The jobless recovery of the Great Recession has led policymakers and citizens alike to ask what can be done to better protect regions from the cascading effects of an economic downturn. Economic growth strategies that aim to redevelop a waterfront for tourism or attract high growth companies to the area, for example, have left regions vulnerable by consolidating resources in just a few industry sectors or parts of town. A promising answer that coincided with growing interest in regional innovation policy has been to promote entrepreneurship for bottom-up, individual-led regional development. However, these policies have also failed to maximize the potential for bottom-up development by focusing on high skill entrepreneurs and high tech industry sectors, such as green energy and nanotechnology.

This study uses the extended case approach and mix methods to determine whether cluster theory can be usefully extended from regional networks of high skill innovators to solo entrepreneurs in traditional trades. It is within spatially proximate clusters that we find the positive externalities associated with agglomeration economies and regional growth. Whether it is due to entrepreneurial ideas, skills diffusion or shared resources, small co-located firms are thought to create an environment ripe for entrepreneurship and regional economic growth. The study uses U.S. Census data in 12 representative regions to assess whether traditional entrepreneurs cluster at the neighborhood level. In-person interviews are also conducted in cluster and non-cluster neighborhoods in Dayton, Ohio to determine whether social networks explain high rates of neighborhood self-employment. Whereas, case studies of entrepreneurs have been confined to mega-cities on the coasts (largely anomalies in the American landscape), Dayton, Ohio better represents typical American regions and neighborhoods because it is mid-sized, has average population density and has no major public train transport. This has implications for the frequency and diversity of network-building that have not yet been explored and for cluster development in depressed economies.

The quantitative analysis documents, for the first time, a minor degree of neighborhood-level entrepreneur clustering in the sample regions. These cluster scores (locational Gini coefficients) are compared to other worker groups, previous census years and to a subset of neighborhoods with below average college attainment and non-distressed poverty rates. Moreover, in over a dozen interviews, entrepreneurs offered clear examples of social networks that demonstrate positive externalities and resemble those spillovers and linkages shown to make regional clusters successful. The interviews help clarify that a slightly larger geography than the neighborhood and smaller than the region, may reveal more clustering. The research informs growing policy interest in bottom-up urban development by offering evidence of how local mechanics, seamstresses, lawn care businesses and many others can be regional assets.