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ESSnet on Measuring Global Value Chains ESSnet workshop Roma, 3-4 December 2012 Co-ordinator:

ESSnet on Measuring Global Value Chains ESSnet workshop Roma, 3-4 December 2012 Co-ordinator: Peter Bøegh Nielsen, Statistics Denmark pbn@dst.dk. ESSnet Measuring Global Value Chains. Globalisation indicators

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ESSnet on Measuring Global Value Chains ESSnet workshop Roma, 3-4 December 2012 Co-ordinator:

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  1. ESSnet on Measuring Global Value Chains ESSnet workshop Roma, 3-4 December 2012 Co-ordinator: Peter Bøegh Nielsen, Statistics Denmark pbn@dst.dk

  2. ESSnet Measuring Global Value Chains Globalisation indicators Methodological development and support for International Organisation and Sourcing of Business Functions survey Methodological development and support for Micro Data Linking project Linking of FATS statistics with Business Registers Analysis and dissemination

  3. What is Micro Data Linking? Matching of statistical registers at the level of the statistical unit. In this case enterprise level. Validation of the statistical units presnet in the different statistical registers (Are we talking about the same units?) Combining relevant variables from the differents registers at enterprise level in new data sets.

  4. Reasons for micro data linking Establish new knowledge without increasing the respondent burden Add value to already collected data by integrating the different registers Fine tune surveys by focusing on collecting information which is not available from existing statistical registers

  5. Micro data linking: addressing the stove pipe approach FDI Foreign trade (Services) Foreign trade(Goods) FATSInward FATSOutward Internationalsourcing Business Register Research, Development and innovation Accounts statistics

  6. Micro data linking: future projects R&D Statistics R&D personnelR&D expenditures Structural Business statistics Turnover Value added Employment Foreign Trade Statistics Imports of goods Exports of goods Business Register Unique enterprise id no FATS Statistics Nationality of ownership Foreign affiliates Innovation Statistics Type of innovation Int’l organisation and sourcing of business functions Functions sourced Destination for sourcing

  7. Project phases Establishing national longitudinal data sets with a harmonised structure and contents of variables from the statistical registers in question. Running of SAS programs based on a harmonised syntax. Consequently, no micro data will be exchanged but only tabular data as output of this exercise. Provision of policy relevant analytical outputs based on new information on economic globalisation and the impact on e.g. employment and trade patterns

  8. Project design

  9. Control Group Extraction of control group Weightedmatching keep most information in the data no problem with insufficient population for the control group Criteria(on the basis of the latestyear) NACE section International activity (foreign affiliates, sourcing) Foreign trade in goodsfor manufacturingenterprises

  10. Analytical approaches

  11. Employment trends by function sourced internationally (Denmark, 2000-2007) Median values of full-time equivalent number of employees

  12. Business functions Core business function Production of final goods or services intended for the market / for third parties carried out by the enterprise and yielding income Support business functions Support business functions (ancillary activities) are carried out in order to permit or facilitate production of goods or services intended for the market / for third parties by the enterprise Distribution and logistics Marketing, sales and after sales services ICT services Administrative and management functions Research & development, engineering and related technical services Other support functions

  13. Impact analysis. Effects of International sourcing on domestic employment. Case: The Netherlands Employment in enterprises grows slower as a result of international sourcing activities. Conclusion: international sourcing has negative impact on employment

  14. Using micro data linking as input for classification of globalised enterprises

  15. Conclusions (1) 1) Micro Data Linking is an efficient way to produce new statitical information without surveying 2) Relative high matching rates indicates micro data linking is feasible 3) But never total match due to demographic events such as deaths, change in type of ownership etc. 4) The set-up with identical data sets stored in the NSIs has worked well 5) The approach of sharing of common and centrally developed sas programmes worked excellent

  16. Conclusions (2) How to deal with demographic events? Mergers and acquisitions vs. organic growth Need for co-ordination of samples across surveys? Size of population can hamper micro data-linking Which statistical unit is the most appropriate for globalisation statistics? Enterprise vs. Enterprise group

  17. Thank you!

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