2023. vol. 27. No. 4

The paper investigates the effectiveness of government support measures provided for small and medium enterprises during the spread of COVID-19. On the one hand, government sup­port aimed at maintaining the economy during the pandemic helped companies survive in the short term, on the other hand, it could lead to distorting allocative effects in the long term (especially if support was mainly allocated to less productive firms). We apply a counterfactual impact evaluation method to quantify the effect of government support on the productivity of SMEs during COVID-19. We assess the effect of four groups of support measures: financial support, support for innovation, property or tax support, and other types of support. The resulting indicators are total factor productivity (TFP) of firms, calculated as the residuals of the estimated production function, and labor productivity. The analysis showed that, in general, government support offered during the COVID-19 crisis has had a positive impact on the productivity of firms. On average, initially more productive and younger firms were more likely to receive support – so, apparently, there was no distorting effect of support. Despite the fact that the effect of support was relatively small, it still did its part to contain the fall in aggregate productivity in 2020. The effect of support for innovation, as well as tax support, was especially high. The effect of subsidies and other financial measures was lower and more ambiguous, the effect of other measures was insignificant.

This paper investigates variations in the accuracy of forecasting key macroeconomic indicators through the comparison of Frequentist and Bayesian vector autoregression (VAR) models. The primary aim of the study is to identify the most effective prior type in minimizing forecast errors for the key macroeconomic indicators in the context of the Russian economy. A significant aspect of this research involves elucidating the theoretical foundations of Bayesian methods and delineating the roles of different priors in the prediction of macroeconomic indicators. A pivotal consideration in the application of the Bayesian approach is the diversity of priors, such as Jeffreys and Minnesota, which may overlook economic considerations like inflation targeting and neutral money. Conversely, certain priors, such as steady-state or independent normal-Wishart priors, are grounded in economic policy. The study delves into the nuanced interplay between these priors and their implications for forecasting accuracy. The empirical findings reveal that all Bayesian VARs exhibit superior forecasting accuracy compared to the classical VARs. Furthermore, expanding the model's scope from a limited number of variables (4) to a more comprehensive set (18) enhances forecast precision, as evidenced by the escalating log-predictive scores, Model Confidence Sets, and The Diebold-Mariano test. Simultaneously, the BVAR with the steady-state prior has demonstrated the lowest forecast error over a two-year period, but the prediction with the Minnesota prior looks relatively stable in all horizons.

The paper is devoted to studying the links of Russian economy with EU, USA, China and ASEAN in intermediate trade. The statistical basis is the OECD Trade in Value Added Database that contains a set of inter-country input-output tables for 2018. Such data allow tracking inter-country trade flows for 67 countries and 45 industries by the direction of use (the data help to see which industries act as consumers of intermediate products). The analytical apparatus is based on input-output analysis and matrix algebra. The methodology of the study is based on calculating the Leontief and Ghosh input-output multipliers – not for the global economy as a whole, but for the regional blocs of countries, and also with a focus on the role of Russia as a consumer and supplier of intermediate products. The three matrices reflecting the value-added distribution (the ‘source-sink’ matrix, the ‘source-assembly’ matrix and the matrix of domestic and foreign contents of a country’s final good exports) are also calculated.

The conclusions regarding the importance of Russia’s links with the mentioned countries and country blocs in various industries and in different roles (consumer or supplier of intermediate products) are the following. For Russia, industries that are sensitive to intermediate imports are machinery, rubber and plastics, and textiles. Computer equipment and electronics extensively rely on Chinese intermediate goods, while the automotive industry depends primarily on intermediates from EU and other countries (Japan, South Korea). Russia is an important supplier of intermediate resources such as fuel, ores, metals, chemical products, timber industry products. China primarily relies on Russian primary energy and forest resources, while EU uses a wide range of fuels and metals, and USA extensively imports metals and chemi­cal products. Russia is embedded in global value chains mainly as an exporter of intermediate products and a consumer of final goods and services. Importance of intermediate imports for production or exports from Russia is limited.

One of the global macroeconomic trends of recent years is the increase of public debt by many developed and developing countries. The global cycle of interest rate hikes that began in 2021 poses risks to debt sustainability, especially in developing countries. These trends predetermine the growing relevance of research in the field of public debt sustainability. The paper surveys the state analyzes the main factors of dynamics of the public debt of four Central Asian countries – the Republic of Kazakhstan, the Kyrgyz Republic, the Republic of Uzbekistan, the Republic of Tajikistan. It is shown that the state of public debt in these countries is significantly different. Namely, the amount of debt, its structure, as well as approaches to debt management are significantly different. In particular, the paper describes the history of Eurobonds placements by the considered countries and shows that the efficiency of this instrument was significantly different. The paper presents the results of factorial decomposition of the growth of public debt,which allows to evaluate the sources of debt sustainability risks. It is shown that for the Republic of Kazakhstan the main source of risk is the budget deficit, while for the other considered countries it is the devaluation of the national currency.

Based on the above analysis, recommendations are made to improve the management of the public debt of the considered countries, which appear to be highly important for the reduction of debt sustainability risks for the considered countries. These recommendations include the clarification of liability accounting methodology, increase of transparency of public debt data, development of a risk assessment system based on the decomposition of debt growth, introduction of fiscal rules or other legal restrictions on debt dynamics, development of the domestic debt market.

Limited access to low-cost financing hinders the development of the use of solar photovoltaic technology. A significant way to solve this problem may be the securitisation of leasing assets (SLA) in the solar energy sector, which has the ability to provide additional liquidity in the renewable energy market. The article presents the theoretical aspects of emission financing of solar energy through securitization, defines the SLA in solar energy, examines the diversity and essence of contractual relations that develop regarding the supply and operation of solar equipment on the roofs of houses, their investment component. These agreements form portfolios that combine the assets of small solar energy users – households into a single transaction that is attractive to all parties, and which will open up additional opportunities for the use of renewable energy sources for investors. The pro- and contra mechanisms of SLA application in solar energy are considered. It is questioned that these transactions are characterized by excessive collateral. The parameters and structure of the analyzed market are evaluated. The author formalized the calculation of emissions reduction during the electrification of houses by replacing coal with solar energy generated by panels. The analysis reflecting the results of SLA transactions in solar energy in the USA in 2013–2022 under 729478 contracts was carried out. Conclusions are drawn regarding the further application of an effective financial mechanism.

The Russian university admissions mechanism which is based upon a combination of the university proposing deferred acceptance algorithm and serial dictatorship is shown to generate unstable and manipulable allocations. To improve on the mechanism, we propose a sequenced student proposing deferred acceptance (DA) algorithm with a serial dictatorship which is followed after every cycle of the student-proposing DA, allocating state-funded placements and offering the opportunity to decommit and be allocated to tuition placements based on the hybrid STB-MTB tie-breaking rules (Single Tie Breaking – Multiple Tie Breaking rules). The proposed algorithm will satisfy both stability and strategyproofness assuming the Russian higher education system is defined as a large market and universities cannot manipulate their preferences. In addition, this paper deals with the possibility of students taking a risk of preference misrepresentation to improve their allocation despite the fact the mechanism is strategy-proof and chances of success are low. We identify that the profitability of preference misrepresentation depends on the size of the market (the number of universities participating in the algorithm), preference list size, and existence of a recommendation mechanism. The paper also reviews how truth-telling can be promoted specifically in the form of recommendation mechanisms being applied in the university admissions systems.