Over at Atlantic Cities, Richard Florida has written up some of my data on sports leagues and economic structure. The average MLS fan lives in a city with a higher creative class share than any other league, and this is consistent with the story that America’s soccer boom is propelled by creatives.
As someone who studies the economy more closely than Chivas box scores, I am intrigued by how the MLS might explain economic structure, just as economic structure seemingly explains the MLS. Specifically, “Does having an MLS team predict higher human capital?” The following story is preliminary, it won’t ever end up in the NY Times Style Section, but here I am telling it anyway…
Soccer as a New Idea
In 2002, Florida and Gates famously proposed that openness to new ideas is associated with human capital and economic success. To measure openness they used demographic diversity (“tolerance”) variables including the number of gay households and the number of artists. These are proxies for tolerance and ultimately for growth. It’s not that gays and artists make cities grow, but that human capital goes, so the theory goes, to where new ideas and lifestyles are welcome.
If there is a link between tolerance and human capital, then we can imagine a lot of ways to measure it. Maybe the presence of a soccer team in a city is such a way. Soccer is a distinctly foreign sport. It was developed and popularized abroad, and it still attracts derision in many corners of America. If openness to "new ideas" matters for human capital, then surely openness to soccer does too.
MLS does predict the Creative Class
To explore this hunch I performed a simple study of major league cities. I restricted the study to the 54 metros with either a pro sports league, or a NASCAR race. Roughly speaking, this ensured that every place under observation is big enough to support an MLS league.
I performed two simple linear regressions. In the first I used the presence of a MLS team in 2013 to predict 2008 creative class levels. The results are significant, and show that the presence of an MLS team is associated with a 4% higher creative class share on average. Only 15% of all variation in creative class shares can be explained, but given the size of the league that is not surprising. Compared to the weighted averages previously published, these results provide stronger evidence that MLS is associated with human capital.
To get a sense of whether the MLS adds any statistical power above Florida’s measure, I included the tolerance index in a second regression model. This improves the total variance explained to 21%, and only reduces the effect of MLS marginally. When tolerance is taken into account the average MLS city has a 3.7% higher creative class share.
Interestingly the correlation between tolerance and having an MLS team is only .132. In other words, these two measures are not measuring the same thing ; MLS really does predict human capital on its own.
A Caveat: MLS as an Indicator of Human Capital
Here we see evidence that MLS cities are significantly more creative. The next question is “Why?” Florida’s openness-to-ideas thesis, suggests one mechanism through which the MLS can explain creative class share. Soccer is a cosmopolitan sport, and more open-minded places embrace it and human capital more. These results are consistent with that story, but they do not (and cannot) show that MLS cities have higher human capital levels because they are more tolerant.
The presence of a new league in a place might merely reflect its economic vitality, and not its tolerance per se. When MLS owners establish franchises, they are almost surely interested in places that demand soccer, but they also want places that have strong economies generally. Economic conditions, not tolerance per se, probably explain why the MLS isn’t rushing into Detroit or Cleveland and why San Jose was a charter team.
I hope subsequent work can parse these possibilities. I doubly hope that we can be even more creative in how we measure regional openness. PW
Footnote on Robustness In separate models, I tried to control for the percentage of immigrants and the percentage of people under forty. In the first case, the variable was excluded due to multicollinearity. The second variable was not significant.