Geography of inventive activity in OECD regions

Geography of inventive activityin OECD regions

Stefano UsaiCRENoS, University of Cagliari

29 June 2009DIMETIC Summer School, Pecs

Thanks to a contribution by OECD, Directorate for Science Technology and Industry within the research project on THE IMPACT OF BUSINESS STRUCTURES AND STRATEGIES ON THE DEGREE AND PATTERNS OF INNOVATION AT REGIONAL LEVEL

Thanks to a contribution by OECD, Directorate for Science Technology and Industry within the research project on THE IMPACT OF BUSINESS STRUCTURES AND STRATEGIES ON THE DEGREE AND PATTERNS OF INNOVATION AT REGIONAL LEVEL

21/04/23 Geography of innovation in OECD regions

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Technological progress as an engine of growth

PCT-GDP per capita 1998-2000

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PCT-GDP per capita 2002-2004

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Research line

• Technological activity is acknowledged as the main engine of growth and we contribute in investigating on how this engine works at the regional level

• First systematic, albeit preliminary, attempt to analyse comparatively the processes of knowledge creation and dissemination across regions (and possibly in the future also sectors) in OECD countries


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TABLE OF CONTENTS

• 1 Introduction• 2 Theoretical and empirical background• 3 Some methodological and data issues• 4 Descriptive statistics

– 4.1 Spatial concentration– 4.2 Patents and other variables– 4.3 Sector Analysis

• 5 Econometric estimation– Cross region KPF– Cross region-industry KPF

• 6 Conclusions and Policy implications• 7 Appendix


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Main Objectives

• To estimate a Knowledge Production Function (KPF) at the regional level– (and later at the regional-industry)

• We assess the importance of local and external factors and among them knowledge spillovers (both pecuniary and technological) in facilitating innovative activity

• We also assess the importance of geographical proximity


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The literature behind us/1

• From a theoretical point of view: knowledge and technological progress are engines of economic dynamics in most endogenous growth models (since Romer, 1986). In the spatial context this implies that local growth depends on

– the amount of technological activity which is carried out locally (depending on several factors among which internal technological spillovers)

– the ability to exploit technological achievements from outside, that is external technological spillovers (through several channels)

• In this respect geographical (Glaeser et al, 1992; Henderson, 1997, Paci and Usai, 2000) and technological (Keller, 2000, Verspagen, 2000, Paci and Usai, 2005) proximity have been considered and proved relevant.


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• From an empirical point of view: a useful starting point is the Knowledge Production Function (KPF) originally formalised by Griliches, 1979, and mainly applied at the firm level and refocused by Jaffe, 1989, to study knowledge spillovers from university to firms at the local level

• Empirical estimations of general KPF have been carried out for different levels of aggregation:– For the US case: Acs et al, 1994; Audretsch and Feldman, 1996;

Carlino et al, 2007; O hUchallain and Leslie, 2007; Soon and Storper, 2007

– For the EU case: Maurseth and Verspagen, 1999; Bottazzi and Peri, 2003; Moreno, Paci and Usai, 2005, 2006a, 2006b, Rodriguez Pose and Crescenzi, 2007

– For the US and the EU together*: Crescenzi, Rodriguez-Pose and Storper, 2007.

*with heterogenous datasets

Never done for the whole ofdeveloped countries

with a homogenous dataset


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The literature behind us, that is ourselvesMoreno, Paci and Usai (2005)

EPO data on EU regions• Agglomeration economies are positively and

significantly related to innovative activity.

• RD expenditure has a positive and significant impact

• GDP per capita impact is always positive and significant.

• Country dummies are mostly significant signalling the presence of institutional differences and possibly national systems of innovation.


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Moreno, Paci and Usai (2005): Main conclusions

• Clusters of regional innovative systems based on different specialisations have formed across Europe

• They are within national innovation systems: different paths for each country

• They are getting stronger and bigger, thanks to spatial dependence

• All in all, it is clear that sector and regional dimension should be combined to have a clear picture of innovation distribution and dynamics across countries…


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• Spatial autocorrelation is often present– It is almost always positive– It goes up to second level of contiguity (or up to

250 kms)

• Technological proximity matrix does not give rise to spatial autocorrelation

• Only when the technological dimension is combined to the geographical one results are again significant

Moreno et al (2005): Main results


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Feldman and Audretsch, 1999

Paci and Usai, 2000

Massard and Riou, 2002 Greunz, 2004

USA Italy France Europe

Dependent variable

no. of innovation in sector j and city i

no. of EPO patents per capita in sector j and local labour system i

no. of EPO patents in industry j and department i

no. of EPO patents in sector j and region i

specialisation negative positive negative positive

diversity - positive negative positive

data panel panel panel+sector panel

Empirical estimations of KPF at the regional-industry level have been just a few

Moreno-Paciand Usai

(2006)


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Moreno et al (2006): Main results for EU regions

• The role of technological specialisation is significative and positive in many sectors– Contrary to results for US and France (but for some

sectors)

• Such a role is deepening along time in most sectors– Contrary to specialisation in production: there is less

delocalisation processes in innovation. • Diversity is almost always positive but never

significant– Contrary to most previous analyses…but for results for

France…

Spatial autocorrelation is often present


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OECD Regional Database (ORDB)/1

• ORDB provides quantitative information on socio-economic issues (demographics, economy and labour market, social issues) for potentially 2014 regions within 30 OECD member countries

• This is one of the first implementation and therefore CRENoS has compared ORDB with respect to national and international sources and has integrated and corrected the database

• Innovative activity is measured both with input and output indicators, among the latter patents

• We concentrate on the latter and in particular on Patent Cooperation Treaty (PCT) applications...but before that


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http://stats.oecd.org/


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http://stats.oecd.org/OECDregionalstatistics/


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Country Large Regions (TL2) Small Regions (TL3)Australia 8 States/Territories 60 Statistical Divisions

Austria 9 Bundesländer35 Gruppen von Politischen Bezirken

Belgium 3 Régions 11 Provinces

Canada 12 Provinces and Territories 288 Census Divisions

Czech Republic 8 Groups of Kraje 14 Kraje

Denmark 3 Regions 15 Amter

Finland 5 Suuralueet 20 Maakunnat

France (without DOM-TOM) 22 Régions 96 Départements

Germany 16 Länder97 Spatial planning regions (groups of Kreise)

Greece4 Groups of Development regions

13 Development regions

Hungary 7 Tervezesi‑statisztikai regio 20 Megyek (+Budapest)

Iceland 2 regions 8 Landsvaedi

Ireland2 Groups Regional Authority Regions

8 Regional Authority Regions

Italy 21 Regioni 103 Province

Japan 10 Groups of prefectures 47 Prefectures

Territorial grids by countryTerritorial grids by country


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Country Large Regions (TL2) Small Regions (TL3)

Korea 7 Regions16 Special city, Metropolitan area and Province

Luxembourg 1 State 1 StateMexico 32 Estados 209 Grupos de MunicipiosNetherlands 4 Landsdelen 12 Provinces

New Zealand2 Groups of regional Councils

14 Regional Councils

Norway 7 Landsdeler 19 FylkerPoland 16 Voïvodships 45 Subregions

Portugal5 Comissaoes de coordenaçao regional + 2 Regioes autonomas

30 Grupos de Concelhos

Slovak Republic 4 Zoskupenia Karajov 8 KrajSpain 19 Comunidades autonomas 52 ProvinciasSweden 8 Riksomraden 21 LänSwitzerland 7 Grandes régions 26 CantonsTurkey 26 Regions 81 Provinces

United Kingdom12 Government Office Regions + Countries

133 groups of authorities or districts

United States 51 States 179 BEA Economic Areas


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OECD Regional Database (RDB)/2

• PCT provide a unified preliminary procedure for filing patent applications to protect inventions in each of its Contracting States.

• PCT procedure is costly and a step ahead the national award, it is assumed that most innovations are valuable ones.

• Comparing PCT and TPF (triadic patent families):– TPF are less numerous (they share one or more priorities at

USPTO, JPTO, EPO)– Both indexes do not suffer from home-bias– The latter provides a stronger profit-based indicator for an

international report even though both refer to valuable inventions

– PCT permit a wider perspective and its regionalisation is more straightforward


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OECD Regional Database (RDB)/3

• Macro areas: Europe, Asia/Pacific and North America.• Countries: 30 countries• Regional level (tl2 and tl3)

– Most of this report and the econometric analysis is based on TL2

– The regions of OECD are 324 (some countries at TL0 included)

• Temporal dimension: (1998-2000 and 2002-2004)• Sectoral level: (potentially 44 NACE-ISIC sectors)

• Main indicator:– Absolute value of PCT (around 600,000 in total)– PCT per million population


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Some features of the RDB

• PCT provide a measure which is of a sufficiently homogenous quality: potentially highly remunerative innovations. Indicator for both product and process innovations

• Medium time span (potentially long): three-year averages to smooth data

• Use of the inventor’s residence instead of applicant’s residence.

• Specific treatment of multiple inventors• Use of “Schmlook et al.” Technology Concordance (still

to be done)– Such a concordance uses the probability distribution of each

IPC across industries of manufacture in order to attribute each patent proportionally to the different sectors where the innovation may have originated

Regions in ourdatabase

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OCSE

Nation

Australia 8 TL2 962,919 2,484,040

Austria 9 TL2 9,319 902,893

Belgium 3 TL2 10,173 3,458,922

Canada 12 TL2 766,934 2,639,336

Czech Republic 8 TL2 9,859 1,276,004

Denmark 1 TL0 43,098 5,389,733

Finland 5 TL2 67,629 1,042,780

France 22 TL2 24,726 2,735,994

Germany 41 TL2 8,708 2,012,461

Greece 4 TL2 32,907 2,756,083

Hungary 7 TL2 13,290 1,447,386

I celand 1 TL0 102,696 290,661

I reland 1 TL0 69,797 3,993,767

I taly 21 TL2 14,349 2,745,044

J apan 10 TL2 37,758 12,758,000

Korea 7 TL2 14,209 6,835,549

Luxembourg 1 TL2 2,586 449,733

Mexico 1 TL0 1,959,248 101,970,271

Netherlands 4 TL2 8,471 4,054,683

New Zealand 1 TL0 277,039 4,002,267

Norway 7 TL2 43,928 650,180

Poland 16 TL2 19,543 2,387,900

Portugal 7 TL2 13,135 1,491,029

Slovak Republic 4 TL2 12,259 1,345,067

Spain 19 TL2 26,631 2,210,705

Sweden 8 TL2 55,168 1,119,863

Switzerland 7 TL2 5,898 1,052,053

Turkey 1 TL0 769,603 70,228,333

United Kingdom 37 TL2 6,573 1,610,381

United States 51 TL2 119,774 5,702,560

Total 324 94,757 3,556,366

average region (km2)

average region (population 2002-04)Regions Level


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Geographical distribution of innovative activity

OECD

Nations

Num. Of Regions 1998-2000 2002-2004 var % Nations

Num. Of Regions 1998-2000 2002-2004 var %

Australia 8 78.7 94.2 19.8 Korea 7 27.5 69.1 151.4

Austria 9 77.4 106.2 37.2 Luxembourg 1 112.1 70.6 -37.0

Belgium 3 72.1 74.9 4.0 Mexico 1 0.8 1.3 56.7

Canada 12 61.1 73.6 20.4 Netherlands 4 158.7 160.1 0.9

Czech Republic 8 7.0 7.0 0.0 New Zealand 1 68.1 84.8 24.5

Denmark 1 150.1 184.0 22.6 Norway 7 111.1 98.2 -11.6

Finland 5 255.5 228.3 -10.6 Poland 16 1.6 2.1 27.4

France 22 68.6 82.0 19.5 Portugal 7 2.3 1.6 -30.7

Germany 41 143.5 172.5 20.2 Slovak Republic 4 4.9 5.4 9.9

Greece 4 4.2 3.7 -11.7 Spain 19 13.5 16.8 24.2

Hungary 7 14.6 15.1 3.8 Sweden 8 285.3 204.9 -28.2

Iceland 1 103.8 142.4 37.2 Switzerland 7 175.0 233.0 33.2

Ireland 1 51.2 66.2 29.3 Turkey 1 1.0 1.9 93.0

Italy 21 25.9 34.7 34.0 United Kingdom 37 69.0 67.4 -2.3

J apan 10 62.2 129.5 108.0 United States 51 125.2 141.2 12.7

Total 324 2331.9 2572.6 10.3

PCT_ per million Population PCT_ per million Population


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Sector distribution of innovative activity

Still to

be

done


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OECD: PCT per million Population, 1998-2000


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OECD: PCT per million Population, 2002-2004


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Europe: PCT per million, 1998-2000


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Europe: PCT per million, 2002-2004


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North America: PCT per million, 1998-2000


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North America: PCT per million, 2002-2004


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Asia/Pacific: PCT per million, 1998-2000


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Asia/Pacific: PCT per million, 2002-2004

Documents

Geography of inventive activity in OECD regions