Modeling the Development of Regional Economy and an Innovation Space Efficiency
Valery Makarov,
Sergey Ayvazyan,
Mikhail Afanasyev,
Albert Bakhtizin and
Ashkhen Nanavyan
Foresight-Russia Форсайт, 2016, vol. 10, issue 3 (eng), 76-90
Abstract:
Forming the regional space of innovation is accompanied by the simultaneous development of various structures. The contemporary model of innovative development assumes interactions between government, industry, and universities. In this paper, the set of potential links between research organizations and the innovation activity of enterprises is characterized as the innovative space and is seen as a resource for innovation. Obtaining quantitative characteristics of such links and interactions is one of the most difficult tasks in analysing innovation processes. Our hypothesis is that regional innovation depends on the size of the innovation space and on how effectively it is used. The econometric modeling results do not contradict our hypothesis. Our estimates of the size of the innovation space used by regions of Russia when creating new production technologies confirm the high potential value of this resource. Using a Computable General Equilibrium (CGE) model that we developed, we analysed the innovative elements of regional economies (based on the example of the Republic of Bashkortostan) and quantitatively assessed the effects of different scenarios that aim to improve the socioeconomic system. We included an indicator of the effective use of the innovation space for a given region as one of the agents of the CGE model production function. Our results indicate the important role of regional authorities in promoting cooperation between the state, industry, and the research and education communities as well as in developing regional innovation systems.
Keywords: regional economy; innovation; econometric modeling; check of hypotheses; stochastic border; efficiency assessment (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:scn:013126:16907050
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