kiseleva - do national borders slow down knowledge diffusion
TRANSCRIPT
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Do national borders slow down knowledge diffusion within new technological fields? The case of big data in Europe
OECD Blue Sky ForumSeptember 19th, 2016
Tatiana KiselevaAli Palali
Bas Straathof
Netherlands Bureau for Economic Policy Analysis
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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
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The number of big data patents grows fast
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 20140
500
1000
1500
2000
2500
3000
3500
Earliest Priority YearSource: Thomson Reuters
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Big Data technologies are general purpose technologies:
- affect entire economy;
- great societal impact;
BanksChemicals, rubber, plastics, non-
meta..Construction Education, Health Gas, Water, Electricity
Hotels & restaurants
Insurance companies
Machinery, equipment, furniture, recy..
Metals & metal products
Other services
Post & telecommuni-cations
Public administration & defense Publishing, printing
TransportWholesale & retail trade
Source: Thomson Reuters
Use of big data technologies
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Only 1% of all big data patents come from Europe
Sourse: UKIPOUnited States44%
China30%
Japan12%
EPO1%
All Others8%
South Korea
5%
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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!
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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
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Issues with patents citationsDifferences 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
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Data1. 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
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Identification of `big data’ patents
The term `big data’ is relatively new fuzzy definitions
Two definitions1. 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’
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Cited patents
Non Big Data ICT patents
Big Data patents
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
USA+ROW+EUEU+ROWUSA+EUUSA+ROWEUROWUSA
Non Big Data ICT patents
Big Data patents0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Citing patents
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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)
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ResultsVariable Cox Fixed effects Fixed effects
+CensoringCross-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
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Results for the disentangled cross border effect
CB
EU → USA EU → ROWEU → USA+ROWUSA → EUUSA → ROWUSA → EU+ROWROW → EUROW → USAROW → EU+USAUSA + EU → ROWUSA + ROW → EUEU + ROW → USA
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Results for the disentangled cross border effect
CB
EU → USA EU → ROWEU → USA+ROWUSA → EUUSA → ROWUSA → EU+ROWROW → EUROW → USAROW → EU+USAUSA + EU → ROWUSA + ROW → EUEU + ROW → USA
CB • BD
USA → EU •BDROW → EU • BDUSA + 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
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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)