The Tricky Challenge of Measuring Entrepreneurship
There are some useful ways to look at what's happening in the local economy and separate the reality from the cultural buzz.
Entrepreneurship, at least as a cultural phenomenon, is booming: Witness the flood of television shows, movies and even Barbie's latest career move. Meanwhile, entrepreneurship education programs have exploded, and support organizations such as incubators are springing up like wildflowers. Even so, real rates of entrepreneurship in the United States remain in long-term decline, and we have seen only a tepid recovery since the Great Recession.
With such a disconnect between zeitgeist and macroeconomic fact, local policymakers can be left foundering -- which story, they might wonder, describes my city? Soft, anecdotal indicators are frequently unreliable, but broad-based statistics may miss crucial nuance.
For those wishing to measure their entrepreneurial ecosystem more accurately, two challenges await: a mountain of unorganized data and the lack of an agreed-upon framework. In a new paper, we draw on existing entrepreneurship research and take a first crack at both tasks.
Our broad framework provides four dimensions along which to measure entrepreneurial vibrancy: density, fluidity, connectivity and diversity.
Density is the simplest indicator, an effort to assess how many firms are in a region. Looking at density instead of raw volume and normalizing for such factors as population or geography allows us to get at some nuance: Boulder, Colo., for example, is small but clearly punching above its weight. We recommend looking at the density of new and young firms, the share of employment in those firms, and the density of the sector -- high-tech or otherwise - that is most important to the local economy.
Fluidity is our next indicator, with which we intend to capture economic and demographic reallocation -- the processes by which a resource becomes more and more efficiently deployed. For instance, when an individual switches jobs, it is generally for a better match and a higher wage. There are obvious exceptions, but most voluntary movement represents an increase in productivity. To measure this fluidity, we recommend looking at population flux, labor-market reallocation and the number of high-growth firms.
Connectivity is the third indicator, and examines whether and how entrepreneurs, investors and others in the market ecosystem interact. While hard, tangible measures such as available financing are important inputs, soft relationships are how the ingredients get mixed. Healthy ecosystems tend to have dense, highly bunched networks, which allows money and information to flow easily. Good data on connectivity is the hardest to find and interpret; of what is available, we recommend looking at program connectivity, business spinoff rates and deal-maker networks.
Diversity is our final indicator. As in nature, we want an entrepreneurial community to avoid becoming a monoculture. Diversity, along both economic and demographic dimensions, strengthens entrepreneurial ecosystems against the possibility of cascading failure. For example, if one industry or skill type runs into trouble (say, from intense overseas competition), we want that weakness to be relatively isolated and not force the entire ecosystem to restart. To measure diversity, we propose looking at economic diversification, immigration and income mobility.
Hopefully, this framework of four indicators can help cut through the noise of entrepreneurship culture while providing more nuance than any single statistic on business formation. More importantly, we hope to kick off a more general discussion: What other theoretical frameworks might be useful in measuring entrepreneurial ecosystems? What new data sources need to be developed? What's the best way to measure entrepreneurial progress over time? As researchers, policy-makers and practitioners answer these questions, we'll enable ourselves to build stronger and more numerous entrepreneurial ecosystems -- and grow the economic pie for everyone.