From the Geography of Innovation to Development Policy Analysis: The GMRapproach Attila Varga Depart

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From the Geography of Innovation to Development
Policy Analysis The GMR-approachAttila
VargaDepartment of Economics and Regional
StudiesUniversity of Pécs,Faculty of Business
and EconomicsPécs, HungaryandEuropean
Commission-Joint Research CentreInstitute for
Prospective Technological Studies
(JRC-IPTS)Sevilla, SpainSEMINAR PRESENTATION
AT THE FREEMAN CENTRE, UNIVERSITY OF SUSSEX, MAY
23, 2008
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Outline

• Introduction The GMR-approach
• Regional development policy models and the
  geography of innovation
• Modeling static geographic effects The TFP
  sub-model
• Regional, inter-regional and macro effects in the
  GMR system
• Convergence vs/and growth policy simulations
• Summary

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Introduction The GMR-approach

• GMR-Hungary result of an international
  collaboration
• University of Pécs, Hungary Attila Varga
• University of Münster, Germany Hans Joachim
  Schalk
• Tottori University, Japan Atsushi Koike
• TNO, Delft, The Netherlands Lori Tavasszy
• Transman Ltd., Hungary János Monigl

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Regional development policy models and the
geography of innovation

• Knowledge-based regional development policy /
  Innovative cluster building / EU CSF support
  policies
• Policy instruments
• Promoting firms technological potential
  (start-up and investment supports, tax credits,
  low interest rate loans or venture capital)
• Local technological environment support (RD
  promotion universities and private firms, human
  capital improvement, support of public-private
  interactions in innovation, financing physical
  infrastructure building)

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Regional development policy models and the
geography of innovation

• Effects of successful policies
• Static geography effects (region in target and
  spillovers)
• The role of agglomeration in static effects
• Dynamic geography effects (changes in the
  geography of innovation and production)
• Towards convergence or divergence
• Supra regional growth effects of the changing
  geographic structure of innovation

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Regional development policy models and the
geography of innovation

• Likely policy effects the Geography of
  Innovation literature
• Knowledge spillovers localised to a
  considerable extent effect on policy
• Human capital development the role of graduate
  migration effect on policy
• Infrastructure investment the geographical
  reach of the accessibility effect effect on
  policy
• Agglomeration and the policies

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Regional development policy models and the
geography of innovation

• New generation development policy impact models
  considering the geography effect on regional
  differences and growth
• The current state REMI, HERMIN, EcoRET
• GMR-Hungary

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Technological progress, spatial structure and
macroeconomic growth

• Complex issue treated in four separate fields of
  economics
• A. EG 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 RD
• 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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Technological progress, spatial structure and
macroeconomic growth
B. IS Systems of innovationliterature
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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Technological progress, spatial structure and
macroeconomic growth
C. NEG New economic geography models
endogenized spatial economic structure in a
general equilibrium model (Krugman 1991, Fujita,
Krugman and Venables 1999, Fujita and Thisse
2002) - 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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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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Technological progress, spatial structure and
macroeconomic growth

• IS, NEG, EGT, GI complements to each other in
  growth explanation, no theoretical integration
  (Acs-Varga 2002)
• IS, NEG, 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)
• EG, IS, NEG, 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
  2004)

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Modeling static geographic effects The TFP
sub-model

• GMR-Hungary CSF effects
• Technology effect Infrastructure, human capital,
  RD
• Careful modeling of static geographic effect is
  crucial
• Direct regional and spillover effect
• Dynamic effect (centripetal forces)
• Convergence/divergence and growth effects

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Modeling static geographic effects The TFP
sub-model

• The TFP equation (a KPF model)

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Modeling static geographic effects The TFP
sub-model
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Modeling static geographic effects The TFP
sub-model

• The calculated elasticity values are situated
  well in the range of the international
  literature. For infrastructure the
  internationally estimated elasticities range
  between 0.1 and 0.8 whereas the calculated
  elasticity is 0.45. With respect to human capital
  the range is 0.15-0.40 and the GMR elasticity is
  0.34.

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Convergence vs/and growth policy simulations
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Convergence vs/and growth policy simulations
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Convergence vs/and growth policy simulations
GDP growth rates relative to baseline
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Convergence vs/and growth policy simulations
Standard deviations of GDP relative to baseline
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Convergence vs/and growth policy simulations
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Summary

• Aim lessons from the geography of innovation
  literature in development policy modeling
• Limitations of the GMR-approach
• Plans for further developments