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

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  • Max Nathan
  • Anna Rosso

Abstract

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.

Suggested Citation

  • Max Nathan & Anna Rosso, 2014. "Mapping Information Economy Business with Big Data: Findings from the UK," National Institute of Economic and Social Research (NIESR) Discussion Papers 442, National Institute of Economic and Social Research.
  • Handle: RePEc:nsr:niesrd:442
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    Cited by:

    1. Alessandro Marra & Vittorio Carlei & Cristiano Baldassari, 2020. "Exploring networks of proximity for partner selection, firms' collaboration and knowledge exchange. The case of clean‐tech industry," Business Strategy and the Environment, Wiley Blackwell, vol. 29(3), pages 1034-1044, March.
    2. Stathoulopoulos, Kostas & Mateos-Garcia, Juan, 2017. "Mapping without a map: Exploring the UK business landscape using unsupervised learning," SocArXiv ryxdk, Center for Open Science.

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    More about this item

    Keywords

    quantitative methods; firm-level analysis; Big Data; text mining; ICTs; digital economy; industrial policy;
    All these keywords.

    JEL classification:

    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • L63 - Industrial Organization - - Industry Studies: Manufacturing - - - Microelectronics; Computers; Communications Equipment
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software
    • O38 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Government Policy

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