Mapping 'Information Economy' Businesses with Big Data: Findings for the UK - Max Nathan; Anna Rosso; Francois Bouet (Institute for the Study of Labor (IZA), 2014)
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. Overall, we find that the ICT production space is around 40% larger than SIC-based estimates, with almost 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.
Keywords: C55; C81; L63; L86; O38; 330; quantitative methods; firm-level analysis; Big Data; text mining; ICTs; digital economy; industrial policy