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

STATISTICS DIRECTORATE STRUCTURAL ECONOMIC STATISTICS 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

STATISTICS DIRECTORATE STRUCTURAL ECONOMIC STATISTICS 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

STATISTICS DIRECTORATE STRUCTURAL ECONOMIC STATISTICS 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

STATISTICS DIRECTORATE STRUCTURAL ECONOMIC STATISTICS 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

STATISTICS DIRECTORATE STRUCTURAL ECONOMIC STATISTICS 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

STATISTICS DIRECTORATE STRUCTURAL ECONOMIC STATISTICS 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

STATISTICS DIRECTORATE STRUCTURAL ECONOMIC STATISTICS 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

STATISTICS DIRECTORATE STRUCTURAL ECONOMIC STATISTICS 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

STATISTICS DIRECTORATE STRUCTURAL ECONOMIC STATISTICS 10 Some identified key obstacles: Low response rate Sheer size of survey population Differences between business frames

STATISTICS DIRECTORATE STRUCTURAL ECONOMIC STATISTICS 11 Examples of response strategies: Increased use of administrative data Improved and enriched Metadata Inventory of available SME data and sources “Single” Business Register

STATISTICS DIRECTORATE STRUCTURAL ECONOMIC STATISTICS 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..

STATISTICS DIRECTORATE STRUCTURAL ECONOMIC STATISTICS 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)

STATISTICS DIRECTORATE STRUCTURAL ECONOMIC STATISTICS 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

STATISTICS DIRECTORATE STRUCTURAL ECONOMIC STATISTICS 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

STATISTICS DIRECTORATE STRUCTURAL ECONOMIC STATISTICS 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

STATISTICS DIRECTORATE STRUCTURAL ECONOMIC STATISTICS 17 Thank you for your attention!