Arbeitspapier

Mapping 'Information Economy' Businesses with Big Data: Findings for the UK

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.

Sprache
Englisch

Erschienen in
Series: IZA Discussion Papers ; No. 8662

Klassifikation
Wirtschaft
Large Data Sets: Modeling and Analysis
Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
Microelectronics; Computers; Communications Equipment
Information and Internet Services; Computer Software
Technological Change: Government Policy
Thema
quantitative methods
firm-level analysis
Big Data
text mining
ICTs
digital economy
industrial policy

Ereignis
Geistige Schöpfung
(wer)
Nathan, Max
Rosso, Anna
Bouet, Francois
Ereignis
Veröffentlichung
(wer)
Institute for the Study of Labor (IZA)
(wo)
Bonn
(wann)
2014

Handle
Letzte Aktualisierung
10.03.2025, 11:42 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Nathan, Max
  • Rosso, Anna
  • Bouet, Francois
  • Institute for the Study of Labor (IZA)

Entstanden

  • 2014

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