The article proves the usefulness of including aggregate information from economic tendency surveys in the system of nowcasting of economic growth. The authors compare the efficiency of vector autoregressive models that include the economic sentiment indicator based on the results of Rosstat business activity and consumer expectations surveys, and the business climate indicator based on the results of the Bank of Russia enterprise monitoring.
Statistical testing of time series of composite indicators and GDP volume index confirmed a significant correlation and causality between them, as well as the similarity of their cyclical profiles. Both indices pass cyclical turning points synchronously or ahead of the GDP volume index, their predictive capabilities are enhanced by the early availability of information. The capabilities of GDP growth nowcasting using survey information are assessed in three specifications of the vector autoregressive model with dummy variables. On the in-sample period, the model including two composite indicators and the GDP volume index demonstrates the highest accuracy.
The proposed approach allows us to obtain flash estimates of GDP growth prospects that are significantly ahead of the official statistical information

The paper contains the main results of the study of the quality of interval forecasts based on quantile regression and smooth quantile regression models relative to interval forecasts based on OLS models for Russian inflation. All models in the work were built from the logic of the possibility of forecasting in real-time, in connection with which the authors used inflation that was not cleared of seasonality in the expression month to the same month of the previous year. For each forecast horizon, the authors developed a separate model from lagged values of inflation and regressors so that the known values of lagged variables were always used on the right side of the equation.
The authors tested a wide range of specifications – from very compact autoregressive models with one or two lags to wide ones with three additional regressors in addition to inflation lags. The best quality from the point of view of CRPS (Continuous Ranked Probability Score) metrics typical for such a task were the specifications that included the only additional variable – the USD/RUB exchange rate. As the confidence interval narrowed and at longer horizons, quantile and smooth quantile models became increasingly better relative to OLS models according to the CRPS metric.
According to the authors, in the presence of inflation targeting, qualitative inflation forecasts can be used by the Bank of Russia in conducting monetary policy when forecasting future inflation dynamics and stress-testing the Russian economy. In general, this can help increase the economic agents’ confidence in the Bank of Russia within the concept of rational expectations

The article presents the results of a comparative analysis of the residential real estate market in nine administrative districts of Moscow in 2016 and 2024. The paper focuses on the features of housing price formation and considers factors influencing pricing, including socio-economic conditions and transport infrastructure. The study outlines the role of housing construction and the investment attractiveness of various districts of the capital.
The authors used official data from Russia's largest real estate technology service (CIAN) on asking prices for apartments for sale depending on their parameters. The article draws on such indicators as the local average price per square meter of the total area of dwellings and the number of offers of apartments for sale. It is shown that apartment prices in two administrative districts (AO) of Moscow have a stable growth trend in 2024, which was not observed in 2016. It is concluded that the real estate markets in the districts of Moscow in 2016 (exception for the Central AO) were strongly differentiated in price offers in 2024, and, therefore, it is incorrect to use the average price per square meter of Moscow residential real estate as a characteristic of housing quality in 2024.
The article lists events that influenced changes in the Moscow residential real estate market without specifying the relative strength of their impact. According to the authors, each event had its causes, but their almost simultaneous appearance led to tension in the housing market for all participants.
In conclusion, the significant impact of inflation and the restoration of residential premises (after renting) on the growth of residential property values and the potential for using housing as an investment object is emphasized

The article analyses the relationships between economic and demographic processes in contemporary Russia.
Using index analysis, the author concluded that, in 2006–2018, a decline in the working-age population would have reduced, ceteris paribus, almost one-third of the GDP growth rate if the negative impact of this factor had not been fully compensated by an increase in the employment rate of the working-age population during this period. Growth of fertility in 2007–2015 would have led, if the influence of the situation on the labor market was eliminated, to a decrease in the number of employees by 1.2% (caused by the decline in female labor force participation rate), while fertility decrease after 2015 would have led to an increase in this number by 0.4%. Based on this estimation, it was concluded that the changes in fertility can, in the short term, have any significant impact on employment only in those types of economic activity in which the women of reproductive age make up the overwhelming majority of the employees.
It has been suggested that the accumulation of socio-psychological prerequisites for a decline in fertility has led the demographic system, both in Western countries and in Russia, into a state of unstable equilibrium. The global financial crises of 2008–2009 and the 2014–2015 financial crisis in Russia upset this equilibrium and launched a mechanism for fertility decline. It is argued that in the period under consideration, the Russian economy adapted to the turbulence of the external environment more successfully than the demographic sphere

The study examines the socioeconomic, demographic and health determinants of physical activity intensity in Russia. Using RLMS-HSE (the Russia Longitudinal Monitoring Survey – Higher School of Economics) data for 2021 and indicators of six levels of physical activity intensity, the authors built ordered probit models and calculated average marginal effects for a set of covariates. The independent variables were selected based on the SLOTH microeconomic model describing individual preferences towards physical activity.
The ordered probit regression provided empirical support for Meltzer and Jena's theoretical framework, stating that as income increases, with the pronounced substitution effect, the time spent on physical activity decreases, and the intensity of physical activity rises. In our study, the thesis about an increase in intensity with rising income was confirmed for a subsample of men but not women. For women, the intensity was determined by factors such as multiple morbidity and residing outside of Moscow or Saint Petersburg, which were not significant in the regressions for men.
The study resulted in several important conclusions. The intensity analysis showed that physician recommendations regarding the type of physical activity should consider patients' workload. For individuals with a busy schedule, recommended types of exercise that require a long time (for example, walking) are not suitable. At the same time, intense workouts (such as tennis or gym classes) can be built into the schedule. There is a need to develop sports infrastructure at workplaces, allowing individuals to allocate time for classes without bearing additional time and monetary costs associated with travel to the location of workouts. As income increases, exercising near the workplace allows an individual to increase the intensity of physical activity without incurring additional time costs

Since 2022, the school course «Probability and Statistics» has been taught as a compulsory subject in all schools in Russia, and questions on it are included in the Unified State Exam. However, international experience in teaching the basics of statistics shows that this is not an easy task. It includes not only teaching students how to prove the theorems of mathematical statistics and explain the calculation of the median and variance, but also contributes to the development of statistical thinking in them – the ability to make decisions based on the analysis of empirical data. According to the authors, the statistical community cannot and should not replace teachers who promote the teaching of statistics at school, but it has the opportunity to make a significant contribution to this process.
The article presents the experience of the All-Russian School competition on statistics «Trend», the All-Russian teacher competition for the best practices in teaching statistics «We train the best!», with the support of the territorial bodies of state statistics in St. Petersburg, Kirov and Rostov regions; master classes for hundreds of teachers teaching statistics in grades 7–11. In addition, the article presents plans for organizing a competition on civil statistics aimed at developing skills in working with statistical data, as well as teaching the basics of statistical analysis, the use of visualization tools, and the formation of citizenship through familiarity with objective statistical information