A first analysis of statistical strategies regarding SME’s

1. OECD OCDE ORGANISATION DE COOPÉRATION ET DE DEVELOPMENT ÉCONOMIQUES A first analysis of statistical strategies regarding SME’s ORGANISATION FOR ECONOMIC CO-OPERATION AND DEVELOPMENT Workshop on improving statistics on SME’s and Entrepreneurship OECD, 17-19 September 3003 Andreas Lindner 1 STATISTICS DIRECTORATE TRADE & STRUCTURAL ECONOMIC STATISTICS SECTION

2. Structure of the presentation • Background and Introduction • Definition of SMEs • Consultations with stakeholders and users • Business Frames for SBS • Collection & compilation strategies • Relation with administrative sources • SME data demand and dissemination • Conclusions

3. Background and introduction • Recognition that the information base for SME policies is largely insufficient and inconsistent • OECD launched “Strategy” Questionnaire to NSOs in April 2003 • Results obtained allow a detailed & differentiated view on reality and plans • More solid basis for elaboration of recommendations

4. Definition of SMEs • Considerable variety and local approaches • 4 dimensions identified for possible greater harmonisation and the elaboration of recommendations and target definitions: • 1. Improve comparability between legal/administrative and statistical sources

5. SME definitions (cont’d) • 2. Agree on matching of size classes for data collections and agree on recommendations as to the choice of variables which best describe the enterprise • 3. Improve comparability across sectors (recommended size-classes) • 4. Agree on international action plan aiming at ensuring better comparability amongst OECD countries (and NMEs) and with EU countries

6. (SME) Survey consultation and user issues • Consultation process: • Quite user-driven • Focus on survey characteristics • Focus on the product, not the process • Concerns expressed by process stage: • Data collection • Data compilation • Data dissemination

7. Data collection • ALL countries reported complaints about excessive response burden • This is linked to characteristics of survey population, but should also give raise to re-thinking the survey process • 2/3 of responding countries expressed concern about reported duplication of data collections

8. Data compilation: • Low response rate has been identified as an obstacle to SME data collection • Alternative and/or innovative solutions have to be found • Quality concerns are linked to the low response rate • Uncertainty about validity and representativity of data collected

9. Data dissemination: • Countries are aware of a generally unsatisfactory feedback of results to SMEs and some have developed response strategies • Data availability and timeliness concerns • Inadequate size-class breakdowns

10. Some identified key obstacles: • Low response rate • Sheer size of survey population • Differences between business frames

11. Examples of response strategies: • Increased use of administrative data • Improved and enriched Metadata • Inventory of available SME data and sources • “Single” Business Register

12. Limitations of frames for SBS: • Different updating intervals limit comprehensive coverage • A specific SME frame is rather the exception • Confidentiality issues limit availability for others • General concern about quality and coverage of demographic variables (in particular deaths) • Activities -> Industries allocation difficulties • Improvements to Business Frames are foreseen in a number of countries with respect to SME’s , change of activity, legal status, etc..

13. Collection & Compilation Strategies • In majority of countries, NSOs are fully in charge of data collection • In the other countries, NSOs play at least a coordinating role (Exceptions Germany and Japan) • A majority of countries differentiates SME core statistics from specific variables • A combination of sources (e.g. administrative) is customary • Input Data warehouse/longitudinal DB (AUS)

14. NSO access to and linkage with administrative sources regarding SME data • Mixed picture • Half of those having full access do NOT use it or not much. Why? • Main reasons stated include different basic units and absence of links • Different definitions of variables • No common identifier • Different classifications and thresholds

15. SME data demand and dissemination • Generally speaking, no particularly different dissemination pattern from other SBS data could be observed • Despite a clear interest in SME data by, only few specific products or databases were developed in response • Countries consider SME data as an additional “dimension” to yearly Structural Business Statistics (SBS) • Demographic variables needed to complement SBS

16. Conclusions • This exhaustive stocktaking of statistical strategies with respect to SMEs across countries has allowed to identify statistical key issues for further discussion and possible follow-up and action • These include: • Improve international comparability and foster national consistency/compatibility • Make better use of existing data and make availability of data better known • Eliminate duplicative data collections, optimise cost per information item • Develop tools to better trace dynamics over time • Take concrete and visible action so that entrepreneurs become ”converted” stakeholders, ready to contribute to an international SME Data Warehouse

17. Thank you for your attention!