The geography of innovation and growth: An introduction and overview by Attila Varga

1. The geography of innovation and growth: An introduction and overview by Attila Varga Department of Economics and Regional Studies and Center for Research in Economic Policy (GKK) Faculty of Business and Economics University of Pécs, Hungary

2. I. Introduction • A-spatial mainstream economic theory • K, L and A only? How about their spatial arrangements? • Why should we care about space? - Transport costs(can be integrated relatively easily) - Agglomeration externalities (require a different approach) • Policy relevance (EU)

3. Outline • Introduction • Technological progress, spatial structure and macroeconomic growth: An empirical modeling framework • Integrating agglomeration effects to development policy modeling • Concluding remarks

4. II. Technological progress, spatial structure and macroeconomic growth Complex issue treated in four separate fields of economics: A. EGT: “Endogenous economic growth” models: endogenized technological change in growth theory (Romer 1986, 1990, Lucas 1986, Aghion and Howitt 1998) in Romer (1990): • for-profit private R&D • knowledge spillovers are essential in growth • rate of technical change equals rate of per-capita growth on the steady state • Simplistic explanation of technological progress, no geography

5. II. Technological progress, spatial structure and macroeconomic growth B. IS: „Systems of innovation”literature: innovation is an interactive process among actors of the system (Lundval 1992, Nelson 1993) actors of the IS: - innovating firms - suppliers, buyers - industrial research laboratories - public (university) research institutes - business services - “institutions” level of innovation depends on: - the knowledge accumulated in the system - the interactions (knowledge flows) among the actors - codified, non-codified (tacit) knowledge and the potential significance of spatial proximity - geography gets some focus, but IS does not say anything about growth

6. II. Technological progress, spatial structure and macroeconomic growth C. GE: “Geographical economics”models: - „New Economic Geography”(NEG): endogenized spatial economic structure in a general equilibrium model (Krugman 1991, Fujita, Krugman andVenables 1999, Fujita andThisse 2002) - „Evolutionary Economic Geography” (EEG) (Boschma 2007)

7. II. Technological progress, spatial structure and macroeconomic growth In the New Economic Geography: - spatially extended Dixit-Stiglitz framework - increasing returns, monopolistic competition - spatial structure depends on some parameter conditions that determine the equilibrium level of centrifugal and centripetal forces - „cumulative causation” - C-P model by Krugman: still the point of departure - models quickly become complex: simulations if analytical solutions are not accessible - Technological change not explained (not even included until very recently), the study of its relation to growth is a recent phenomenon

8. II. Technological progress, spatial structure and macroeconomic growth D. GI: The „Geography of innovation” literature: the study of the spatial extent of knowledge flows in innovation (Jaffe 1989, Jaffe, Trajtenberg and Henderson 1993, Audretsch and Feldman 1996, Anselin, Varga and Acs 1997) • Empirical litarature: US, European, Asian analyses • Common finding: much of knowledge flows in technological change are spatially bounded • Not connected to growth and to the explanation of spatial economic structure

9. II. Technological progress, spatial structure and macroeconomic growth • IS, GE, EGT, GI: complements to each other in growth explanation, no theoretical integration (Acs-Varga 2002) • IS, GE, EGT, GI: building blocks of a framework to shape empirical research (Varga 2006) • Theoretical integration: endogenous growth and new economic geography (Baldwin and Forslid 2000, Fujita and Thisse 2002, Baldwin et al. 2003) • EGT, IS, GE, GI: methodological problems in THEORETICAL integration (dramatically diverging initial assumptions, different theoretical structures, research methodologies) • EMPIRICALintegration: very few work (Ciccone and Hall 1996, Varga and Schalk 2004, Acs and Varga 2005)

10. II. Technological progress, spatial structure and macroeconomic growth: An empirical modeling framework • Starting points („stylized facts”): • Technological change is a collective process that depends on accumulated knowledge and interactions (IS) • Technological change is the simple most important determinant of economic growth (EG) • Codified and tacit knowledge: different channels of spillovers (GI) • Centripetal and centrifugal forces shape geographical structure via cumulative processes (GE) • The resulting geographic structure is a determinant of the rate of growth (NEG)

11. II. Technological progress, spatial structure and macroeconomic growth: An empirical modeling framework • Y = AKαLβ(EG) • The Romer (1990) equation as in Jones (1995) dA =  HAAφ, - HA: the number of researchers(“person-embodied”, knowledge component of knowledge production) - A: the total stock of technological knowledge (codified knowledge component of knowledge production in books, patent documents etc.) - dA: the change in technological knowledge - : the “research productivity parameter”(0<<1) φ: “codified knowledge spillovers parameter” - reflects spillovers with unlimited spatial accessibility : the “research spillovers parameter” - reflects localized knowledge spillover effects (GI) - regional and urban economics and the new economic geography suggest: changes with geographic concentration of economic activities (depending on the balance between positive and negative agglomeration economies)

12. II. Technological progress, spatial structure and macroeconomic growth: An empirical modeling framework Eq.1 Regional knowledge production: Kr = K (RDr, URDr, Zr) A cumulative process described by Eqs. 2 and 3 (dynamic agglomeration effects: Eq.2 (Static) agglomeration effect in R&D effectiveness: ∂Kr/∂RDr = f (RDr, URDr, Zr) Eq.3 R&D location: dRDr = R(∂Kr/∂RDr) Eq.4 Geography and :  =  (GSTR(HA)) Eq.5 dA =  HA  Aφ Eq.6 dy/y = H(dA, ZN)

13. II. Technological progress, spatial structure and macroeconomic growth: An empirical modeling framework • To test Eq.1: most of the empirical models are based on the „knowledge production framework” log (K) =  +  log(R) +  log(U) + log(Z) + • The KPF framework to study localized knowledge spillovers USA: Jaffe 1989 Acs, Audretsch and Feldman 1991 Anselin, Varga and Acs, 1997 Varga 1998 Feldman and Audretsch 1999 Acs, Anselin and Varga 2002 EU: Moreno-Serrano, Paci, Usai 2005 Italy: Audretsch and Vivarelly 1994, Capello2001 France: Autant-Bernard 1999 Austria: Fischer and Varga 2003 Germany: Fritsch 2002

14. II. Technological progress, spatial structure and macroeconomic growth: An empirical modeling framework To test Eq.2 and Eq. 3: • empirical studies test the effects SEPARATELY (Jaffe 1989, Bania et al 1992, Anselin, Varga, Acs 1997a,b, Varga 2000, 2001) • The dynamic cumulative process is not modeled empirically • Empirical integration of micro to macro (Eqs. 4-6): a real research challenge

15. Empirical research on geography, technology and growth: 1986-2004 1986-2004: 253 papers on the geography of knowledge spillovers journal articles: 175 books, book chapters, working papers: 78

16. Research questions related to the empircal model: The structure of the week • What are the main channels of knowledge spillovers? – the role of entrepreneurship • Zoltan ACS • To what extent knowledge flows are spillovers? • Francesco LISSONI • How to explain the geographical structure of economies? • EEG: Ron BOSCHMA, Giulio BOTTAZZI • NEG: Mark THISSEN • How new product varieties emerge and how they are related to economic growth? • Pier Paolo SAVIOTTI • Empirical research methodology: • Modeling the development of spatial economic structure via SCGE modeling: Mark THISSEN • Accounting for spatial dependence in econometric models via spatial econometrics: Rosina MORENO • Integrating the geography of innovation to policy modeling: Attila VARGA