Abstract
In the course of the research, the authors formed a factor model for the assessment of the regional investment potential, model specification, and its parameters assessment, which check the quality and interpretation of the results obtained. The authors defined the indicators characterizing manufacturing, demographic, credit, fiscal potentials of the region, and its activity results. The factor analysis for the investment potential is conducted on the basis of regression formulas with the addition of stochastic values. To neutralize the impact of regional disproportions on the factor model of investment potential, the authors clusterized the data obtained by k-means methods and identified four clusters. Within the identified clusters, the authors defined the determinants capable of influencing the distribution of the all-Russian regional investment potential. The factor model quality was assessed for an individual cluster on the basis of the determination factor and the average standard error. The factor regressive model of the investment potential integrating the data for all regions not divided into cluster contains the result-based values only as explanatory variables. They are the balanced financial result and the volume of manufactured goods sold. No resource factor is significant. The regressive model built with the adjustment to the heteroscedasticity helped to determine resource factors significantly affecting the investment potential, that is, demographic factors, consumption of households, and the share of knowledge-intensive industries in the GDP. The wholesome regressive analysis of other clusters is not deemed to be possible because of data lack. However, we were able to find out that the determinates with the value that is significantly deviated from average Russian values have a significant effect on the investment potential.
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References
Kurbatova, M.V., Levin, S.N., Kagan, E.S., Kislitsyn, D.V.: Resource-type regions in Russia: definition and classification. Terra Economicus 17(3), 89ā106 (2019). https://doi.org/10.23683/2073-6606-2019-17-3-89-106
Troyanskaya, M.A.: Competition in taxation and the forms of its implementation among the subjects of the Russian Federation. J. Tax Reform. 3, 182ā198 (2017)
Makarov, V., Ayvazyan, S., Afanasyev, M., Bakhtizin, A., Nanavyan, A.: Modeling the development of regional economy and an innovation space efficiency foresight and STI. Governance 10(3), 76ā90 (2016). https://doi.org/10.17323/1995-459X.2016.3.76.90
Belyanichev, V.G., Savderova, A.F.: Assessment of the impact on fixed assets on the gross regional product. Oeconomia et Jus 1, 15ā21 (2019)
Kormishkina, L.A., Koloskov, D.A.: Innovative approaches to the formation of investment policy instruments from the perspective of the paradigm of neo-industrial development. Econ. Soc. Changes: Facts Trends Forecast 10(6), 218ā233 (2017)
Povarova, A.I.: Problems related to regional budgeting amid fiscal consolidation. Econ. Soc. Changes: Facts Trends Forecast 11(2), 100ā116 (2018). https://doi.org/10.15838/esc.2018.2.56.7
Shakleina, M.V., Midov, A.Z.: Strategic classification of regions according to the level of financial self-sufficiency. Econ. Soc. Changes: Facts Trends Forecast 12(3), 39ā54 (2019). https://doi.org/10.15838/esc.2019.3.63.3
Gubanova, E.S., Moskvina, O.S.: Methodological aspects of the assessment of the investment and innovation potential of a region. Econ. Soc. Changes: Facts Trends Forecast 13(2), 41ā55 (2020). https://doi.org/10.15838/esc.2020.2.68.3
Pechenskaya, M.A.: Budget capacity in the system of capacities of the territory: theoretical issues. Econ. Soc. Changes: Facts Trends Forecast 11(5), 61ā73 (2018). https://doi.org/10.15838/esc.2018.5.59.4
Grebennikov, V., Magomedov, R.: Budgetary self-sufficiency as a problem of the governmental programming of regional development. Econ. Math. Methods 55(4), 68ā77 (2019). https://doi.org/10.31857/S042473880006774-0
Maslennikov, D.A., Mityakov, S.N., Kataeva, L.Y., Fedoseeva, T.A.: Identification of the characteristics of the regional strategic development based on the indicatorsā statistical analysis. Econ. Region. 15(3), 707ā719 (2019)
Malkina, M.Y., Balakin, R.V.: Assessing the risk and performance of tax systems based on industry-specific, regional and mixed Portfolios. Finance Credit 23(47), 2823ā2842
Beklaryan, G.L.: Decision support system for sustainable economic development of the far eastern federal district. Bus. Inform. 4, 66ā75 (2018)
Abramova, M.A., Igonina, L.L.: Monetary and credit factors of increasing domestic investment demand in the Russian economy. Finansy: teoriya iĀ praktika = Finance: Theory and Practice 22(1), 128ā143 (2018)
Granitsa, Y.V.: Some approaches to the selection of regional determinants financial instability. In: IOP Conf. Series: Materials Science and Engineering (2020). http://dx.doi.org/https://doi.org/10.1088/1757-899X/753/8/082035
Rumyantsev, A.A.: Research and innovation activity in the region as a driver of its sustainable economic development. Econ. Soc. Changes: Facts Trends Forecast 11(2), 84ā99 (2018)
Cherkashin, A.K., Myadzelets, A.V.: Characterization of regional economic development in response to macroeconomic factors and conditions. Econ. Math. Methods 53(4), 13ā25 (2017)
Leonidova, E.G., Rumyantsev, N.M.: On the question of activating consumer and investment domestic demand. Probl. Territory Develop. 1(105), 52ā63 (2020)
Demidova, O.A., Kayasheva, E.V., Demyanenko, A.V.: Government spending on healthcare and economic growth in Russia: a regional aspect. Spatial Econ. 17(1), 97ā122 (2021). https://doi.org/10.14530/se.2021.1.097-122
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The study was carried out within the framework of the basic part of the state assignment of the Ministry of Education and Science of the Russian Federation, project 0729-2020-0056 āModern methods and models for diagnosing, monitoring, preventing and overcoming crisis phenomena in the economy in the context of digitalization as a way to ensure the economic security of the Russian Federation.ā
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Granitsa, Y.V. (2022). Diagnostics of State of Regional Structures Based on Factor Analysis of Investment Potential. In: Solovev, D.B., Savaley, V.V., Bekker, A.T., Petukhov, V.I. (eds) Proceeding of the International Science and Technology Conference "FarEastŠ”on 2021". Smart Innovation, Systems and Technologies, vol 275. Springer, Singapore. https://doi.org/10.1007/978-981-16-8829-4_100
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