Why should you read it? I think there’s four reasons to care about this stuff:
First, we know that physical co-location has a range of economic benefits, but we’re much less clear about when these kick in. Historically researchers and policymakers have thought in terms of clusters, from neighbourhood level up; more recent work suggests rather smaller microgeographies may be just as important. Understanding this is especially important *right now*, as we exit a giant forced experiment in remote working.
Second, incubators and accelerator programmes have grown VERY fast in the past decade. This Beauhurst report is a great overview of the UK scene, where accelerator participation alone has risen 78% *per year* since 2014.
Third, and relatedly, providers often make strong claims for what their programmes can do in terms of boosting entrepreneurship and innovation. How well founded are these? The more selective your programme, for example, the more likely firms who get in would have done well anyway.
Fourth, these programmes now get a lot of public money. At least 13 countries now support them as part of national innovation programmes. In the UK, according to NESTA/LSE, over half of programmes get at least some public funding: £187,000 per year on average. Is that money well-spent?
With that in mind, we do three things in the paper. First, we develop a typology of colocation-based programmes and show how accelerators, incubators and co-working fit into that. Second, we explore why these programmes have grown so fast, and build a framework to explain their design choices and potential benefits for firms. Third, we check whether those benefits are real. Specifically, we review evidence from across the OECD on the impact of accelerators and incubators — both for firms who take part, and on surrounding cities and regions, as far as we have it.
What do we find? To quote:
We draw five main lessons. First, both accelerators and incubators have positive impacts on participant outcomes, in particular in relation to employment (and, for accelerators, in relation to access to finance). Second, programmes may help ‘non-typical’ firms, such as female- or BAME-headed businesses, where founders may have trouble accessing mainstream economic institutions. Third, programme effectiveness varies by ecosystem features. Accelerators are most effective when located in dense entrepreneurial ecosystems; incubators may be more effective with university involvement. Fourth, evidence of programme effectiveness could increase the price of this type of urban real estate, especially in locations where programmes are most effective, and if demand for permanent office space in cities falls post-lockdown.
Fifth, outcomes for non-profit programmes suggest a potential role for urban public policymakers. However, the impact of detailed design choices is still poorly understood; for example, there is no clear evaluation evidence on the relative importance of funding, mentoring and networking, or the optimal length of tenancy. Providers and policymakers should further test for optimal designs.
So that still leaves us with plenty of unanswered questions; including building a better understanding of how programmes link to cluster and city-level outcomes. In the paper we sketch out some of these questions, and how we might start to answer them.