From the Geography of Innovation to Development Policy Analysis: The GMR-approach Attila Varga Department of Economics and Regional Studies University.

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Presentation transcript:

From the Geography of Innovation to Development Policy Analysis: The GMR-approach Attila Varga Department of Economics and Regional Studies University of Pécs Faculty of Business and Economics

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

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

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 (R&D promotion: universities and private firms, human capital improvement, support of public-private interactions in innovation, financing physical infrastructure building)

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) –Tovards convergence or divergence –Supra regional growth effects of the changing geographic structure of innovation

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

Modeling static geographic effects: The TFP sub-model GMR-Hungary: CSF effects Technology effect: Infrastructure, human capital, R&D Careful modeling of static geographic effect is crucial: –Direct regional and spillover effect –Dynamic effect (centripetal forces) –Convergence/divergence and growth effects

Modeling static geographic effects: The TFP sub-model The TFP equation (a KPF model)

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 With respect to human capital the range is and the GMR elasticity is 0.34.

Convergence vs/and growth – policy simulations

The effects of policy scenarios on the GDP growth rate

The policy effects on convergence measured by standard deviation of regional value added

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