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The Estimation Of The Regions’ Efficiency Of The Russian Federation Including The Intellectual Capital, The Characteristics Of Readiness For Innovation, Level Of Well-Being, And Quality Of Life

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  • Valeriy Makarov
  • Albert Bakhtizin

    (CEMI RAS)

Abstract

On the basis of the authors’ methodology, the models of productive potential of the Russian Federation regions, including estimations of intellectual capital, were constructed. It is shown that characteristics of well-being level and quality of life make a significant impact on the regional production’s efficiency. The characteristics of regions’ readiness to innovate are identified, it is possible to name it as a factor of production’s efficiency. It is shown that the inclusion of different factors of efficiency in the production potential model can significantly increase the differentiation of technical efficiency estimates, besides these estimates and their grades depend on a set of efficiency’s factors. On the basis of a comparison of real GRP and boundary GRP ratings, it is identified locally effective regions with a relatively high estimation of efficiency among regions with similar amounts of GRP and locally ineffective regions. It is calculated marginal effects of influence of the efficiency’s factors on the result of industrial activity in the region. It seems constructively to use these estimates while analyzing the prospects for regions’ development, which is based on the possibility of targeting impact on controllable efficiency’s factors. The article is also offered the option of methodology of the public policy efficiency estimation on the knowledge economy formation — an agent-based model for Russia, which is learning the “knowledge economy†sector and considering their relationship with the rest of the macroeconomic system.

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  • Valeriy Makarov & Albert Bakhtizin, 2014. "The Estimation Of The Regions’ Efficiency Of The Russian Federation Including The Intellectual Capital, The Characteristics Of Readiness For Innovation, Level Of Well-Being, And Quality Of Life," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(4), pages 9-30.
    • Handle: RePEc:ura:ecregj:v:1:y:2014:i:4:p:9-30
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    1. Nikolskiy, Ilya & Furmanov, Kirill, 2023. "Assessing the accuracy of efficiency rankings obtained from a stochastic frontier model," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 71, pages 128-142.
    2. Kleiner, G. B., 2015. "State — Region — Branch — Enterprise: System Sustainability Framework of the Russian Economy," R-Economy, Ural Federal University, Graduate School of Economics and Management, vol. 1(2), pages 212-225.
    3. Aivazian, Sergei & Afanasiev, Mikhail & Kudrov, Alexander, 2018. "Indicators of economic development in the basis of the characteristics of regional differentiation," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 50, pages 4-22.
    4. George Kleiner, 2015. "State — Region — Field — Enterprise: Framework of Economics System Stability of Russia. Part 2," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(3), pages 9-17.
    5. Olga Romanova & Dmitriy Sirotin, 2017. "The Desired Image of the Future Economy of the Industrial Region: Development Trends and Evaluation Methodology," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(3), pages 746-763.
    6. Айвазян С.А. & Афанасьев М.Ю. & Кудров А.В., 2016. "Модели Производственного Потенциала И Оценки Технологической Эффективности Регионов Рф С Учетом Структуры Производства," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 52(1), pages 28-44, январь.

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