http://ej.hse.ru en-us Copyright 2025 Tue, 24 Jun 2025 10:31:52 +0300 https://ej.hse.ru/en/2025-29-2/1060397932.html This study examines the relationship between the ex-ante real interest rate and economic activity in Russia, as well as tests the hypothesis of a structural change in this relationship following the adoption of the inflation targeting regime in 2014. The research employs the Generalized Method of Moments (GMM) to estimate various versions of the New Keynesian IS curve, which links aggregate demand to the real interest rate. The estimation of the selected IS curve specifications aims to evaluate the functionality of the interest rate transmission channel, whose mechanism relies on the ability of the key policy rate to influence aggregate demand through a chain of economic interconnections. The results indicate a persistent negative relationship between the real interest rate and economic activity in Russia over the entire observation period (2003–2023). Furthermore, the formulated hypothesis is not rejected, suggesting a strengthening of the link between the real interest rate and economic activity. This implies an increased capacity of the Bank of Russia to influence real economic indicators through its interest rate policy. https://ej.hse.ru/en/2025-29-2/1060412409.html In September 2023, Russia launched an experiment in partner financing. To participate, entities must undergo an approval process by the Bank of Russia. Once approved, they are permitted to offer financial services based on the principles of partner (sharing of risks and profits).Six months before the official start of the experiment, the authors of this study began collecting data on the interest rates that banks offered to individuals on conventional loans. The resulting unique dataset includes monthly loan rates both prior to and throughout the first year following the experiment's launch. This enables an assessment of whether banks in the experiment changed the pricing of their conventional loan products after the introduction of partner financing – and if so, how and to what extent.The central objective of the study is to determine whether the participating banks adopted a strategy of transfer pricing for products in the scope of the experiment. The analysis employs the triple differences (DDD) method, which simultaneously accounts for the effects of banks, regions, and time periods.The findings offer valuable practical insights for the development of the partner financing market in Russia. They reveal how the banking sector responds to the implementation of innovative financial products and lay the groundwork for further research in this field. https://ej.hse.ru/en/2025-29-2/1060413547.html Research aimed at studying the influence of the place of residence of the population on income differentiation in society is essential for Russia due to the vast territory of the country. Along with the diversity of natural and climatic conditions, the uneven spatial development and resource capabilities of regions and municipalities, there are high gaps in the density and settlement of the territory and the development of infrastructure that provides basic human needs. All this determines the isolation of local populations and their dependence on the general characteristics of the locality of which they are residents.The purpose of this article is to develop approaches to the extended measurement and analysis of income inequality of the Russian population taking into account their place of residence and available information on income at the municipal level. The main indicators for measuring income inequality at the national level were the Gini coefficient and the Palm ratio, which complement each other quite harmoniously, characterizing the overall level of inequality and the income gap between the rich and poor. These coefficients are very popular among researchers and their interpretation requires no effort.Measuring inequality at the local level requires special tools that could make it possible to characterize this phenomenon based on sample data. The publication uses the intra-cluster correlation coefficient (ICC) as such a tool, thanks to which it is possible to assess the degree of uniformity of income of the population within clusters and, accordingly, income differentiation between clusters.The ICC made it possible to link the level of per capita income of the population with the municipality as the place of permanent residence of the household. It was used to assess the ongoing changes in income inequality, taking into account the differences between and within territorial entities, both from the perspective of income inequality within population groups and through the difference in average incomes among local populations.As an empirical basis for the calculations were used files of anonymized microdata available on the website of Rosstat for Sample survey of household incomes and participation in social programs for the period from 2013 to 2022, as well as information on the volume of social benefits to the population and taxable monetary incomes of the population by municipalities. https://ej.hse.ru/en/2025-29-2/1060426746.html Vintage data, or retrospective data, play a crucial role in assessing the accuracy of macroeconomic forecasting models and the decisions based on these models. These data represent a snapshot of information available at a particular point in time in the past and reflect how the economic situation was perceived at that time. It is important to realise that it is on the basis of vintage data, not revised and refined indicators, that forecasts and economic policy decisions were made. As an example, we show that the GDP growth paths in the projection period may diverge by as much as 1 pp.This paper presents a set of vintage data on Russian GDP and its components by the expenditure and production approaches. The dataset consists of revisions of nominal and real quarterly data for the period from December 2005 to the present. In addition to such data, the paper describes some properties of real and nominal GDP indicator revisions (number, frequency, magnitude) and its expenditure components, as well as the methodology for collecting historical indicators using the Wayback Machine, which enables data collection even in the absence of a saved history of their releases.We hope that this dataset will become a valuable tool for researchers and analysts, helping to better understand how the economic situation was assessed in the past. It can also provide a basis for conducting more correct experiments with models in pseudo-real time. https://ej.hse.ru/en/2025-29-2/1060427949.html The article analyzes the evolution of the sources of livelihood in Russian population censuses, starting with the first All-Russian Census of 1897 and ending with the census of 2020. Based on historical and modern data, the authors demonstrate how changes in formulations and categories reflect the transformation of socio-economic relations: from an agrarian society to a market economy, including the growth of self-employment, pension provision, and government social programs. Special attention is paid to methodological problems: incomplete accounting, reduced participation of the population, incorrect categorization of data (for example, combining pensions and benefits in the aggregated tables of the 2020 Census). Comparison with data from the tax service, departmental statistics, and surveys revealed significant discrepancies, especially in estimating the number of self-employed and passive income recipients. The COVID-19 pandemic has intensified the negative trends observed during the census: a decrease in confidence, a shift in focus to administrative sources; at the same time, the digital format could lead to double counting and errors in filling. In conclusion, measures are proposed to improve the design of questions, increase the transparency of the procedure and integrate census data with other sources to form a comprehensive picture of the standard of living of the population. https://ej.hse.ru/en/2025-29-2/1060441006.html The work is devoted to the estimation of the average treatment effect of higher education on health, assuming the existence of structural differences in the dependencies between the studied factors by gender and the birth cohort of individuals. The effects are estimated separately for each cohort of men and women using parametric (multivariate recursive probit model) and nonparametric (matching) methods. The use of fundamentally different approaches makes it possible to verify the robustness of the results to violating the assumptions of the applied methods. During the study the statistical evidence in favor of the existence of significant negative average treatment effects of higher education on the probability of obesity and the probability of hypertension and significant positive effects on the likelihood of high self-esteem of health was revealed for women. For men, the statistical evidence in favor of the presence of positive average treatment effects on the probability of having heart diseases, hypertension, allergy, and high self-esteem of health was found. A significant differentiation of the average treatment effects depending on the age cohort was revealed. For certain types of diseases, the cohort diminishing hypothesis for education is confirmed. The conclusion is made about the necessity of studying the impact of education on individuals’ health separately for men and women born in different time periods, as well as the inexpediency of using aggregated health indicators when analyzing the impact of education on health. The results of the study allow determining the nature of cohort changes in the impact of education on health of the Russian population and can be taken into account when forming state policy on education as a source of positive external effects on health.