Baltic Region (Dec 2017)

Introducing Sectoral Models into Regional Management: An Assessment of Regulatory Impacts on the Economy

  • Voloshenko K.Yu.,
  • Ponomarev A. K.

DOI
https://doi.org/10.5922/2079-8555-2017-4-5
Journal volume & issue
Vol. 9, no. 4
pp. 72 – 86

Abstract

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Regardless of the geography of regions, management at the regional level, both in Russia and the Baltic Sea countries, faces many challenges. Hence, it is necessary to search for new effective economic management tools, since traditional approaches and modeling practices at the regional level are not suitable for either analysing various types of impact on regional economy (production, market (product), sector, region), or assessment of their consequences and identification of the necessary measures in any given economic conditions. The authors construct sectoral models to assess regulatory impacts on regional economic performance. Assessments of regulatory impacts on product value chains, economic sectors, and regions as a whole show good repeatability, which makes it possible to provide a rationale for economic decision-making. The authors propose new sectoral models using the Kaliningrad region as an example. The models are used in a comprehensive analysis of conditions for a GRP growth resulting from an increase in sectoral contributions. To this end, the study uses the well-known approaches of simulation modelling, as well as qualitative and quantitative methods in combination with economic-mathematical optimisation models. The article presents a pilot model of regulatory impacts for selected sectors of the Kaliningrad economy. The developed and tested models suggest that a rationale for economic decision-making and consequent actions should be based on the assessment of the impact of different groups of external, internal, and independent factors on value chains, based on the criterion of optimal factor income. In conclusion, the authors offer recommendations for using the proposed models in business, public administration and regional economic modeling.

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