The article shows that the increase in inflation in 2020—2024 is associated with the acceleration of the growth rate of the money supply. The main contribution to the growth of the monetary base was made by transactions with the National Wealth Fund, which were not sterilized. Following this, there was an acceleration in the growth rate of lending, supported by preferential programs and a decrease in the required reserve ratio, which was reflected in an increase in the credit multiplier. Accelerated growth in the money supply led to an increase in the growth rate of consumer prices. The current phase of the economic cycle, together with the labor shortage, is increasing inflationary pressure. Inflation growth could have been even greater if not for the increased demand for real cash balances and high rates of real GDP growth in 2023—2024. Along with a tight monetary policy, additional measures to reduce inflation may include slower indexation of regulated prices and excise rates; limiting the growth rate of the consumer and auto loan portfolio of commercial banks; increasing reserve requirements for them.

2024 Nobel Prize in Economics was awarded to Daron Acemoglu and Simon Johnson from MIT and to James Robinson from the University of Chicago for fundamental contributions to institutional economics. The laureates and their followers have suggested a number of theoretical models of institutional dynamics, giving rise to new areas of modern economic research. In addition, Acemoglu, Johnson, and Robinson have made major contributions to empirical studies of long-term economic development by establishing critical patterns that connect economic development with political and social institutions.

The paper presents a comprehensive analysis of labor migration in Moscow, including all types of spatial mobility that are significant for the capital’s labor market. The research focuses on both international and internal migrants, including commuting labor migrants. The information base includes microdata from the Labor Force Survey by Rosstat, statistics of the Ministry of the Interior of the Russian Federation, and the results of the survey of international migrants working in Moscow. Assessment of the scale and dynamics of labor migration is made, a comparative characteristic of the socio-demographic and economic peculiarities of Muscovites and various groups of migrants is given, professional and sectoral niches of migrant labor are identified, the impact of migration on the labor market of Moscow is assessed. Temporary labor migrants represent a significant part of the Moscow labor market: they account for at least a quarter of all workers in the capital. It is shown that labor migrants compensate for the decreasing groups of Muscovites — young people and the population with a low level of education. For the first time, calculations of selectivity indices are performed on Russian data. The analysis shows that migrants are concentrated in a limited industrial and professional segment, which indicates the formation of migrant employment niches. It is proved that migrants fill the gap in the demand for low-skilled labor and its supply from the highly educated Moscow labor force. As a result, the shortage of labor is decreasing, especially in the sectors that are not attractive to Muscovites. From the perspective of places of employment (industry and profession), migrants and Muscovites are not competitors but complement each other.

The paper studies the association between the artificial intelligence (AI) and employment characteristics. As a theoretical framework, we use the Acemoglu et al. model, which introduces opposing effects of the AI algorithms on labor employment on the firm level such as substitution effect and complimentary/ productivity effects. Depending on their relative strength, the AI algorithms may both decrease and increase employment. The overall effect is estimated using the data on 3.5 million of vacancies for about 35 thousand firms published up to 2022 spring on the HeadHunter website. According to the results, the existence of tasks realizable using AI is consistent with a higher AI employment, which implies the substitution effect. The other, less intuitive, result is that the same tasks suggest a higher non-AI employment, supports complimentary/productivity effects. The overall employment effect is positive as follows from the positive AI tasks—total employment association.

The main household decisions are related to the consumer and housing market, while housing decisions are related to mortgages. Moreover, both markets are significantly influenced by the macroeconomic environment. The paper aims to study the structural relationships between the macroeconomic environment, consumer and housing markets. How do these aspects relate to each other in Russia? To analyze the associations, the Bayesian vector autoregression methodology with sign restrictions is used. The obtained results show that the housing market strongly depends on fluctuations in the consumer market, whereas the inverse dependence is not so strongly manifested. At the same time, the impact of mortgage shocks and monetary conditions has a greater impact on the volume indicators of the consumer and housing markets than on prices. The dynamics of housing prices is more related to the supply of housing, while consumer prices are related to the ruble exchange rate and supply and demand shocks. The impact e of oil prices on the dynamics of both markets is analyzed. Oil prices have the most significant impact on household consumption, mainly through the demand channel. One way of functioning of this channel are the fluctuations of real disposable incomes in response to fluctuations in oil prices. The constructed model built demonstrates acceptable predictive characteristics, outperfoming the best univariate time series models on certain horizons.

After the launch of mass preferential mortgage program in 2020, subsidizing interest rates on housing loans has become a key factor affecting the primary housing market in Russia. In 2024, the portfolio of preferential mortgage lending approached RUB 9 trillion, indicating the high importance of this factor for the financial sector and the entire economy. Nevertheless, the effectiveness of subsidized mortgage programs and their effect on the socio-economic situation remain a subject of debate among economists, politicians and the public. The paper analyzes the impact of these programs on the residential real estate market, house prices and housing affordability. The core part of the paper contains the estimation of the scale of the substitution effect — the share of subsidized mortgage loans that would have been granted under market conditions. Based on the results obtained, alternative methods of housing support are proposed.

The article considers the dynamics of housing construction in the Russian Soviet Federative Socialist Republic (RSFSR — a constituent republic of the Soviet Union) and the Russian Federation from the year of 1918 to 2023. For our analysis, we make use of such indicators as housing completions overall and in urban and rural areas, by source of financing, by segment (apartment buildings and individual houses); the data on the size of the housing stock and its structure depending on the form of ownership; housing availability to the population; quantity, structure and floor space of housing units built as well as number of people who improved their housing conditions. On the basis of the data on housing completions in various segments and changes in the legislation, we identify seven stages in the evolution of housing construction in the RSFSR and the Russian Federation during the century considered as well as characterize each of the stages. The article presents for the first time estimates of the area of total and rural socialized housing stock and the housing stock of the RSFSR that was in the personal ownership of citizens for the years of 1926, 1939, 1949 and for the period from 1958 to 1979. We also pinpoint major current socioeconomic problems in housing construction and suggest measures to resolve them with the aim of raising housing availability and affordability for the population of the Russian Federation.