Прогнозирование смертности в России с помощью актуарной стохастической модели Рэншоу-Хабермана
The death rate in Russia is much higher than in the economically developed countries and has a very special developmental trajectory due to historical features. The total life expectancy in Russia, despite the positive trends of the last decade, lags far behind the economically developed countries. Modelling and forecasting mortality is of great importance from a scientific and practical point of view, insurance companies and pension funds are constantly need of such research, because prediction of life expectancy allows to calculate adequate insurance rates and to estimate the required insurance reserves. The actuarial stochastic models that appeared at the end of the 20th century significantly advanced the actuarial science in the question of life expectancy evaluation. The presented work is devoted to the classic models of Lee-Carter and Cairns-Blake-Dowd, and their modified versions with the inclusion of the cohort effect, that was built with the StMoMo package in the R software environment. We found, that Renshaw-Haberman model (Lee-Carter model with the cohort effect) fits the Russian data best. For modelling, the age-specific mortality rates and the probability of dying for 1959-2014 were taken. For the population aged 20 to 88 years from the international database on mortality (Human Mortality Database). Forecasting was carried out using standard ARIMA models.