Posts Tagged ‘big data’

New big data paper

November 27, 2014

(c) 2014 NIESR / GI

Anna Rosso and I have just published the next phase of our big data project. Kindly funded by NESTA, this builds on the work we did with Google last year. As before we’re working with Growth Intelligence, who’ve developed the very nice multi-layer dataset we use. We’ll be publishing a further paper sometime in the New Year.

You can download the full NIESR working paper here or a summary here. A version of the paper will also be coming out in Research Policy shortly.

The abstract is below. Or take a look at this writeup in the FT.

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Governments around the world want to develop their ICT and digital industries. Policymakers thus need a clear sense of the size and characteristics of digital businesses, but this is hard to do with conventional datasets and industry codes. This paper uses innovative ‘big data’ resources to perform an alternative analysis at company level, focusing on ICT-producing firms in the UK (which the UK government refers to as the ‘information economy’). Exploiting a combination of public, observed and modelled variables, we develop a novel ‘sector-product’ approach and use text mining to provide further detail on the activities of key sector-product cells. On our preferred estimates, we find that counts of information economy firms are 42% larger than SIC-based estimates, with at least 70,000 more companies. We also find ICT employment shares over double the conventional estimates, although this result is more speculative. Our findings are robust to various scope, selection and sample construction challenges. We use our experiences to reflect on the broader pros and cons of frontier data use.

Big data and digital firms

July 23, 2013

(C) 2013 niesr and growth intelligence

I’ve just published some new analysis of the UK’s digital economy, joint with Anna Rosso and Growth Intelligence, and funded by Google. We had a launch session yesterday with Vince Cable – see here for a good write-up by the Guardian.

We’ve done pretty well for media so far: see coverage from the BBC, FT [£], Sky, Telegraph, Independent, Scotsman and Guardian (again) among others, and a nice blog post from Google’s Hal Varian.

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This is the first phase of a research programme with roots in the resurgence of industrial policy around the world. Like many others, the UK government wants to promote ICT and digital content activities – in the global North at least, this is generally high value activity, with spillover effects to the rest of economy.

A big problem is that we have little idea of the true size and nature of these digital companies. That’s because official definitions use SIC codes, which don’t work well for companies doing innovative, high-tech stuff.

To try and fix this, we use big data provided by Growth Intelligence. GI pull in data from the web, social media, news feeds, patents and a range of other sources, and layer this on top of public data from Companies House. That gives a much richer picture of who’s out there, their characteristics and their performance.

Crucially, GI’s data buys us a lot more precision than SIC-based analysis. We can look at industries and at products, services, clients and distribution platforms.  For increasingly tech-powered sectors like architecture, that allows us to distinguish ‘digital’ companies producing (say) CAD specialist software from ‘non-digital’ ones making buildings.

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Overall, we find over 40% more digital companies than official estimates suggest. We also find that digital companies who report revenue or employment are pretty resilient, with faster revenue growth and higher average employment than non-digital companies.

And contrary to the popular sense that it’s all about London start-ups, we find hotspots of digital activity across the country, including some perhaps surprising places like Aberdeen, Middlesbrough and Blackpool.

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Okay, this is all fascinating stuff for researchers. But what should Government do differently? First, the big data field is still in its early days, and we’d encourage officials to explore how it can complement conventional statistics. Second, better data should lead to better-designed industrial policies. Finding the optimal policy mix, however, is a separate and much harder question to answer.

BIS’ information economy strategy is rightly cautious about hands-on intervention. This NBER paper by Aaron Chatterji, Ed Glaeser and Bill Kerr is a good overview of the wider evidence. Henry Overman and I will be publishing a piece in the Oxford Review of Economic Policy soon too, which puts the case for a more agglomeration-focused approach.

We’ll also be continuing the data analysis, thanks to further support from NESTA. Look out for further mapping and econometric work in the months ahead.

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