The highest share of the middle-class population among federal subjects of Russia was observed in the Yamalo-Nenets Autonomous Okrug, where nearly four in ten households were classified as belonging to the middle class between 2022 and 2023. The Chukotka Autonomous Okrug and the Magadan Oblast closely followed, with a share of 32.5 percent and 31.9 percent, respectively.

Over ** million Russians aged 20 years and above, or approximately ** percent of the total adult population of the country, had wealth under 10,000 U.S. dollars in 2022. To compare, on average around the globe, the share of residents belonging to this wealth range was measured at **** percent in the same year. Economic inequality in Russia The latest available data by the World Bank recorded Russia’s Gini index, used as a measurement of income or wealth inequality, at **. The organization classified Russia as an upper-middle-income economy. Over ** percent of Russians considered themselves belonging to the middle class in 2020. HNWIs in Russia Approximately *** percent of Russian adults, or ******* residents, owned over *********** U.S. dollars, or were referred to as high-net-worth individuals (HNWIs). In 2021, the total wealth of the adult population in the country reached nearly *** trillion U.S. dollars. A significant portion of it belonged to roughly ***** ultra-high-net-worth individuals (UHNWIs) whose net worth exceeded ** billion U.S. dollars.

Between 2022 and 2023, the share of the middle-class population across federal subjects of Russia was the lowest in the Ingushetia Republic, where 1.4 percent of households were considered middle class. In the Chechen Republic, this ratio amounted to approximately 1.7 percent. All the regions in the top five, with the exception of the Kalmykia Republic, were located in the North Caucasian Federal District.

Key information about Russia Household Income per Capita

• Russia Annual Household Income per Capita reached 8,179.123 USD in Dec 2024, compared with the previous value of 7,549.747 USD in Dec 2023.
• Russia Annual Household Income per Capita data is updated yearly, available from Dec 1992 to Dec 2024, with an averaged value of 5,882.623 USD.
• The data reached an all-time high of 9,660.697 USD in Dec 2013 and a record low of 183.584 USD in Dec 1992.
• In the latest reports, Retail Sales of Russia grew 5.200 % YoY in Dec 2024.

CEIC calculates Annual Household Income per Capita from Monthly Average Household Income per Capita multiplied by 12 and converts it into USD. Federal State Statistics Service provides Average Household Income per Capita in local currency. The Bank of Russia average market exchange rate is used for currency conversions.

A large literature expects rising middle classes to promote democracy. However, few studies provide direct evidence on this group in nondemocratic settings. This article focuses on politically important internal differentiation within the middle classes, arguing that middle class growth in state-dependent sectors weakens potential coalitions in support of democratization. I test this argument using surveys conducted at mass demonstrations in Russia and detailed population data. I also present a new approach to studying protest based on case-control methods from epidemiology. The results reveal that state sector professionals were significantly less likely to mobilize against electoral fraud, even after controlling for ideology. If this group had participated at the same rate as middle class professionals from the private sector, I estimate that another 90,000 protesters would have taken to the streets. I trace these patterns of participation to the interaction of individual resources and selective incentives. These findings have implications for authoritarian stability and democratic transitions.

The dataset contains the replication material for "The Two-Pronged Middle Class: The Old Bourgeoisie, New State-Engineered Middle Class and Democratic Development". The project investigates the democratic role of the middle classes. It argues that it in many contexts it is important to distinguish between the autonomous middle class emerging through gradual capitalist development and the state-induced middle class created by the authoritarian regime. The anylsis is conducted using historical and contemporary data from the Russian Federation: sub-national (district-level and oblast-level) data, as well as results of an original survey. The dataset contains both Stata dta and do files and the full text of statistical appendix with numerous robustness checks corroborating the results of the study.

Approximately one third of Russians considered themselves poor in mid-November 2020. The largest share of respondents, measuring at 64 percent, believed they belonged to the middle-income population. Over the observed period since 2004, the share of those who classified themselves as belonging to the middle class increased in the country.

In 2024, almost all consumers in Moscow and Saint Petersburg earned at least the equivalent of the highest ** percent of global income earners as of 2022 in purchasing power parity (PPP) terms. Of them, the share of those who earned at least the equivalent of the top 10 percent of global income earners stood at around ** and ** percent, respectively.

The bottom 50 percent in Russia earned an average of 7.7 thousand euros at purchasing power parity (PPP) before income tax in 2021. To compare, the mean income of the top 10 percent stood at 104.6 thousand euros in the same year. Looking at the percentage distribution of national wealth in the country, the poorest half held only three percent of the total in 2021.

The average nominal salary in Russia was measured at ****** Russian rubles per month in 2024, marking an increase of roughly ****** Russian rubles compared to the previous year. After the currency redenomination and the financial default in 1998, the average wage levels in the country have grown exponentially. Who gets paid more in Russia? The Russian oil and gas industry paid the highest average wage to their employees, at ******* Russian rubles between January and September 2021. Salaries in management and management consulting were the second-highest, followed by air transportation and software development. On average, men earned more than women across all industries in the country. For example, in the information and communications sector, the average wage of a male worker amounted to nearly ******* Russian rubles, compared to under ****** Russian rubles for a female worker. Economic inequality in Russia The national income distribution of Russian households shows a high concentration of income and wealth in the hands of few individuals. In 2021, the mean income of the top one percent exceeded ******* euros before income tax, compared to ***** euros earned by the bottom 50 percent of the population. Furthermore, the richest one percent in Russia held an average wealth of over *** billion euros, whereas the personal wealth of the bottom 50 percent was measured at ***** euros in the same year. However, the income gap was forecast to decrease in Russia, with the Gini index expected to decline to **** by 2029.

Merchandise exports to low- and middle-income economies outside region (% of total merchandise exports) in Russia was reported at 49.92 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Russia - Merchandise exports to developing economies outside region (% of total merchandise exports) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Merchandise imports from low- and middle-income economies in Sub-Saharan Africa (% of total merchandise imports) in Russia was reported at 5.1327 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Russia - Merchandise imports from developing economies in Sub-Saharan Africa (% of total merchandise imports) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Merchandise imports from low- and middle-income economies in Middle East & North Africa (% of total merchandise imports) in Russia was reported at 0.65963 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Russia - Merchandise imports from developing economies in Middle East & North Africa (% of total merchandise imports) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

The monthly minimum wage in Russia as of January 1, 2025, amounted to ****** Russian rubles, or approximately *** U.S. dollars using the exchange rate as of February 28, 2025. In the capital Moscow, it was set at ****** Russian rubles, or around *** U.S. dollars. In the country's second-largest city, Saint Petersburg, it was lower, at ****** Russian rubles. Since 2021, the minimum wage in Russia has been calculated as 42 percent of the median wage. Between 2018 and 2020, it equaled to the minimum cost of living that was set in the country. The poor and the rich in Russia Around ** million residents lived under the poverty line in Russia. Those earning the highest 20 percent of income accounted for approximately ** percent of the total composite monetary income in 2023, while the group with the lowest income had a ***-percent share. Regional disparities The economic disparity was also observed across Russian federal subjects. The median monthly wage ranged from ****** Russian rubles in the Kabardino-Balkaria Republic to ****** Russian rubles in the Chukotka Autonomous Okrug between September 2018 and August 2019. Minimum wage thresholds can be regulated by regional authorities, as long as they are not lower than the federal minimum wage.

Abstract (en): The Research on Early Life and Aging Trends and Effects (RELATE) study compiles cross-national data that contain information that can be used to examine the effects of early life conditions on older adult health conditions, including heart disease, diabetes, obesity, functionality, mortality, and self-reported health. The complete cross sectional/longitudinal dataset (n=147,278) was compiled from major studies of older adults or households across the world that in most instances are representative of the older adult population either nationally, in major urban centers, or in provinces. It includes over 180 variables with information on demographic and geographic variables along with information about early life conditions and life course events for older adults in low, middle and high income countries. Selected variables were harmonized to facilitate cross national comparisons. In this first public release of the RELATE data, a subset of the data (n=88,273) is being released. The subset includes harmonized data of older adults from the following regions of the world: Africa (Ghana and South Africa), Asia (China, India), Latin America (Costa Rica, major cities in Latin America), and the United States (Puerto Rico, Wisconsin). This first release of the data collection is composed of 19 downloadable parts: Part 1 includes the harmonized cross-national RELATE dataset, which harmonizes data from parts 2 through 19. Specifically, parts 2 through 19 include data from Costa Rica (Part 2), Puerto Rico (Part 3), the United States (Wisconsin) (Part 4), Argentina (Part 5), Barbados (Part 6), Brazil (Part 7), Chile (Part 8), Cuba (Part 9), Mexico (Parts 10 and 15), Uruguay (Part 11), China (Parts 12, 18, and 19), Ghana (Part 13), India (Part 14), Russia (Part 16), and South Africa (Part 17). The Health and Retirement Study (HRS) was also used in the compilation of the larger RELATE data set (HRS) (N=12,527), and these data are now available for public release on the HRS data products page. To access the HRS data that are part of the RELATE data set, please see the collection notes below. The purpose of this study was to compile and harmonize cross-national data from both the developing and developed world to allow for the examination of how early life conditions are related to older adult health and well being. The selection of countries for this study was based on their diversity but also on the availability of comprehensive cross sectional/panel survey data for older adults born in the early to mid 20th century in low, middle and high income countries. These data were then utilized to create the harmonized cross-national RELATE data (Part 1). Specifically, data that are being released in this version of the RELATE study come from the following studies: CHNS (China Health and Nutrition Study) CLHLS (Chinese Longitudinal Healthy Longevity Survey) CRELES (Costa Rican Study of Longevity and Healthy Aging) PREHCO (Puerto Rican Elderly: Health Conditions) SABE (Study of Aging Survey on Health and Well Being of Elders) SAGE (WHO Study on Global Ageing and Adult Health) WLS (Wisconsin Longitudinal Study) Note that the countries selected represent a diverse range in national income levels: Barbados and the United States (including Puerto Rico) represent high income countries; Argentina, Cuba, Uruguay, Chile, Costa Rica, Brazil, Mexico, and Russia represent upper middle income countries; China and India represent lower middle income countries; and Ghana represents a low income country. Users should refer to the technical report that accompanies the RELATE data for more detailed information regarding the study design of the surveys used in the construction of the cross-national data. The Research on Early Life and Aging Trends and Effects (RELATE) data includes an array of variables, including basic demographic variables (age, gender, education), variables relating to early life conditions (height, knee height, rural/urban birthplace, childhood health, childhood socioeconomic status), adult socioeconomic status (income, wealth), adult lifestyle (smoking, drinking, exercising, diet), and health outcomes (self-reported health, chronic conditions, difficulty with functionality, obesity, mortality). Not all countries have the same variables. Please refer to the technical report that is part of the documentation for more detail regarding the variables available across countries. Sample weights are applicable to all countries exc...

Merchandise exports to low- and middle-income economies in Latin America & the Caribbean (% of total merchandise exports) in Russia was reported at 3.3455 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Russia - Merchandise exports to developing economies in Latin America & the Caribbean (% of total merchandise exports) - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

Merchandise imports from low- and middle-income economies in Europe & Central Asia (% of total merchandise imports) in Russia was reported at 19.38 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Russia - Merchandise imports from developing economies in Europe & Central Asia (% of total merchandise imports) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Merchandise exports to low- and middle-income economies in East Asia & Pacific (% of total merchandise exports) in Russia was reported at 26.56 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Russia - Merchandise exports to developing economies in East Asia & Pacific (% of total merchandise exports) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

The most often named digital healthcare trend of 2019 by representatives of private clinics and other medical organizations in Russia was online booking of consultations with a doctor. Telemedicine was mentioned by over 40 percent of respondents. As of 2018, one half of Russians from a connected middle-class population stated that they had not used telemedicine, but wanted to try.

BackgroundUnderstanding how urbanisation and rural-urban migration influence risk-factors for non-communicable disease (NCD) is crucial for developing effective preventative strategies globally. This study compares NCD risk-factor prevalence in urban, rural and migrant populations in China, Ghana, India, Mexico, Russia and South Africa.MethodsStudy participants were 39,436 adults within the WHO Study on global AGEing and adult health (SAGE), surveyed 2007–2010. Risk ratios (RR) for each risk-factor were calculated using logistic regression in country-specific and all country pooled analyses, adjusted for age, sex and survey design. Fully adjusted models included income quintile, marital status and education.ResultsRegular alcohol consumption was lower in migrant and urban groups than in rural groups (pooled RR and 95%CI: 0.47 (0.31–0.68); 0.58, (0.46–0.72), respectively). Occupational physical activity was lower (0.86 (0.72–0.98); 0.76 (0.65–0.85)) while active travel and recreational physical activity were higher (pooled RRs for urban groups; 1.05 (1.00–1.09), 2.36 (1.95–2.83), respectively; for migrant groups: 1.07 (1.0 -1.12), 1.71 (1.11–2.53), respectively). Overweight, raised waist circumference and diagnosed diabetes were higher in urban groups (1.19 (1.04–1.35), 1.24 (1.07–1.42), 1.69 (1.15–2.47), respectively). Exceptions to these trends exist: obesity indicators were higher in rural Russia; active travel was lower in urban groups in Ghana and India; and in South Africa, urban groups had the highest alcohol consumption.ConclusionMigrants and urban dwellers had similar NCD risk-factor profiles. These were not consistently worse than those seen in rural dwellers. The variable impact of urbanisation on NCD risk must be considered in the design and evaluation of strategies to reduce the growing burden of NCDs globally.