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Geography of inventive activity in OECD regions

Geography of inventive activity in OECD regions. Stefano Usai CRENoS, University of Cagliari 29 June 2009 DIMETIC Summer School, Pecs.

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Geography of inventive activity in OECD regions

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  1. Geography of inventive activityin OECD regions Stefano Usai CRENoS, University of Cagliari 29 June 2009 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

  2. Technological progress as an engine of growth Geography of innovation in OECD regions

  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 Geography of innovation in OECD regions

  4. 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 Geography of innovation in OECD regions

  5. 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 Geography of innovation in OECD regions

  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. Geography of innovation in OECD regions

  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, 2007. *with heterogenous datasets Never done for the whole of developed countries with a homogenous dataset Geography of innovation in OECD regions

  8. 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. Geography of innovation in OECD regions

  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… Geography of innovation in OECD regions

  10. Moreno et al (2005): Main results • 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 Geography of innovation in OECD regions

  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) Geography of innovation in OECD regions

  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 Geography of innovation in OECD regions

  13. 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 Geography of innovation in OECD regions

  14. Geography of innovation in OECD regions

  15. Geography of innovation in OECD regions

  16. http://stats.oecd.org/ Geography of innovation in OECD regions

  17. Geography of innovation in OECD regions

  18. http://stats.oecd.org/OECDregionalstatistics/ Geography of innovation in OECD regions

  19. Territorial grids by country Geography of innovation in OECD regions

  20. Geography of innovation in OECD regions

  21. 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 Geography of innovation in OECD regions

  22. 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 Geography of innovation in OECD regions

  23. 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 Geography of innovation in OECD regions

  24. Regions in ourdatabase

  25. Geographical distribution of innovative activity Geography of innovation in OECD regions

  26. Sector distribution of innovative activity Still to be done Geography of innovation in OECD regions

  27. OECD: PCT per million Population, 1998-2000 Geography of innovation in OECD regions

  28. OECD: PCT per million Population, 2002-2004 Geography of innovation in OECD regions

  29. Europe: PCT per million, 1998-2000 Geography of innovation in OECD regions

  30. Europe: PCT per million, 2002-2004 Geography of innovation in OECD regions

  31. North America: PCT per million, 1998-2000 Geography of innovation in OECD regions

  32. North America: PCT per million, 2002-2004 Geography of innovation in OECD regions

  33. Asia/Pacific: PCT per million, 1998-2000 Geography of innovation in OECD regions

  34. Asia/Pacific: PCT per million, 2002-2004 Geography of innovation in OECD regions

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