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Kiseleva - Do national borders slow down knowledge diffusion

Parallel session 2, Monday 19 September 2016

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Kiseleva - Do national borders slow down knowledge diffusion

  1. 1. Centraal Planbureau Do national borders slow down knowledge diffusion within new technological fields? The case of big data in Europe OECD Blue Sky Forum September 19th, 2016 Tatiana Kiseleva Ali Palali Bas Straathof Netherlands Bureau for Economic Policy Analysis
  2. 2. Centraal Planbureau What is `big data’? `Big data’ refers to data sets that are so large and complex that traditional data processing and analysis tools are inadequate
  3. 3. Centraal Planbureau The number of big data patents grows fast 0 500 1000 1500 2000 2500 3000 3500 2002 2004 2006 2008 2010 2012 2014 Earliest Priority YearSource: Thomson Reuters
  4. 4. Centraal Planbureau Big Data technologies are general purpose technologies: - affect entire economy; - great societal impact; Banks Chemicals, rubber, plastics, non-meta.. Construction Education, Health Gas, Water, Electricity Hotels & restaurants Insurance companies Machinery, equipment, furniture, recy.. Metals & metal products Other services Post & telecommunications Public administration & defense Publishing, printing Transport Wholesale & retail trade Source: Thomson Reuters Use of big data technologies
  5. 5. Centraal Planbureau Only 1% of all big data patents come from Europe Sourse: UKIPO United States 44% China 30% Japan 12% EPO 1% All Others 8%
  6. 6. Centraal Planbureau Research focus Is Europe lagging behind in big data innovation? Policy relevance: Lagging behind in a general purpose technology can affect productivity in many sectors!
  7. 7. Centraal Planbureau Approach Patents - indicator of innovative activities Patent citations - measure of technology diffusion Time between cited and citing patent – speed of diffusion Control for other factors
  8. 8. Centraal Planbureau Issues with patents citations Differences in regulations across patent offices  We restrict ourselves to patents filed to USPTO  We use ICT patents as control group to correct for administrative home bias Citation delays associated with the technological field ICT, and not BD directly  We use ICT patents as control group
  9. 9. Centraal Planbureau Data 1. PATSTAT – the EPO Worldwide Patent Statistical Database bibliographic data (application data, inventor’s info etc), citations and family links of 90 million applications of more than 80 countries. 2. Derwent World Patent Index - Thomson Reuters bibliographic data, technological content, sectorial data 3. Orbis – Bureau van Dijk patent ownership, characteristics of patent’s owners
  10. 10. Centraal Planbureau Identification of `big data’ patents The term `big data’ is relatively new fuzzy definitions Two definitions 1. Thomson Reuters (DWPI) (yields ~44K patents) core analysis 2. UKIPO (yields ~6,6K patents) robustness check `Big data’ patents are identified by IPC codes and `keywords’
  11. 11. Centraal Planbureau Cited patents 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Non Big Data ICT patents Big Data patents USA+ROW+EU EU+ROW USA+EU USA+ROW EU ROW USA 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Non Big Data ICT patents Big Data patents Citing patents
  12. 12. Centraal Planbureau Estimation strategy  We use the multiple spel mixed proportional hazard model to estimate the diffusion lag (citation duration)  We control for • technological distance between patents • firms charsteristics of the owner (size, number of patents, etc) • cross-firm citations • cross-border citations • patents quality (fixed effects)
  13. 13. Centraal Planbureau Results Variable Cox Fixed effects Fixed effects +Censoring Cross-border (CB) - 0.092*** (0.005) 0.006 (0.007) 0.007 (0.007) Big Data (BD) 0.004 (0.006) - 0.092*** (0.009) - 0.094*** (0.010) CB • BD 0.048*** (0.014) - 0.004 (0.018) -0.008 (0.019) Tech.distance - 0.312*** (0.008) - 0.309*** (0.012) - 0.314*** (0.013) Within firm 0.183*** (0.004) 0.226*** (0.006) 0.236*** (0.006) *** p<0.001
  14. 14. Centraal Planbureau Results for the disentangled cross border effect CB EU → USA EU → ROW EU → USA+ROW USA → EU USA → ROW USA → EU+ROW ROW → EU ROW → USA ROW → EU+USA USA + EU → ROW USA + ROW → EU EU + ROW → USA
  15. 15. Centraal Planbureau Results for the disentangled cross border effect CB EU → USA EU → ROW EU → USA+ROW USA → EU USA → ROW USA → EU+ROW ROW → EU ROW → USA ROW → EU+USA USA + EU → ROW USA + ROW → EU EU + ROW → USA CB • BD USA → EU •BD ROW → EU • BD USA + ROW → EU •BD - 0.053** (0.017) - 0.092** (0.028) - 0.130** (0.046) 0.028 (0.053) 0.324** (0.124) - 0.230 (0.156) ** p<0.01
  16. 16. Centraal Planbureau Discussion of the results  Big data technologies diffuse slower than ICT  No delay in `big data’ innovation in Europe compared to ICT  Within-firm citations are faster (Griffith et al. 2014)  Citation delay increases with the technological distance (Griffith et al. 2014)

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Parallel session 2, Monday 19 September 2016

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