, Raleigh, and Chapel Hill, North Carolina. Also considered are cities that once had large single employers or industries, including Seattle (Boeing), Detroit (the automobile industry) and Pittsburgh (steel), to better understand why their fortunes diverged.
The researchers’ findings include:
- One of the key factors found to encourage and support the establishment, growth and success of innovation hubs is having a “local supply” of entrepreneurs. “Several studies have documented that entrepreneurs tend to disproportionately found their companies in their regions of birth and that these business are in fact stronger on average than the businesses of the typical migrating entrepreneur…. This line of work suggests that policy efforts to build entrepreneurship among a location’s existing residents may be more powerful than efforts to attract outside entrepreneurs to the city.”
- Cities that have a high entry rate for innovative firms tend to have an educated workforce, but this depends on the sector in question. By some measures, an older, more experienced workforce has been found to be positively correlated with more entrepreneurship: “Studies employing metrics that emphasize the creation of start-ups that employ other workers tend to find workers in ages near 40 years old to be most important.”
- Successful clusters have arisen with and without dedicated planning and support. While federal research funds were involved early on with Silicon Valley and Route 128, neither was the result of a cohesive vision. However, North Carolina’s Research Triangle Park involved significant state-level planning from its conception in 1955 through today. “Taken together, while public policy played some role in the creation of the United States’ most successful clusters, there was no national-level strategy to develop and sustain these clusters.”
- Policies used to encourage the establishment of entrepreneurial clusters are distinguished by their variety. National policies can include overall taxation policy, industry-specific provisions, research subsidies and firm-specific guarantees. Cities and counties can employ tax breaks, infrastructure or contracts. “The largest determinant of the degree of geographic specificity is the geographic reach of the governmental unit itself.”
- Federal support to spur regional growth is significant but not highly coordinated. “As of 2008, the federal government already had 250 overlapping programs worth $77 billion that were designed in part to spur regional economies.” Recent efforts by the Obama administration have focused on improving the efficiency and impact of programs.
- Entrepreneurship backed by venture-capital (VC) funds is highly clustered, with about 40% of the total in the United States going to firms in Silicon Valley. The two regions with the next highest totals are Boston and New York, both of which receive about 10% of the VC funding. Together all three regions constitute only 11% of the U.S. population.
- Local governments often promote industries with which they have long-standing relationships — finance in New York City, for example — or areas perceived as promising for the future, such as biotech. Based on past experience, however, industrial and business monocultures have the potential to dampen entrepreneurial activity. (Concentration can also lead to increased risk, as Chatterji writes in the New York Times.)
“Regional foundation for growth-enabling innovation is complex and … we should be cautious of single policy solutions that claim to fit all needs,” the researchers caution. “The existing work on entrepreneurship and local innovation does not imply any natural local policy. It does, however, point to the power of small start-ups, which can collectively shape the economic destiny of a locale.”
A related 2012 study published in the Journal of Economic Geography, “Cities, Skills and Wages,” found that high-skill jobs benefit from “clustering” and thus tend to concentrate in larger, denser metropolitan areas. As a consequence, workers’ skill levels are a much better predictor of wages than their education. “While the return to a college education has remained relatively flat between 1999 and 2008, the return to skills has more than doubled.”
Keywords: employment, entrepreneurship, small business, clustering, cluster effect, agglomeration effects
Read the issue-related New York Times article titled "Patent Producers Clustered in Only a Few Cities."
- What key insights from the news article and the study in this lesson should reporters be aware of as they cover these issues?
Read the full study titled “Clusters of Entrepreneurship and Innovation.”
- What are the study's key technical terms? Which ones need to be put into language a lay audience can understand?
- Do the study’s authors put the research into context and show how they are advancing the state of knowledge about the subject? If so, what did the previous research indicate?
- What is the study’s research method? If there are statistical results, how did the scholars arrive at them?
- Evaluate the study's limitations. (For example, are there weaknesses in the study's data or research design?)
- How could the findings be misreported or misinterpreted by a reporter? In other words, what are the difficulties in conveying the data accurately? Give an example of a faulty headline or story lead.
Newswriting and digital reporting assignments
- Write a lead, headline or nut graph based on the study.
- Spend 60 minutes exploring the issue by accessing sources of information other than the study. Write a lead (or headline or nut graph) based on the study but informed by the new information. Does the new information significantly change what one would write based on the study alone?
- Compose two Twitter messages of 140 characters or fewer accurately conveying the study’s findings to a general audience. Make sure to use appropriate hashtags.
- Choose several key quotations from the study and show how they would be set up and used in a brief blog post.
- Map out the structure for a 60-second video segment about the study. What combination of study findings and visual aids could be used?
- Find pictures and graphics that might run with a story about the study. If appropriate, also find two related videos to embed in an online posting. Be sure to evaluate the credibility and appropriateness of any materials you would aggregate and repurpose.
Class discussion questions
- What is the study’s most important finding?
- Would members of the public intuitively understand the study’s findings? If not, what would be the most effective way to relate them?
- What kinds of knowledgeable sources you would interview to report the study in context?
- How could the study be “localized” and shown to have community implications?
- How might the study be explained through the stories of representative individuals? What kinds of people might a reporter feature to make such a story about the study come alive?
- What sorts of stories might be generated out of secondary information or ideas discussed in the study?