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 [1]. 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.
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