Kiseleva - Do national borders slow down knowledge diffusion

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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)