Methodological Aspects of the Study of the Resource Potential of Pension Provision as an Object of Modeling and Forecasting
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https://doi.org/10.14571/brajets.v16.n4.1317-1326Abstract
The article deals with the methodological aspects of the study of the resource potential of pension provision as an object of modeling and forecasting. It is noted that the resource potential, the parameters of its condition become factors in the development of a promising state policy for the development of the pension system, and the use of a systematic approach is a necessary step in strategic analysis, modeling and long-term forecasting. The position is substantiated that the functioning of the pension system in difficult political, socio-economic and demographic conditions, the urgent need to solve a set of problems for the implementation of the target function of the pension system actualizes the need to use a set of modeling and forecasting methods, both pension obligations and insurance premiums. The content characteristics of the resource potential of pension provision as an object of modeling are disclosed, including its state, behavior, individuality, boundaries of the object, which serve as initial information in the construction and study of models. The levels of relations and connections of the resource potential, which unite spatial and temporal characteristics, are revealed. The conceptual scheme of the methodology for forecasting the resource potential of the state pension system is substantiated and the methodological principles for forecasting the potential of pension resources are formulated.References
Common features and properties of models Center of Excellence "Automated control systems and industrial safety". URL: http: // www.automationlab.ru/index. - p. 1-2.
https://www.google.ru/search?ie=UTF-8&q=http%3A%2F%2Flekcion.ru% 2Fmodelirovanie_modeli%2FSvoystva_priznaki_harakteristiki_obektov_modelirovaniya.html. - p.3.
Donoso, P. C., Pérez, M. P. S., Aguirre, C. C., Barbosa, A. O., Gómez, C. M. G., Jimenez, A. M., & Nodar, S. R. (2022). Angiosarcoma suprarrenal primario. Reporte de caso. Archivos de Patologia, 3(3), 96-103.
Farhud, D., & Mojahed, N. (2022). SARS-COV-2 Notable Mutations and Variants: A Review Article. Iranian Journal of Public Health, 51(7), 1494.
Ferrer, N. R., Romero, M. B., Ochenduszko, S., Perpiñá, L. G., Malagón, S. P., Arbat, J. R., & Nodar, S. R. (2022). Solitary fibrous tumor of the thyroid. Report of a case with unusual clinical and morphological findings Archivos de Patologia, 3(3), 104-109.
Jamalpour, H., & Derabi, J. Y. (2023). Aesthetic Experience, Neurology and Cultural Memory. Passagens: Revista Internacional de História Política e Cultura Jurídica, vol. `5, no. 2, pp. 340-348, https://doi.org/10.15175/1984-2503-202315208
Jamalpour, H., & Verma, A. (2022). Introduction to Psychoanalysis: A New Perspective on Linguistics and Psychoanalysis, Vol. 1, Rose Publication PTY LTD, Melbourne, Australia.
Martynova, N. A. (2019). Resource potential of the organization / Economics, management and finance in the XXI century: facts, trends, forecasts // Proceedings of the International Scientific and Practical Conference. -. - Publishing house of the Kursk Institute of Cooperation (branch), p. 168.
Modeling of the complex probability systems. (2011). Collective of authors. Scientific editor V.A. Morozova. Ekaterinburg: Ural Federal University, p.8.
Parsadanov, G. A., & Parsadanov, V. V. (2002). Forecasting of the national economy. Egorov. M.: Izd vošshaya shkola, p. 49.
Properties, attributes, and characteristics of modeling objects // URL:
Pryadeho, A. A., & Pryadeho, A. N. (2014). Prediction as a component of cognitive abilities. Bulletin of Bryansk State University,1, p. 80.
Rudakova, R. P. (2010). Methodological foundations of socio-economic forecasting. Vestnik of Leningrad State University named after A.S. Pushkin, 6(2), 5-15.
Safronova, V. M. (Ed) (1999). Social forecasting and modeling. Moscow: Moscow State University of Management, 249-250.
Sedova, M. L. (2018). Balanced budget of the Russian pension fund and the problems of financial sustainability of the pension system. Izvestiya SPSEU, 5(113), p. 70.
Selivanov, A. I. (2021). Methodological platforms and methods of strategic forecasting: World experience and Russian potential. Power, 1, 280-281.
Shariati, A., Azaribeni, A., Hajighahramanzadeh, P., & Loghmani, Z. (2013). Liquid–liquid equilibria of systems containingsunflower oil, ethanol and water. APCBEE procedia, 5, 486-490.
Skripchenko, T. L. (2009). Assessment of economic potential of consumer cooperation organizations. Bulletin of BUPC, 4(32), 314.
Todortsev, Y. K. (2008). Numerical methods and modeling on the computer. - Publishing house of Odessa National Polytechnic University, p.5.
Vildanov, H. S., & Derkach, V. V. (2017). Methodological features of social forecasting. Bulletin of the Ural State Technical University. Science, Education, Economics. Series Economics, 1(19), 133-134.
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