DIMETIC Pécs 2009 The geography of innovation and growth: An introduction and overview by

1. DIMETIC Pécs 2009 The geography of innovation and growth: An introduction and overview by Attila Varga Department of Economics and Regional Studies 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?

3. I. Introduction • Why should we care about space? - Transport costs(can be integrated relatively easily) - Agglomeration externalities (require a different approach) • Policy relevance (EU)

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

5. 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, 2009) 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

6. 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

7. 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)

8. 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

9. 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, Anselin, Varga and Acs 1997) • Empirical litarature: US, European, Asian analyses • Common finding: much of knowledge flows in technological change are spatially bounded (though differences with respect to industry, stage of innovation, institutional proximity exist, related variety important) • Not connected to growth and to the explanation of spatial economic structure

10. 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)

11. 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)

12. II. Technological progress, spatial structure and macroeconomic growth: An empirical modeling framework • Y = AKαLβ • 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 φ: “codified knowledge spillovers parameter” - reflects spillovers with unlimited spatial accessibility : the “research productivity 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)

13. 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)

14. 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

15. II. Technological progress, spatial structure and macroeconomic growth: An empirical modeling framework To test Eq.2 and Eq. 3: • Some of the empirical studies test the effects SEPARATELY (Jaffe 1989, Bania et al 1992, Anselin, Varga, Acs 1997a,b, Varga 2000, 2001) • The dynamic cumulative process modeled econometrically (Varga, Pontikakis, Chorafakis 2009)

18. Regional R&D productivity in competitive research

19. Regional R&D productivity in pre-competitive research

22. II. Technological progress, spatial structure and macroeconomic growth: An empirical modeling framework • Empirical integration of micro to macro (Eqs. 4-6): a real research challenge: needs an integrated macro-regional approach (back to this on Friday afternoon)

23. Research questions related to the empircal model: The structure of the week • The geography of innovation: knowledge interactions in space • Stefano USAI • Francesco LISSONI • How to explain the geographical structure of innovation and the resulting growth? • 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: • Frank van OORT • Attila VARGA

24. The structure of the week