This is my first post as an official Transit Miami contributor, but this post is actually a follow-up to an earlier piece that I wrote but which was published under Felipe’s name. In that post, which appeared earlier this summer, I made a case for extending Metrorail out to FIU. That case was essentially this: two intertwined, near-term policy priorities announced by Miami leaders are to solve the problem of the region’s brain drain and to establish Miami as a prominent player for technology start-ups. By better integrating FIU into a comprehensive transit system, we’ll be building the physical infrastructure to cultivate greater personal and professional connections between the university community and the broader South Florida region, particularly its business community; these connections, I argue, will be instrumental in reversing Miami’s brain drain and catalyzing the entrepreneurial culture necessary for a start-up scene.
In that piece, I discussed the nearly universal trend in the United States over the past ten years of cities connecting their colleges and universities to their transit systems. That trend is founded upon two crucial propositions of economic development. Those propositions are:
- City centers and universities represent two of the most productive hubs of innovation, and by improving the physical connections between them, we can facilitate connections between the people, ideas, and resources of each.
- When people, ideas, and resources are well connected, economies thrive.
It is these propositions that have influenced transit planning and economic development in cities throughout the United States, and which I believe should also influence transit planning and economic development in Miami. The transportation case for mass transit stands on its own; mass transit is unquestionably the most efficient technique for transporting people and any serious transportation policy has mass transit as its backbone. Yet, there is also the economic case for mass transit, represented in part by the propositions outlined above. This post will address some of the data that back up those propositions and the assertion that building transit connections to universities like FIU can foster business start-up activity and mitigate and reverse brain drains.
Downtowns and universities represent a disproportionately high share of start-up activity. The days where suburban landscapes, such as Silicon Valley and Route 128, dominate the start-up scene are unsurprisingly over. According to data from the National Association of Venture Capitalists, downtown San Francisco now produces more tech start-ups than Silicon Valley. In the New York metro area, among the ten zip codes that received the highest amounts of venture capital dollars, nine of them were in Midtown or Lower Manhattan. In the Boston area, seven of the ten zip codes receiving the most VC investment are in downtown Boston or downtown Cambridge; only three are in the Route 128 corridor. In all, urban areas received three-fourths of all VC investment in New York, seven-tenths of all VC investment in Boston, and two-thirds of all VC investment in Washington, DC.
In addition to downtowns, universities represent the other major generator of start-up activity. According to data from the Association of University Technology Managers, universities generated 705 spin-off companies in 2012. That number was up from 671 spin-offs in 2011. In 2011 and 2012, 73 percent and 79 percent, respectively, of these spin-offs retained their primary place of business in the university’s home state. This is significant in that is shows that not only to universities generate new businesses, but those businesses tend to stay in that community and remain a long-term contributor to the local economy. Four schools – MIT, Harvard, Tufts, and Boston University – accounted for 35 (or twenty percent) of the 179 start-ups established in Boston last year. In Philadelphia, university spin-offs represented over forty percent of all start-ups.
High transit ridership and low car usage correlates with increased start-up activity in metropolitan areas. Using the PricewaterhouseCoopers MoneyTree Report, the most well-known quarterly study on venture capital investment activity in the United States, and the U.S. Census Bureau’s American Community Survey, I compiled data on all 123 metropolitan areas in the United States that recorded at least a single dollar of VC investment in 2011.
On the graph below, I plotted the percentage of residents commuting to work by public transit along the X axis and the total value of venture capital investment activity along the Y axis for each of the 123 metropolitan areas. Because the graph gets rather cluttered with 123 data points, for aesthetic reasons I removed the individual data points and just left the trendline. The resulting graph shows that higher transit ridership is correlated with higher VC investment.
Here’s the same graph with the trendline calculated using only those mid-sized metropolitan areas, like Miami, with a population between two million and eight million people. We can see that the correlation is similar even when just looking at similarly size metro areas.
When we compare venture capital investment activity to the percentage of residents commuting to work by automobile, we find the reverse correlation to be true. Here’s the data once again from all 123 metropolitan areas. The resulting graph shows that higher car usage correlates with lower VC investment.
And for just mid-sized metro areas of two million to eight million people as well. Again, the correlation is similar among similarly sized metro areas.
High transit ridership and low car usages correlates with higher start-up activity at universities. In addition to looking at the amount of venture capital investment, there are other ways to measure start-up activity. It makes sense to look at these other ways, as well, because venture capital investment does not always tell the whole story. Often times, for example, start-ups are launched in one location, but they move to another location, particularly the Bay Area and New York, once they are ready to begin seeking larger investments. For this reason, it makes sense to look at other metrics, and at the university level, there are a few good ones. We can look at the number of start-ups that a university generates, for example. We can also look at the licensing income that a university receives. Fortunately, the Association of University Technology Managers maintains a robust database of all this information. Comparing data from the AUTM’s annual survey from 2012 with zip-code data from the American Community Survey, we can get a sense of the relationship between commuting habits and the start-up activity at 141 American colleges and universities.
For the first cluster of graphs below, I plotted the percentage of residents in each university’s zip code area who commute to work by public transit along the X axis. Along the Y-axis in the first graph is the total value of licensing income received by each university for each of the 141 universities. Again, I cleared the individual data points and kept just the trendlines. What we see is that as transit ridership rates increase so does university licensing income.
Along the Y-axis in this graph is the number of start-ups generated by each university. Likewise, as transit ridership rates increase, the number of start-ups generated by a university increase as well.
Once again, when we compare the same variables to the share of car commuters, we find a negative correlation. Here’s the share of car commuters to each university’s licensing income. Increased car usage correlates with decreased licensing income.
And here’s car commuters to the number of start-ups generated by each university. Likewise, increased car usage correlates with fewer start-ups generated.
The data here are not a grand slam – these are just correlations – but they begin the paint a picture that supports our central premise: that transit can play a role in building the professional and social connections that are essential to a robust, productive entrepreneurial landscape.
Entrepreneurship is as much a culture as it is a single act. Developing policy to facilitate entrepreneurship requires recognition that more is involved than simply the isolated decision to establish an enterprise. It must also consider the multitude of conscious and unconscious factors that make such decisions possible and likely as well as those factors influencing rates of success. Those include, of course, establishing economic incentives such as subsidized incubators, mentoring programs, and tax benefits for business owners. But these are only helpful once a prospective entrepreneur has made a relatively firm commitment to pursue his or her own business. They do not offer much in the way of giving people the ideas and resources that prompt them to make such a commitment in the first place. Entrepreneurs are not created overnight, just as cultures are not fostered overnight. Cultures are layered and complex and sophisticated, and building an entrepreneurial culture requires more than a few well-targeted incentives packages. It necessitates approaching entrepreneurship from a wide array of directions, including immigration policy, education policy, and even transportation policy. The correlations presented in the charts above should not come as a surprise to anyone who understands how the flow of people and ideas bring about economic innovation and opportunity. And they offer evidence in support of the vital propositions that downtowns and universities are key drivers of our economies, and that by connecting downtowns, universities, and entire regions by transit, we foster greater entrepreneurship.
For Miami, this would be a game changer. We are facing a brain drain and we have the opportunity to reverse that trend and create economic growth by building a technology sector in South Florida. We’ve identified the problems and potential solutions, but without a comprehensive, long-term path for reaching those goals, we won’t succeed. We must recognize that while we cannot centrally plan entrepreneurship from a command tower, we can and must put in place the supports that encourage organic entrepreneurship. This includes developing the infrastructure that facilitates connections between people, ideas, and resources, particularly at hubs of innovation, such as city centers and universities. What we see from the data above is evidence that supports that mass transit is a piece of this infrastructure puzzle.
Special thanks to Jodi Talley from the Association of University Technology Managers for providing me with access to AUTM’s robust database without which this piece would not have been possible.
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