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International Data on Business Start-ups: Factors Affecting Comparability PowerPoint Presentation
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International Data on Business Start-ups: Factors Affecting Comparability

International Data on Business Start-ups: Factors Affecting Comparability

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International Data on Business Start-ups: Factors Affecting Comparability

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  1. OECD OCDE International Data on Business Start-ups:Factors Affecting Comparability Steven VALE, OECD / ONS

  2. The Issue • Increasing political and academic interest in business demography and entrepreneurship • Accurate measures of business start-ups are important indicators for both • OECD project on international comparability of start-up rates • Funded by the International Consortium for Dynamic Entrepreneurship Benchmarking, led by FORA

  3. Current Position • Inventory of 49 Internet data sources from 27 countries • Statistical business register is the most common source • Examination of metadata to try to understand the differences in sources • Typology of factors affecting comparability • Tested on countries with multiple sources

  4. Factors Affecting Comparability • Reasons why data are not comparable • Genuine variation • Methodological differences

  5. Proportion of businesses with no employees Source: Taken from “Business Demography in Europe, Results for 10 Member States and Norway”, Table 2.5, published by Eurostat in 2004. Data for 2001 (except Belgium – 2000)

  6. Factors Affecting Comparability • Reasons why data are not comparable • Genuine variation • Methodological differences • Factors provide a framework to help understand methodological differences • Start-up rates = New Businesses Population • Numerator and denominator factors

  7. Numerator Factors • Source – register, census or survey? • Units – enterprise, establishment,...? • Scope – inclusions / exclusions? • Threshold – small units? • Time – when to measure? • Purity – births or other events?

  8. Denominator Factors • Population – businesses or people? • Coverage – inclusions / exclusions? • Temporal basis – “point in time” or “live during period”?

  9. United States Data – 4 Sources

  10. Conclusions • The charts clearly show why start-up rates need to be broken down into their components • Each component is affected by a number of factors • A framework to systematically assess these factors helps to make better informed and more reliable comparisons

  11. What Next? • Short-term: • Apply framework to data from different countries • Standard methods to adjust for methodological differences? - “Quick wins” • Impact of births – how important are they really for job creation?

  12. What Next? • Short-term: • Apply framework to data from different countries • Standard methods to adjust for methodological differences? - “Quick wins” • Impact of births – how important are they really for job creation? • Long-term: • What do data users really want? • “Gold-standard” methodology

  13. Thank-you for listening. Any Questions? steven.vale@oecd.org steven.vale@ons.gov.uk