Search Results (22)

Sustainable agriculture has been a focus of research for over three decades, gaining particular urgency with the escalation of global conflicts, especially the Russian–Ukrainian war. Selecting appropriate parameters for objectively assessing sustainable agricultural development remains challenging, with limited studies addressing the aggregation of all relevant indicators into a single analytical framework. Given that these indicators and their quantitative values change annually, continuous updating and analysis are essential. This study was guided by selected SALSA/PRISMA principles to structure the indicator-selection process for examining Ukraine’s agricultural sector, which is vital to both national and global food security and accounts for approximately 10% of GDP, more than 50% of exports, and nearly 17% of employment. Alongside climate change pressures, the sector faces severe disruption from military aggression, undermining its economic contribution and stability. This research identifies and selects the most relevant economic, ecological, and social indicators to assess sustainable agricultural development in Ukraine, comparing values before and during the war. Based on these, this study proposes the Sustainable Agriculture Index (ISA), an aggregated measure that integrates multiple dimensions of sustainability. The ISA was calculated using a normalized weighted aggregation approach across economic, environmental, and social indicators. This approach enables a comprehensive evaluation of Ukraine’s agricultural resilience and its capacity to contribute to sustainable development under crisis conditions. Full article

This paper proposes an innovative research algorithm “measurement—pattern—driving force—synergy” that determines the eco-efficiency of 83 Russian federal subjects (2000–2019) using the Slacks-Based Measure (SBM) model with non-desired outputs (incorporating comprehensive input indicators such as water resources and electricity input, and dual non-desired outputs of waste gas and wastewater). Combined with hot spot analysis, a gravity center model, and panel Tobit regression, we reveal the temporal-spatial evolution and driving mechanisms of eco-efficiency in resource-based economies. The research finds that the overall eco-efficiency of Russia is at a medium level and shows a dynamic correlation with the economic development stage. In the early stage of the period under review, there was a high degree of synergy, but the efficiency declined during the period of rapid economic growth. Later, it rebounded somewhat in tie with technological progress. Spatially, it presents a special pattern of low efficiency in the western European industrialized regions and high efficiency in the Arctic and Far East peripheral regions, reflecting the spatial heterogeneity of resource-dependent economies and the survival-constrained efficiency feature. The analysis of influencing factors indicates that per capita GDP has a significant positive driving effect on eco-efficiency, but the expansion of residents’ consumption, the improvement of education level and the dependence on foreign trade all have inhibitory effects, highlighting the path dependence of the current growth model on the structure of resource consumption. The research suggests that Russia should implement differentiated spatial governance in the future, promote the green transformation of consumption and trade structures, and strengthen the ecological orientation of the education and scientific research system to achieve a fundamental transformation of regional sustainable development from survival constraints to innovation-driven. Full article

This study examines the potential of grain trade within the context of global commerce, highlighting its role as a primary component of the worldwide agricultural market and a crucial factor in ensuring global food security and price stability. To achieve the research objectives, we utilized panel data from Russia, a leading player in the grain market, and employed a gravity model along with Poisson pseudo-maximum likelihood (PPML) to analyze the impact of demand factors and the economic openness of importing countries, as well as the effects of distance, sea access, borders, language, trade unions, and tariffs on exports. Our research challenges the notion that an increase in the wealth of countries leads to a corresponding rise in trade between them. In the case of grain, evidence indicates a negative contribution of GDP per capita in importing countries. The gravity model and PPML enabled us to assess individual country effects and quantitatively evaluate the potential for increasing Russian grain exports to Asian and African nations. We propose recommendations for enhancing domestic grain production and improving the effectiveness of marketing strategies in countries with underutilized export potential. Full article

Crises like the COVID-19 pandemic, the Russian-Ukrainian war, and challenges associated with sustainable development have emphasized the need for local food to increase the food system’s resilience. Therefore, this research analyzes the food self-sufficiency ratio (SSR) and revealed comparative advantage (RCA) of cereals in Western Balkan countries (Serbia, Bosnia and Herzegovina, Montenegro, Albania, and North Macedonia) and compares them with the same indicators for all European countries. The methodological framework of this research examined the food self-sufficiency and macro-level competitiveness for cereals in Western Balkan countries, as well as in Europe. The results of the research showed that all European countries have higher self-sufficiency in cereals (109.12%) and higher revealed comparative advantage (2.21) compared to the group of Western Balkans countries (71.89%; 1.53), which have lower values of the mentioned indicators. The results of econometric modeling for the Western Balkan countries showed that GDP per capita negatively influences the SSR of cereals, and agriculture value added per worker and area harvested under cereals positively influence the SSR of cereals. When it comes to the influence on the RCA of cereals in the Western Balkan region, the critical influence is GDP per capita, political stability, and agriculture value added per worker, all of which positively influence the RCA. Full article

The manufacturing industry makes a significant contribution to Russia’s GDP and exports, but it faces problems that hinder its development. The aim of this study is to estimate the relationship between intellectual capital and performance indicators of Russian manufacturing companies. The study analysed a sample of 23,494 observations of Russian manufacturing companies for the 2017–2020 period. The value-added intellectual coefficient (VAIC) and its components were used to evaluate the impact of intellectual capital on firm performance using polled ordinary least squares, fixed, and random effects models. Intellectual capital significantly and positively affects the performance of companies in both structural and human terms—both through the integrated coefficient VAIC and in the context of individual components of intellectual capital. However, the impact of structural and human capital on performance indicators is significantly lower than the impact of capital employed. There is a distinct focus of enterprises on making profit through the use of company assets, while in the case of Russian manufacturing companies, the potential for profit generation from structural and human capital remains unfulfilled. Full article

Sustainable development of the state implies a proportional change in the key macroeconomic indicators described by standard models, one of which is the exponential production function (a special case of the Cobb-Douglas function), where the number of employees (labor) and the value of fixed assets (capital) acts as factor inputs, and GDP becomes the output, and output elasticities of production factors are estimated. This function is successfully used to analyze and predict macroeconomic processes in both developed and developing economies. The purpose of the study is to use econometric modeling—applying the exponential Cobb-Douglas production function—to identify the presence or absence of dependencies of production factors (labor, capital, etc.) on the final product output in Russia. The study shows that in Russia, GDP does not significantly depend on fixed assets. The authors hypothesized that this discrepancy is due to underutilization of production capacities and proved that to reveal the real dependence of Russian GDP production on the value of fixed assets it is necessary to adjust the indicators published by Rosstat for utilization of production capacities, which made it possible to fully use the methodological capabilities of production functions for the analysis and forecasting of macroeconomic processes in Russia. Full article

The Russian invasion of Ukraine and the resulting warfare within direct proximity to the European Union (EU) have significantly changed the conditions of Europe’s energy policy. Consequently, the energy security agencies and governments have been deliberating over an energy trilemma: the problem of balancing affordability, security, and environmental considerations, with much greater ramifications than before the breakout of the current military conflict. The past structural similarities and differences of the EU member states’ dependence on Russian energy raw materials, and the factors that might have determined those differences, may be among the key drivers of future energy policy choices in Europe and the prospective paths of the European Green Deal (EGD). Historical convergence might encourage an EGD consensus, while divergent past patterns might not allow for such a single direction throughout the EU. The multifaceted research proposed in this paper, from descriptive statistics to multiple linear regression model analyses, identifies structural dissimilarities among the EU economies relating to their dependence on Russia. Key findings suggest that the past dependencies on Russian energy raw materials have not been similar across the EU countries, and have been associated with the economic size of the EU member states and their proximity to or remoteness from Russia. In this regard, economic size and distance from Russia may be significant determinants of certain dissimilarities. Some countries, especially Estonia, Lithuania, and Poland, have demonstrated a structurally different energy mix dependence on Russian fossil energy raw materials than countries more remote from Russia that boast a higher GDP per capita. Full article

The importance of environmental sustainability is becoming more and more obvious, so the rationale behind long-term usage of solely non-renewable energy sources appeared questionable. This study aims to identify, using Kaplan-Meier survival analysis and logistic regressions, the main determinants that affect the duration of Russian non-renewable energy exports to different regions of the world. Data were retrieved from the databanks of the World Development Indicators (WDI), World Integrated Trade Solution (WITS), and the French Centre for Prospective studies and International Information (CEPII). The obtained results point to the fact that approximately 52% of energy products survive beyond their first year of trading, nearly 38% survive beyond the second year, and almost 18% survive to the twelfth year. The survival of Russian non-renewable energy exports differs depending on the region, and the affecting factors are of different importance. The duration of Russian non-renewable energy exports is significantly linked to Russia’s GDP, Total export, and Initial export values. A decline in Russia’s GDP by 1% is associated with an increasing probability of a spell ending by 2.9% on average, in turn growing Total export and Initial export values positively linked with the duration of non-renewable energy exports from Russia. These findings may have practical relevance for strategic actions aimed at approaching both energy security and environmental sustainability. Full article

Food self-sufficiency in a large country with 1.4 billion people is very important for the Chinese government, especially in the context of COVID-19 and the Russian–Ukrainian conflict. The objective of this paper is to explore the spatial–temporal evolution and driving factors of non-grain production in thirteen major grain-producing provinces in China, which account for more than 75% of China’s grain production, using 2011–2020 prefecture-level statistics. In the present study, the research methodology included GIS spatial analysis, hot spot analysis, and spatial Durbin model (SDM). The findings of this study are as follows: (1) The regions with a higher level of non-grain production were mainly concentrated in the central and western regions of Inner Mongolia, the middle and lower reaches of Yangtze River and Sichuan, while the regions with a low level of non-grain production were mainly distributed in the Northeast Plain. The regions with a higher proportion of grain production to the national total grain production were concentrated in the Northeast Plain, the North China Plain, and the Middle and Lower Yangtze River Plain of China. The hot spot regions with changes in non-grain production levels were mainly distributed in the Sichuan region and Alashan League City in Inner Mongolia, and the cold spot regions were mainly distributed in Hebei, Shandong, Henan, and other regions. (2) An analysis of the SDM indicated that the average air temperature among the natural environment factors, the ratio of the sum of gross secondary and tertiary industries to GDP, the ratio of gross primary industry to the GDP of economic development level, the urbanization rate of social development, and the difference in disposable income per capita between urban and rural residents of the urban–rural gap showed positive spatial spillover effects. The grain yield per unit of grain crop sown area of grain production resource endowment, the total population of social development, and the area sown to grain crops per capita of grain production resource endowment all showed negative spatial spillover effects. The research results of this paper can provide a reference for the country to carry out the governance of non-grain production and provide a reference for China’s food security guarantee. Full article

The start of the full-scale Russian-Ukrainian war caused the largest wave of migration in the 21st century. More than five million Ukrainian citizens left for EU countries within a few months of the start of the conflict. The purpose of this paper is to forecast the level of health care expenditure in Ukraine for 2023–2024, considering the scale of migration and the fall in the level of GDP. The authors propose three scenarios for the development of Ukraine’s economy in 2023–2024, taking into account changes in the age structure of the population, migration, and the amount of health care expenditure: (1) Pessimistic, in which economic growth will resume only in 2024, with a GDP rise of 5.6%, provided that the war concludes at the end of 2022. Under this scenario, inflation will be about 21% in 2023–2024, a slight decrease compared with the previous year. Some 12% of the population of Ukraine will have emigrated, resulting in a corresponding 12% drop in health care expenditure in 2023–2024. (2) Basic (realistic), in which economic growth will be about 5% in 2023–2024, inflation will be under 10%, and migration will have accounted for 5% of the country’s population. Under this scenario, there will be an increase in health care expenditure of more than 40% in 2023–2024. (3) Optimistic, according to which rapid economic growth is expected in 2023–2024, inflation will not exceed 7%, the majority of those who left Ukraine in the early months of the war will return, and health care expenditure will increase by more than 70% in 2023–2024. The methodology of forecasting public expenditure on health care has been based on a six-step cohort method. The results have indicated that the cost of updating the age structure of Ukraine’s population every year will decrease due to the aging of the population, and the overall impact of demographic processes will be negative. The impact of mass migration due to the war creates a significant change in health care costs, requiring administrative bodies to monitor the situation promptly and make appropriate changes to the structure of budget expenditure. Full article

The sustainability of international trade is subject to immense pressure. Apart from obstructed logistics, disruption of production chains and changes in demand, the sustainability of international trade is heavily affected by the sanctions caused by the Russia–Ukraine conflict. This paper studies the factors predicting sustainable international trade in the post-Soviet region. We hypothesize that ongoing conflicts, infrastructure, language integration, geographical proximity, common border, and economic wellbeing significantly impact international trade. Methodologically we rely on linear and hierarchical regressions estimating a set of gravitation models (N = 15 countries—104 trading pairs; 2010–2020). The results suggest that Russian as a primary language and the average density of road networks positively predict bilateral trade volume. The geographical distance, infrastructure differences, military conflicts, and, surprisingly, the pair-average GDP per capita diminish bilateral trade. Countries’ GDP mediates the effect of GDP per capita. The results are robust over time. The results present an important insight into sustainable international trade within the region affected by the numerous military conflicts in the past and the war conflict between Russia and Ukraine nowadays. The rebuilding of Ukrainian transport infrastructure is one of the essential measures from the country’s point of view and a factor supporting internationally sustainable food supply. Full article

After the annexation of Crimea in 2014, many EU–Russia projects such as the concept of Strategic Partnerships, negotiations on the New Basic Agreement, and the abolishment of visa regime, among other important issues, were suspended. On top of that, the parties involved imposed mutual sanctions which seriously damaged bilateral trade relationships. The present article aims to analyse EU–Russia bilateral trade under the sanctions and low oil prices together with such factors as the growth of Russian and the EU’s GDPs per capita, geographical distance between parties and devaluation of Russian currency by applying a gravity model. Moreover, the model allows us to carry out simulations of circumstances as they would likely have unfolded had the sanctions not been imposed and if oil prices had remained at a reasonable level. Full article

This paper investigates the impact of the moderate growth of government borrowing on debt sustainability in 11 Russian regions over about 10 years, starting in 2010. The current study aims to assess the debt sustainability of the Russian region’s budget by determining Euclidean distance budget constraints and cluster analysis. This study is based on the methodology of hierarchical cluster analysis, which makes it possible to isolate regions of accumulation of objects from the aggregate data and combine them into homogeneous segments. The central hypothesis of this study is that by using this method, it is possible to increase the accuracy of the values that limit budget constraints in a region’s financial system. This study, using open data from the Federal State Statistics Service, is based on a database of statistical, financial, and economic indicators of the Russian economy. The calculations include about 45 macroeconomic indicators, which reflect the ratios of socio-economic development of the region’s financial system. The methodology described in the paper for assessing the debt sustainability of budget policy proves the need to calculate six indicators and determine the debt limits for the regions of each cluster. It finds a need to reduce the high debt burden of 46% of the regions belonging to the Northwestern Federal District. Confidence intervals for the debt limit suggest that the negative growth effect of high debt may start from levels of around 5% of the debt-to-GDP ratio and about 43% of the debt-to-revenue ratio. The results indicate that regions with a high level of debt sustainability include St. Petersburg city, the Leningrad region, and the Kaliningrad region. From a state debt policy perspective, the results provide additional arguments for debt reduction for the Republic of Komi, the Republic of Karelia, the Arkhangelsk region, and the Pskov region. The general conclusion of the study boils down to the need to reduce the debt burden of the budgets of some regions of the SFZO, as well as to the need to change the upper limits of debt, which are equally set for all regions by the Budget Code of the Russian Federation, to differentiated values of public domestic debt, taking into account the results obtained in the study. Full article

The purpose of this paper is to conduct a comparative analysis of monetization as a priority of the new monetary growth of the economies using the example of the Russian economy, identifying new trends in global practices of monetary factor management, as well as the search for ways to stimulate economic growth using the best international experience. Our paper tackles the novel research question of whether changing the priorities of monetary policy from targeting (and curbing) inflation to stimulating economic growth might yield more favorable economic results and what best world practices should be appropriately introduced in Russia to improve the effectiveness of monetary policy. The key results of the paper are focused on a comparative analysis of the economies’ development under the influence of monetary factors in comparison with the most progressive economies, the study of the best practices for increasing the monetization of national economies, and the identification of recommendations for determining the most optimal way to increase economic growth through the monetization of the economy. Monetarist views on the decisive role of fiat money in the development of the real sector of the economy, capital markets, payment and settlement systems, the standard of living of the population, and other important aspects of macro- and microeconomics have become the mainstream of government regulation. It seemed that by finding the right indicators of the relationship between interest rates, GDP, and inflation, all problems of economic growth could be solved. By increasing the amount of money faster than the achieved economic growth, it was believed that it was possible to stimulate GDP growth through monetary investments and credit, i.e., more money was issued than the value produced represented by the goods and services. Accordingly, new money that had no value had to create new value. We argue that monetization can be seen as the main factor in providing such incentives. Our results can be useful for central bankers, policymakers, and stakeholders in the banking and financial sector. The conclusions and recommendations of the authors are based on studies conducted using such research methods as content analysis, logical analysis, and statistical analysis. Full article

We examine a different approach to complete the decarbonization of the Russian economy in a world where climate policy increasingly requires the radical reduction of emissions wherever possible. We propose an energy system that can supply solar and wind-generated electricity to fulfill demand and which accounts for intermittency problems. This is instead of the common approach of planning for expensive carbon capture and storage, and a massive increase in energy efficiency and, therefore, a drastic reduction in energy use per unit of Gross Domestic Product (GDP). Coupled with this massive increase in alternative energy, we also propose using excess electricity to generate green hydrogen. Hydrogen technology can function as storage for future electricity needs or for potential fuel use. Importantly, green hydrogen can potentially be used as a replacement export for Russia’s current fossil fuel exports. The analysis was carried out using the highly detailed modeling framework, the High-Resolution Renewable Energy System for Russia (HIRES-RUS) representative energy system. The modeling showed that there are a number of feasible combinations of wind and solar power generation coupled with green hydrogen production to achieve 100% decarbonization of the Russian economy. Full article