Mapping Information Economy Business with Big Data: Findings from the UK

Publication type: NIESR Discussion Paper | Publication date: 26 Nov 2014 | Theme: Structural Economics & Productivity | External Author(s): Francois Bouet (Growth Intelligence), Max Nathan, Anna Rosso | Project: Measuring the UK’s Digital Economy With Big Data

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.

Keyword tags: 
quantitative methods
firm-level analysis
big data
text mining
digital economy
industrial policy