The diminishing potential for enhancing productive resources in order to sustain economic growth demands greater emphasis on how efficiently they are used as measured by total factor productivity (TFP). Long-term trends, differences between countries, and macro-level factors were assessed using qualitative and quantitative analysis of economic and financial indicators for a sample of 74 countries from 1978 to 2022. The article confirms that Russia and most other countries have been experiencing a steady downturn in total factor productivity. In some cases, productivity has been falling since the 2008 global financial crisis because key factors changed in the post-crisis period. In particular, growth of TFP has become correlated with increasing fixed investment, a high level of domestic financial development and protection of property rights, and limitation of state intervention in the economy, as well as with following a model of capitalism that allows for a moderate level of state ownership. Those developing countries of Central and Eastern Europe that have consistently implemented market-oriented reforms have also been able to sustain growth. The increasing importance of highly country-specific variables suggests that countries are trying to make greater use of domestic economic policies to support TFP growth and thus counteract the global productivity decline observed by many economists. Although individual countries may succeed in maintaining their growth, such measures are not sufficient to prevent a global slowdown.

The purpose of the article is to analyze the behavior of economic agents with limited rationality in a New Keynesian model which postulates that imported equipment and technology are one of the factors of production and that households consume only domestic products. Economic agents’ expectations are based on stationary values for the output gap and inflation and also on extrapolation of the latest available data on these variables. The weighted shares of agents applying these rules change endogenously. Histograms of the frequency distribution of the degree of optimism and the impulse responses of monetary policy shocks and technology shocks to the variables under study indicate that a less open economy tends to undergo an economic cycle with a smaller amplitude than a more rigid economy. An analysis of the trade-offs between inflation volatility and the output gap established their non-linear nature (in contrast to standard models with rational expectations). The results from analysis of trade-offs was that stabilization of inflation in models with limited rational expectations requires an increased interest rate reaction compared to a similar reaction for a model in which agents have rational expectations. The results obtained may be useful in designing monetary policy to stabilize inflation and output gaps.

The paper develops a dynamic stochastic general equilibrium (DSGE) model of the Russian economy based on an endogenous housing sector and three categories of homeowners – patient, impatient and non-Ricardian. The DSGE model is applied from the first quarter of 2010 to the fourth quarter of 2019 using a Bayesian method for minimizing the discrepancy between theoretical and empirical impulse responses to a shock due to modified terms of trade. The model is then employed to provide a quantitative assessment of how macro variables respond to shocks generated by the housing market, interest rates, mortgage subsidies, financial liberalization, and altered terms of trade. At the same time, the impact of shocks on a number of economic indicators is largely determined by the functional form of household utility, as demonstrated by the robustness test. The results obtained based on the model also do not demonstrate a strong inertial effect in the economy due to the revival of the residential real estate construction sector, and they contradict a number of studies and expert estimates based primarily on the input-output model. One reason for this discrepancy may be the analysis, which is based on a horizontal supply curve, resulting in an overestimation of the impact of the construction sector on the economy. This DSGE model can serve as a starting point for scenario-based projections of the dynamics of the residential real estate market and the associated mortgage market, for testing the impact of various policy measures on the housing sector, and for assessing their effects on various categories of households.

After external trade restrictions were imposed on Russia and China in recent years, their access to foreign technologies decreased. This created new incentives for scientific and technological partnership between the two countries. In addition, an analysis of strategic documents indicates that the US and the EU are likely to increase economic and technological pressure in the future. This article analyzes China’s experience in shoring up technological sovereignty under sanctions, an exercise which can be instructive for many countries. China’s long-term scientific and technological policy follows a catch-up development model, which has enabled a transition from borrowing simple technologies via specialized institutions (joint ventures, special economic zones, etc.) to global leadership in R&D and technologies that has been made possible through developing human capital and applying preferential treatment to local innovative businesses. Although Russia is one of the world’s leading scientific and technological centers, to some extent it lags in developing high-tech businesses and exports. Moreover, for some time it has been importing advanced products and technologies, some of which are now being quickly replaced by Chinese versions as Western companies have exited. The article applies a SWOT analysis to Russian-Chinese scientific and technological cooperation in order to highlight the benefits of this collaboration, especially concerning machine tools, microelectronics, and aerospace. The benefits from such partnership will materialize for most high-tech industries over the long run by means of joint scientific research. However, one cannot ignore the risks for Russia due to increased technological dependence on a single partner and the potential outflow of personnel and technology, as well as risks for China related to potential secondary sanctions.

The article examines the practice of engaging private providers to deliver public social services in Russia, as well as the legal regulation applicable to those activities. In addition, it outlines the evolution of the legislation and incentives affecting the access of private providers to the public services market, what their actual share in this market is, and the benefits and risks from expanding it. The author’s overall conclusion is that involving private providers to deliver public services is advisable, but it should not be an end in itself. The consequences of this policy for the state budget, public infrastructure, and consumers should be considered. In keeping with this recommendation, the author suggests legislative amendments designed to eliminate artificial incentives for expanding the share of private providers in the public services market while maintaining state control over the volume of financing of the public infrastructure in order to prevent its degradation. The article also analyzes the Russian system for independent assessment of the quality of public services (IQA) which began in 2015 and assesses its suitability for comparing the quality of services from public and private providers. The author finds shortcomings in the IQA methodology, which artificially inflate the overall level of assessments. This becomes a disincentive for providers to improve the quality of their services and also reduces public confidence in the results of IQA. This analysis of IQA is used to generate proposals for improving its methodology by making its results more objective.