Geography of inventive activity in OECD regions Stefano Usai CRENoS, University of Cagliari 8 july 2010 DIMETIC 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

14/11/2015 Geography of innovation in OECD regions Pag.2 Technological progress as an engine of growth

14/11/2015 Geography of innovation in OECD regions Pag.3 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

14/11/2015 Geography of innovation in OECD regions Pag.4 TABLE OF CONTENTS 1Introduction 2Theoretical and empirical background 3Some methodological and data issues 4Descriptive statistics for patents and citations –Spatial concentration 5Econometric estimation –Cross region Knowledge Production Function (KPF) –Across regions Knowledge Gravity Model (KGM) 6(Many) Other things to do

14/11/2015 Geography of innovation in OECD regions Pag.5 Main Objectives To estimate a Knowledge Production Function (KPF) at the regional level –(and later at the regional-industry) To estimate a Knowledge Gravity Model (KGM) at the regional level (also for some sectors) 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

14/11/2015 Geography of innovation in OECD regions Pag.6 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.

14/11/2015 Geography of innovation in OECD regions Pag.7 The literature behind us/2 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, *with heterogenous datasets Never done for the whole of developed countries with a homogenous dataset

14/11/2015 Geography of innovation in OECD regions Pag.8 The literature behind us, that is ourselves Moreno, 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.

14/11/2015 Geography of innovation in OECD regions Pag.9 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…

14/11/2015 Geography of innovation in OECD regions Pag.10 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

14/11/2015 Geography of innovation in OECD regions Pag.11 The literature behind us/3 Empirical estimations of KPF at the regional- industry level have been just a few Moreno-Paci and Usai (2006)

14/11/2015 Geography of innovation in OECD regions Pag.12 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

14/11/2015 Geography of innovation in OECD regions Pag.13

OECD Regional Database (ORDB)/1 The OECD Regional Database provides a unique set of comparable statistics and indicators on about 2000 regions in 30 countries. It currently encompasses yearly time-series for around 40 indicators of demography, economic accounts, labour market, social and innovation themes in the OECD member countries and other economies.OECD Regional Database Regions in OECD member countries have been classified according to two territorial levels (TL) to facilitate international comparability. The higher level (Territorial level 2) consists of macro-regions, while the lower level (Territorial level 3) is composed of micro-regions. Regions in OECD member countries 14/11/2015 Geography of innovation in OECD regions Pag.14

OECD Regional Database (ORDB)/2 In addition, OECD small regions (Territorial level 3) are classified according to their geography into predominantly rural, intermediate or predominantly urban. This typology of regions has been refined to take into account remoteness of rural regions: the extended typology comprises remote rural regions, rural regions close to a city, intermediate and predominantly urban regions. predominantly rural, intermediate or predominantly urbanextended typology The OECD metrodatabase provides statistics on 90 large metropolitan areas in the OECD countries and shows how these regions have changed over the past decade. OECD metrodatabaselarge metropolitan areas 14/11/2015 Geography of innovation in OECD regions Pag.15

14/11/2015 Geography of innovation in OECD regions Pag.16

14/11/2015 Geography of innovation in OECD regions Pag.17

14/11/2015 Geography of innovation in OECD regions Pag.18

14/11/2015 Geography of innovation in OECD regions Pag.19

14/11/2015 Geography of innovation in OECD regions Pag.20 CountryLarge Regions (TL2)Small Regions (TL3) Australia8 States/Territories60 Statistical Divisions Austria9 Bundesländer 35 Gruppen von Politischen Bezirken Belgium3 Régions11 Provinces Canada12 Provinces and Territories288 Census Divisions Czech Republic8 Groups of Kraje14 Kraje Denmark3 Regions15 Amter Finland5 Suuralueet20 Maakunnat France (without DOM-TOM)22 Régions96 Départements Germany16 Länder 97 Spatial planning regions (groups of Kreise) Greece 4 Groups of Development regions 13 Development regions Hungary 7 Tervezesi ‑ statisztikai regio 20 Megyek (+Budapest) Iceland2 regions8 Landsvaedi Ireland 2 Groups Regional Authority Regions 8 Regional Authority Regions Italy21 Regioni103 Province Japan10 Groups of prefectures47 Prefectures Territorial grids by country

14/11/2015 Geography of innovation in OECD regions Pag.21 CountryLarge Regions (TL2)Small Regions (TL3) Korea7 Regions 16 Special city, Metropolitan area and Province Luxembourg1 State Mexico32 Estados209 Grupos de Municipios Netherlands4 Landsdelen12 Provinces New Zealand 2 Groups of regional Councils 14 Regional Councils Norway7 Landsdeler19 Fylker Poland16 Voïvodships45 Subregions Portugal 5 Comissaoes de coordenaçao regional + 2 Regioes autonomas 30 Grupos de Concelhos Slovak Republic4 Zoskupenia Karajov8 Kraj Spain19 Comunidades autonomas52 Provincias Sweden8 Riksomraden21 Län Switzerland7 Grandes régions26 Cantons Turkey26 Regions81 Provinces United Kingdom 12 Government Office Regions + Countries 133 groups of authorities or districts United States51 States179 BEA Economic Areas

the OECD Patent Database fully covers: Patent applications to the European Patent Office (EPO) (from 1978 onwards); Patents granted by the US Patent and Trademark Office (USPTO) (from 1976 onwards); Patents filed under the Patent Co-operation Treaty (PCT), at international phase, that designate the EPO (from 1978 onwards); Patents that belong to Triadic Patent Families (OECD definition): i.e. sub-set of patents all filed at the EPO, at the Japanese Patent Office (JPO) and granted by the USPTO, protecting the same set of inventions. EPO and PCT patent counts are based on data received from the EPO (EPO Bibliographic database, patent published until November 2009). Series on Triadic patent families are mainly derived from EPO's Worldwide Statistical Patent Database (PATSTAT, September 2009). Regional data are based on OECD, REGPAT database, January /11/2015 Geography of innovation in OECD regions Pag.22

14/11/2015 Geography of innovation in OECD regions Pag.23 OECD Regional Database (ORDB)/3 PCT provide a unified preliminary procedure for filing patent applications to protect inventions in each of its Contracting States. patent applicationsinventions 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

14/11/2015 Geography of innovation in OECD regions Pag.24 OECD Regional Database for the KPF 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: ( and ) Sectoral level: (potentially 44 NACE-ISIC sectors) Main indicator: –Absolute value of PCT (around 600,000 in total) –PCT per million population

14/11/2015 Geography of innovation in OECD regions Pag.25 OECD Regional Database for the KGM It is difficult to keep track of knowledge flows: one way is through citations, which are provided under request by the OECD STI office Citations EPO on EPO We use only data on Europe for 22 countries (EU15 plus Slovak Republic, Poland, Hungary, Czech Republic, Turkey and Norway and Switzerland) It provides a dynamic picture for the period going from 1990 to 2000 Most importantly provides disaggregated estimations for some selected sectors, that is Chemicals, Machinery, Traditionals

14/11/2015 Geography of innovation in OECD regions Pag.26 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 our database 14/11/2015 Pag.27

14/11/2015 Geography of innovation in OECD regions Pag.28 Geographical distribution of innovative activity

14/11/2015 Geography of innovation in OECD regions Pag.29 OECD: PCT per million Population,

14/11/2015 Geography of innovation in OECD regions Pag.30 OECD: PCT per million Population,