05/10/2016 - In the third data pilot in Arloesiadur, Nesta’s innovation analytics project for Welsh Government, the innovation charity draws on cutting edge economic geography research to identify related industries for clustering analysis, measure the complexity of local economies in the UK, explore the links between complexity and better economic outcomes such as productivity and wealth, and generate predictions about the future specialisations of UK local economies based on their current profiles. View the data map here.
Complex places for complex times: An analysis of the complexity of UK local economies, and their future evolution
Nesta - One of the key economic lessons of the last 20 years is that, in spite of globalisation and the Internet, place still matters: industries tend to cluster in particular places; the industrial composition of those places shape future opportunities and constraints . Too much specialisation creates fragile local economies reliant on the fortunes of a small number of sectors. Too much variety could reduce the scope for spillovers between them.
The questions for policymakers are:
- What is the current profile of a local economy?
- What are the potential and desired future paths of development?
- How to intervene (if at all) to achieve desired outcomes?
These are very topical issues: many analyses have linked the discontent behind the results of the European Referendum to regional economic divides, and the same seems to apply to the advance of Donald Trump in the USA. National and local industrial strategies to drive industrial growth are back on the agenda.
The challenge is how to design and implement these strategies in a way that creates new markets, strengthens industrial ecosystems and drives growth, rather than prop up inefficient industries or satisfy vested interests. Ideas such as ‘smart specialisation’ or ‘entrepreneurial discovery’, originated in academia and adopted by the European Commission are an important contribution to these debates. In a nutshell, they ask regions to focus on those industries where they have established strengths rather than trying to build new clusters from scratch, and to identify what the new opportunities are in a process driven by entrepreneurs instead of officials.
This blog post reports the findings of an innovation analytics pilot where we apply new approaches developed by economic geographers and complexity scientists with the goal of generating data that can inform policy decisions in this important area. The pilot is part of Arloesiadur, our project to develop an innovation dashboard for Welsh Government.
We discuss some of the findings in the rest of the blog. Although we introduce key concepts and intuitions for the methods used in the relevant sections, we don’t go into their detail. If you want further information, check the GitHubrepository with the scripts we have used to process and analyse the data. We've made a visualisation of the data available here.
Before starting, we should point out this is an exploratory pilot with limitations that we highlight where relevant, so the (suggestive) results should be taken with caution. Our goal is to take this analysis further when we start building the Arloesiadur platform in the coming months, incorporating any feedback or suggestions you might have. Read full article.