1. USE OF E- COMMERCE DATA International comparisons and a micro-perspective Michael Polder, OECD-STI/EAS Business Statistics User Event: How E-commerce is changing the shape of business, October 8 2015, BIS conference centre, London, UK

2. A sketch of messages from recent OECD publications From statistics to economic analysis: – Using ICT survey micro-data to investigate the relation between E-commerce and competition E-commerce, innovation, and productivity – Cross-country analysis with micro-data Overview

3. A new STI Scoreboard coming up… 2015 To be released October 20

4. Relative to broadband and website, e-commerce adoption is still fairly low … and there is substantial variation between countries Sketches from recent OECD publications

5. Magnitude of cross-border e-commerce is limited … pointing at serious obstacles to ‘go international’ Sketches from recent OECD publications

6. Magnitude of cross-border e-commerce is limited … similarly for online purchases by individuals … pointing at a lack of confidence and trust Sketches from recent OECD publications

7. Online purchases by individuals are up… But still substantial country variation … and a gap between young and old Sketches from recent OECD publications

8. A new development: ‘m-commerce’ and ‘m-payment’ Increasing importance and policy interest … But measurement? Sketches from recent OECD publications

9. Relatively few firms are engaging in e-commerce … especially cross-border e-commerce Likewise, few individuals buy online from abroad However, overall, online purchasing is increasing … although a significant age gap remains Overall there is still a substantial amount of cross-country variation in the adoption of e-commerce by both firms and households Sketches from recent OECD publications

10. ICT usage by enterprises Relation of e-commerce with – Competition – Innovation – Productivity Need firm-level analysis – It is (too) often forgotten that the micro-data underlying national statistics is a valuable product! Use of e-commerce data for economic analysis

11. Background – Consequences of online trading: Lower search cost Lower transaction cost Markets become more transparant – E.g. Brynjolfsson and Smith (2000, Management Science): “Frictionless markets” Increases (price) competition Motivates firms to operate cost efficiently E-commerce and competition

12. Data (Netherlands only) – ICT usage and e-commerce enterprise survey – Structural Business Statistics – Innovation Survey – Period: 2002-2010 E-commerce and competition

13. E-commerce and competition

14. E-commerce and competition

15. Markups lower in manufacturing relative to services, which indicates stronger competition in manufacturing Source: CBS (2015), ICT and Economic Growth.

16. E-commerce and competition Increases in e-sales and e- commerce in general have significantly lowered markups, in all sectors Source: CBS (2015), ICT and Economic Growth.

17. Background – Innovation is a driver of economic growth – Crépon-Duguet-Mairesse (CDM): Firms invest in R&D (innovation input) … this leads to knowledge generation (product innovation) … which ultimately results in increased business performance (productivity) – Variations: Griffith et al. (2004): product and process innovation Brynjolfsson et al: ICT investments and complementary organizational changes E-commerce and competition

18. E-commerce, innovation and productivity Innovation input R&D ICT Innovation output Product Process Organisational E-commerce Performance productivity

19. E-commerce, innovation and productivity Innovation input R&D ICT Innovation output Product Process Organisational E-commerce Performance productivity

20. Data (Netherlands only) – ICT usage and e-commerce enterprise survey – Structural Business Statistics – Innovation Survey – Period: 2004-2010 E-commerce and competition

21. E-commerce, innovation and productivity Manufacturing PRODUCTPROCESSORGANIZATIONALE-COMMERCE coef product innovation--0,447***0,100*0,112*** process innovation0,447***--0,425***-0,032* organizational innovation0,100**0,425***--0,036 e-commerce innovation0,112***-0,032*0,036-- broadband intensity0,160-0,1050,424***-0,008 R&D performer1,315***0,428***-- Services PRODUCTPROCESSORGANIZATIONALE-COMMERCE coef product innovation--0,626***0,239***0,106*** process innovation0,626***--0,459***0,055*** organizational innovation0,239***0,459***--0,062*** e-commerce innovation0,106***0,055***0,062***-- broadband intensity0,427***-0,0540,257***0,074* R&D performer1,134***0,640***--

22. E-commerce, innovation and productivity Manufacturingproductprocessorganizational e-commercen.s.COMP Servicesproductprocessorganizational e-commerceSUBSCOMP In terms of productivity gains: e-commerce and process innovation complement each other – That is: combination of both leads greater increase in productivity than the sum of their effects in isolation Same for e-commerce and organizational innovation Combination of product innovation with e-commerce does not have any excess productivity gains in manufacturing, and leads to lower gains in services (substitutes)

23. Background: – Comparability of micro-level studies – What is the impact of institutional setting, regulation, and policy? – Lack of available cross-country micro-data Cross-country analysis using micro-data

24. Source: Bartelsman, Hagsten and Polder (2015), forthcoming

25. ESSNet projects on data linking and ICT impact (ICT Impact, ESSLimit, ESSLait) 14 participating NSOs ‘Micro-moments database’ – Indicators based on ‘micro-aggregated’ data – … from linked EC, IS, PS, trade databases – … going beyond usual breakdowns of aggregate data Moreover: harmonized ‘distributed’ micro- datasets at various NSOs allow for remote execution type of empirical analysis Cross-country analysis using micro-data

26. Source: Bartelsman, Hagsten and Polder (2015), forthcoming

27. Examples: – Dispersion of productivity growth and ICT Productivity growth by country × time × industry … and ICT vs non-ICT intensive firms – Resource allocation: Employment growth by by country × time × industry … and by quartile of the firm-level productivity growth distribution Cross-country analysis using micro-data

28. Examples: – Dispersion of productivity growth and ICT Productivity growth by country × time × industry … and ICT vs non-ICT intensive firms – Resource allocation: Employment growth by by country × time × industry … and by quartile of the firm-level productivity growth distribution Cross-country analysis using micro-data

30. International comparability is in general hampered by differences in surveys between EU and non-EU and/or non-OECD countries frequency of the survey voluntary or compulsory nature of the survey coverage of subsamples, especially in small countries reference and recall periods treatment of outliers and multinationals ranges recorded in surveys sectoral coverage … Selected data issues

31. Micro-data analysis benefits from Increased coverage of firms over time Coordination of sampling design between surveys (e.g. innovation and ICT) Stability of definitions and concepts over time Harmonization of definition and concepts across surveys Increased international harmonization allows the analysis of micro-data in a cross-country setting Data issues

32. Any Questions?? Thank you for listening