Российская пенсионная система в контексте демографических вызовов и ограничений
This work, based on the results of long-term (up to 2050) pension forecasting, is devoted to the study of the impact of demographic parameters on the future of the Russian pay-as-you-go pension system. It assesses the sensitivity of the parameters of the pension system to changing scenarios of the population forecast. It is shown that the scenario with low birth rate, life expectancy and migration leads to the smallest increase in the number of pensioners, but at the same time to the greatest reduction in the number of contributors, which may have negative consequences for the situation on the labor market and economic development in general. On the contrary, the scenario with a high birth rate, high migration and the greatest increase in life expectancy gives the least reduction in the number of contributors, but dramatically increases the number of ‘insurance’ pensioners. From the perspective of fiscal sustainability of the pension system, the ‘low’ scenario is the best, but even there the number of pensioners begins to exceed the number of contributors already in 2024, and the gap between pension contributory incomes and the expenditures on ‘insurance’ pensions increases from 2.4% of GDP in 2017 to 4.6% in 2050. Furthermore, the dynamics of life expectancy in the ‘low’ scenario leaves no room for raising the retirement age. On the basis of statistics and population surveys, the article discusses whether there are socio-demographic reasons for raising the retirement age in Russia and concludes that the significance of the ill health is weakening as an argument against this measure. The article also presents the results of pension forecast performed for one of the possible options for raising the retirement age, which show that this measure significantly reduces the negative consequences of aging, even under the assumptions about a possible increase in unemployment and disability. By 2050, the gap between the pension incomes and expenditures is almost equal to the level of 2017 under the ‘high’ scenario of the population forecast and still remains 1.3-1.5 times lower for ‘medium’ and ‘low’ scenarios.