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![Page 1: The geography of innovation and growth: An introduction and overview by Attila Varga Department of Economics and Regional Studies and Center for Research.](https://reader036.fdocuments.in/reader036/viewer/2022083005/56649f1f5503460f94c36ed9/html5/thumbnails/1.jpg)
The geography of innovation and growth:
An introduction and overview
by
Attila Varga
Department of Economics and Regional Studiesand
Center for Research in Economic Policy (GKK)Faculty of Business and Economics
University of Pécs, Hungary
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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)
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Outline
• Introduction• Technological progress, spatial structure and
macroeconomic growth: An empirical modeling framework
• Integrating agglomeration effects to development policy modeling
• Concluding remarks
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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
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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
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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 and Venables 1999, Fujita and Thisse 2002)- „Evolutionary Economic Geography” (EEG) (Boschma 2007)
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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
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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
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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)
• EMPIRICAL integration: very few work (Ciccone and Hall 1996, Varga and Schalk 2004, Acs and Varga 2005)
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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)
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• 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)
II. Technological progress, spatial structure and macroeconomic growth: An empirical modeling
framework
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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)
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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 2005Italy: Audretsch and Vivarelly 1994, Capello 2001
France: Autant-Bernard 1999 Austria: Fischer and Varga 2003 Germany: Fritsch 2002
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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
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Empirical research on geography, technology and growth: 1986-2004
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1986-2004: 253 papers on the geography of knowledge spillovers
journal articles: 175
books, book chapters, working papers: 78
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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