On the issue of forecasting social transfers for the macro-regions of Russia

Author:

Yakovets T. Y.1,Golubkov V. V.1

Affiliation:

1. Russian Academy of Natural Sciences

Abstract

The work is a continuation of the research carried out in 2017 and published in the journal “Economics and Mathematical Methods” (2018, N 4). The need is formulated in a force majeure situation for the country to prevent a sharp drop in the standard of living of the population of the country to increase the role of social transfers. A special role belongs to this in the conditions of the modern demographic situation in Russia. The expediency of the development and adoption at the level of the federal law of the Social Doctrine of the Russian Federation 2025–2030 is substantiated. The main provisions of such a Doctrine developed by N.M. Rimashevskaya and S.S. Sulakshin are considered. The basic principles of the Social Doctrine and its components are given. The scheme of interrelations of models in forecasting social transfers is given. The scheme of classification of regions of the Russian Federation for carrying out model demographic calculations based on the territorial-ethnic principle based on the values of indicators of natural population growth and the integral index of quality of life and its rank calculated by L.A. Migranova is given. It is recommended to carry out calculations using models as a 12-regional bundle. The influence of the level of GDP on the main demographic indicators is analyzed on statistical material. As examples of modeling demographic indicators as functions of GDP per capita, the following indicators were taken: total fertility rate; average age of women at birth; life expectancy of men at birth; life expectancy of women at birth. Indicators for evaluating the effectiveness of the social transfer system are proposed.

Publisher

Faculty of Sociology, Lomonosov Moscow State University

Subject

General Medicine

Reference22 articles.

1. Bejker Dzh. (ml.), Grejvs-Morris P. Approksimacii Pade [Padé approximants]. M., 1986 (in Russian).

2. Chislennost’ naseleniya RF na 1 yanvarya 2019 goda [The population of the Russian Federation as of January 1, 2019]. URL: https://realnoevremya.ru/attachments/1043 (data obrashcheniya: 25.02.2020) (in Russian).

3. Demograficheskij ezhegodnik Rossii [Demographic Yearbook of Russia]. M., 2009 (in Russian).

4. Demograficheskij ezhegodnik Rossii [Demographic Yearbook of Russia]. M., 2021 (in Russian).

5. Federal’nyj byudzhet 2023–2025 gg. Federal’nyj zakon ot 05.12.2022 N 466–FZ. Oficial’noe opublikovanie pravovyh aktov [Federal budget 2023–2025 Federal Law No. 466-FZ dated December 5, 2022. Official publication of legal acts] // Oficial’nyj internet-portal pravovoj informacii. URL: pravo.gov.ru (data obrashcheniya: 10.01.2023) (in Russian).

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