According to the May Presidential Decree (2018), one of the national goals and strategic objectives of the development of the Russian Federation for the period up to 2024 is “ensuring sustainable natural growth in the population of the Russian Federation and increasing life expectancy to 78 years”. Thus, the increased need to monitor the current demographic situation, the study of the structure of demographic indicators, and the close attention of the community to the realization of national goals led to the choice of the topic of this study. The paper studies the problems of modeling the seasonality of demographic indicators in the Russian Federation (the number of births, the number of deaths, infant mortality, the number of marriages) according to monthly data of Rosstat for the period 2007-2018. Foreign studies have shown that, along with traditional demographic methods, ARIMA models give good results in forecasting of demographic indicators (population size, birth and death rates, life expectancy). Using the approach based on SARIMA models in this work allowed us to obtain adequate models with good statistical and prognostic properties. The stationarity of processes was analyzed on the basis of the HEGY test. The indicators studied in the work had a number of features that must be taken into account when modeling. The series of the number of births and the number of deaths had second and first integration orders respectively and contained deterministic seasonality, the series of the number of marriages had the first integration order and seasonal integration, and the infant mortality series did not contain seasonality, which was confirmed based on the analysis of the autocorrelation function and periodogram. Point and interval estimates of the forecast for 2019 were built for all indicators here studied. To compare the quality of forecasting SARIMA models, seasonal Holt -Winters models were also evaluated.
The paper deals with the relation between traditional family norms and women’s age at first marriage. The study is based on data from Karachay-Cherkessia, a republic of the North Caucasus (Russia), and uses results of a survey among women of reproductive ages conducted there in 2018. It has been demonstrated that traditional family norms, including those empowering elder generations and limiting women’s social role to housework and bringing up children, are rather strong in that region. It is currently assumed that these norms generally correlate with women’s younger age at first marriage. However, our analysis of the data from Karachay-Cherkessia, which used proportional hazard models and logistic regressions, does not fit this assumption. Specifically, it turns out that precisely that ethnic group of Karachay-Cherkessia which shows a higher concentration of traditional family norms also demonstrates a statistically significant tendency towards women’s older age at first marriage. Thus the relation between traditional family norms and the timing of marriage appears to vary more across different societies than is supposed. The consequences of this result for the study of demographic transformations taking place in different countries and regions together with the breakdown of traditional family norms are discussed.
The book is devoted to issues of forecasting the size and structure of the Earth’s population until the end of the XXI century; it focuses on both the methodological aspects of making such demographic projections and on the consequences of various forecast scenarios for future trajectories of human development. The authors pay special attention to the level of education - in their opinion, the most significant component of human capital. At the same time, the educational structure of the population is not only a derivative of demographic changes and the pace of "education expansion" in various regions and countries of the world, but also itself has and will continue to have a significant impact on demographic processes. This is precisely the kind of defining impact education will have for the population of our planet in the 21st century.
One of the declared national goals of Russia's development is to increase life expectancy at birth to 80 years by 2030. To achieve this, it is important to understand life expectancy determinants that the government can influence. This paper aims to identify main determinants of life expectancy in groups of countries that differ in the level of life expectancy and show the place of Russia in this range. We use data on 82 countries and conduct descriptive, cluster, and correlation analysis. Our analysis shows that life expectancy in Russia is much lower than in countries with a comparable level of economic development and health care expenditures. Various factors affect public health in different ways depending on the countries' belonging to different clusters on life expectancy. These factors are development of the economy, including health care, urbanization, ecology, nutrition, and unhealthy lifestyles. In conclusion, we provide recommendations for the public policy.
The paper deals with different ‘local’ sources of data on the number of children and fertility in the Republic of Dagestan (North Caucasus, Russia). A study of ‘local’ sources on fertility in comparison with census data in Dagestan is necessary for two reasons. First, the region is known to have serious problems with official demographic statistics, so that all alternative sources should be considered. Second, different parts of Dagestan demonstrate outstanding diversity with respect to fertility, which needs to be studied and explained. The paper discusses the results of a field study undertaken in Dagestan in 2015. In the course of that study, data on the number of children born in different years between 2000 and 2014 were collected from local administrations, medical institutions and schools in ten villages of Dagestan. The data of the three sources never fully agreed with each other or with census data, but showed regular, statistically significant correspondences. We hypothesize about possible reasons for the differences between the data of the sources on the basis of our interviews with local officials in the villages under study. We argue that the data of medical institutions and schools should be the most reliable. We also compare data of local administrations and medical institutions on the number of women of different age groups and study the possibility of using these data for calculating fertility rates (crude birth rate, total fertility rate, etc.) for different parts of Dagestan, in order to establish the differences between their fertility dynamics.