Search

Concerns about climate change are a hot topic in the current debate about a sustainable future, and despite more than 30 years of international conferences, including the Intergovernmental Panel on Climate Change (IPCC) and the United Nations Climate Change Conference (COP), the annual usage amount of fossil fuel-based energy sources has remained largely unchanged, and the green transition to a carbon-free energy system is progressing at a much slower pace than anticipated. This paper presents an original approach that consists in addressing the green transition’s dilemmas by analyzing the complex interplay of strongly interwoven forces hindering the rapid adoption of so-called green energy sources scrutinized from a three-fold perspective: socio-psychological; political–strategic and territorial; and technological. Moreover, these forces are ranked according to the magnitude of their impact on the anticipated transition to green, and it is estimated by logistic fit extrapolation that the total share of the contribution of low-carbon sources might reach a maximum of about 25% among all energy sources in 2050. A final original picture is presented, summarizing how all the involved forces are acting upon the expected transition as well as their consequences.

The global energy transition is an uneven process, fundamentally related to the level of economic development of countries and their access to energy resources (renewable and non-renewable) to a large extent. The global climate is interconnected, and all nations impact it through their products and services. The six countries discussed—China, Brazil, Germany, Japan, Russia, and India—account for 44.8% of global primary energy consumption and 49% of global CO2 emissions. Each of them has its own strategy for achieving carbon neutrality, based on different decarbonization scenarios, which, according to the authors, depend on geopolitical factors, national economy characteristics, and the established pragmatic goals and objectives. However, the “green agenda” itself may not always be among the top priorities when formulating energy strategies. The study objective is to analyze the feasibility of the stated goals in these countries using a combined logistic curve-based forecasting tool for predicting solar and wind production as well as investment volumes. It aims to justify the relation between solar and wind energy production and investment policies using a calculated technological coefficient. Results show similar, but time-shifted fluctuating investment dynamics in solar and wind energy trends in Japan, Germany and China, with Germany and Japan outperforming investment forecasts when considering the technology efficiency coefficient. Furthermore, the findings highlight the overwhelming appreciation of the unevenness of the green transition process, which will consequently make it impossible to meet the goals of the Paris Agreement until 2050. Taking these factors into consideration, exploratory decarbonization scenarios for these six major world economies alongside two dimensions, namely, the pace of green transition versus green technology and versus resources, are presented.

Concerns about climate change are a hot topic in the current debate about a sustainable future, and despite more than 30 years of international conferences, including the Intergovernmental Panel on Climate Change (IPCC) and the United Nations Climate Change Conference (COP), the annual usage amount of fossil fuel-based energy sources has remained largely unchanged, and the green transition to a carbon-free energy system is progressing at a much slower pace than anticipated. This paper presents an original approach that consists in addressing the green transition's dilemmas by analyzing the complex interplay of strongly interwoven forces hindering the rapid adoption of so-called green energy sources scrutinized from a three-fold perspective: socio-psychological; political–strategic and territorial; and technological. Moreover, these forces are ranked according to the magnitude of their impact on the anticipated transition to green, and it is estimated by logistic fit extrapolation that the total share of the contribution of low-carbon sources might reach a maximum of about 25% among all energy sources in 2050. A final original picture is presented, summarizing how all the involved forces are acting upon the expected transition as well as their consequences. [ABSTRACT FROM AUTHOR]

The global energy transition is an uneven process, fundamentally related to the level of economic development of countries and their access to energy resources (renewable and non-renewable) to a large extent. The global climate is interconnected, and all nations impact it through their products and services. The six countries discussed—China, Brazil, Germany, Japan, Russia, and India—account for 44.8% of global primary energy consumption and 49% of global CO2 emissions. Each of them has its own strategy for achieving carbon neutrality, based on different decarbonization scenarios, which, according to the authors, depend on geopolitical factors, national economy characteristics, and the established pragmatic goals and objectives. However, the "green agenda" itself may not always be among the top priorities when formulating energy strategies. The study objective is to analyze the feasibility of the stated goals in these countries using a combined logistic curve-based forecasting tool for predicting solar and wind production as well as investment volumes. It aims to justify the relation between solar and wind energy production and investment policies using a calculated technological coefficient. Results show similar, but time-shifted fluctuating investment dynamics in solar and wind energy trends in Japan, Germany and China, with Germany and Japan outperforming investment forecasts when considering the technology efficiency coefficient. Furthermore, the findings highlight the overwhelming appreciation of the unevenness of the green transition process, which will consequently make it impossible to meet the goals of the Paris Agreement until 2050. Taking these factors into consideration, exploratory decarbonization scenarios for these six major world economies alongside two dimensions, namely, the pace of green transition versus green technology and versus resources, are presented. [ABSTRACT FROM AUTHOR]

In an unstable economic climate, all market participants want to know is when is the timing to overcome a recession, and what measures and means to use for economic recovery. In this regard, the process through which the Eurozone economy has gained momentum since the summer of 2022 has been a volatile one. This was reflected in a sharp rise in the price level, followed by a sharp rise in the ECB interest rates. The purpose of this paper is to provide short-term forecasts of the main parameters of monetary and fiscal policy by the euro area monetary authorities, based on a model developed by the authors. The distinctive feature of the presented and proposed model lies in the particularly careful selection of the parameter values based on actual statistical data. The statistics used for the proposed model cover the period from 2015 to December 2022. The simulation results show that the European Central Bank (ECB) needs to maintain a policy of high interest rates for a period of 12 to 14 months, which will help to bring inflation down to 2–3 percent in the future and move to a stage and phase of sustainable economic growth.

The paper aims to assess how the existing imbalance between the education system and the regional economy influences the formation of spatial inequality and uneven economic development. Based on the structural and comparative analysis of data on Russia and China as the members of the Organization for Economic Co-operation and Development, we demonstrate that the technologies of the 4th Industrial Revolution shift the demand for highly skilled labour force. This situation leads to the gap between labour demand and supply, as the education systems are oriented to the economic needs of the 3rd Industrial Revolution. We consider cross-country differences in the quantity of STEM graduates and researchers (science, technology, engineering, and mathematics) as a possible cause of spatial inequality in the context of digital transformation. Further, on the example of Russia, we apply correlation and regression analysis to show that the discrepancy between the skill level of graduates and market expectations contributes to regional development inequality. We demonstrate the strong relationship between the share of unemployed persons among the economically active population and the skills of the labour force for all federal districts of the Russian Federation. On average, an increase in the share of employees with higher or secondary vocational education by 1 % decreases unemployment by 0.32 %. Additionally, in all federal districts of Russia, there is a discrepancy between the economic need for highly qualified workers with higher education and the education system producing too many specialists with secondary vocational education. The discrepancy between the structure of skilled labour force produced by the education system and the employment structure in the labour market by 10 % increases unemployment by almost 1 %. The results of the study can be used by the government for creating the development strategy of the education system and reducing spatial inequality.

Seventeen sustainable development goals were formulated to create a harmonious world order for the benefit of different nations and peoples. At the same time, economic practice provides a lot of examples of conflicts of an economic nature between individual sustainable development goals. One of these conflicts is the need for environmental imperatives and economic growth when a massive assessment of land used for crop production and green energy projects is needed. The present paper considers a non-traditional approach to the mass evaluation of land plots on the condition that geographic information systems provide the main source of information, such as the case of land allocation for green energy facilities and evaluation of agricultural plots. The novelty of the proposed approach firstly means the development of a comparative approach, which receives much less attention in the valuation literature than cost and income approaches, as it can give an adequate picture of the current state of the market. The model includes the study of the entire dataset, the selection of model distributions and the construction of estimates based on model distributions. The methodology of multivariate lognormal distribution of factors and prices of analogues is used. The peculiarity of the market evaluation of land plots in such cases is, as a rule, the absence of rank predictors and sufficient number of continuous predictors, which provides a base for the application of a novel approach. The method of express testing of hypotheses about joint normality of logarithms of values of pricing factors and prices is proposed. The market value is estimated as an estimate of the modal value of conditional lognormal price distribution. Secondly, the problem of market valuation is solved in case of the almost complete absence of information about price-forming factors in the areas being assessed, and thirdly, the factors are determined based on geoinformation databases (distance to the nearest large city, regional center, federal highway, large rivers, lakes, and solid waste landfills), which allow for market assessment in the absence of information on pricing factors for land plots, except for the offer price and the plot area. The research was necessitated by the claim to determine on a specific date the cadastral value of agricultural land for the purposes of taxation, corresponding to the market value, in the almost complete absence of information on pricing factors in the assessed areas. The value of land reflects a complex combination of factors, so the use of the proposed mathematical toolkit allows for building a consistent model for the evaluation of land where improvements are absent or have no value in terms of land acquisition purposes.

The outburst of the COVID-19 pandemic and its rapid spread throughout the world in 2020 shed a new light on mathematic models describing the nature of epidemics. However, as the pandemic shocked economies to a much greater extent than earlier epidemics, the recovery potential of economies was emphasized and its inclusion in epidemic models is becoming more important. The present paper deals with the issues of modeling the recovery of economic systems that have undergone severe medical shocks, such as COVID-19. The proposed mathematical model considers the close relationship between the dynamics of pandemics and economic development. This distinguishes it from purely “medical” models, which are used exclusively to study the dynamics of the spread of the COVID-19 pandemic. Unlike standard SIR models, the present approach involves the introduction of the “vaccine” equation to the SIR model and introduces correction components that include the possibility of re-infection and other nuances such as the number of people at risk of infection (not sick with COVID but not vaccinated); sick with COVID; recovered; fully vaccinated (two doses) citizens; the rate of COVID infection; the rate of recovery of infected individuals; the vaccination coefficients, respectively, for those who have not been ill and recovered from COVID; the coefficient of revaccination; the COVID re-infection rate; and the population fluctuation coefficient, which takes into account the effect of population change as a result of births and deaths and due to the departure and return of citizens. The present model contains governance so that it not only generates scenario projections but also models specific governance measures as well to include the pandemic and restore economic growth. The model also adds management issues, so that it not only generates scenario forecasts but simultaneously models specific management measures as well, aiming to suppress the pandemic and restoring economic growth. The model was implemented on specific data on the dynamics of the spread of the COVID-19 pandemic in selected developing economies.

In an unstable economic climate, all market participants want to know is when is the timing to overcome a recession, and what measures and means to use for economic recovery. In this regard, the process through which the Eurozone economy has gained momentum since the summer of 2022 has been a volatile one. This was reflected in a sharp rise in the price level, followed by a sharp rise in the ECB interest rates. The purpose of this paper is to provide short-term forecasts of the main parameters of monetary and fiscal policy by the euro area monetary authorities, based on a model developed by the authors. The distinctive feature of the presented and proposed model lies in the particularly careful selection of the parameter values based on actual statistical data. The statistics used for the proposed model cover the period from 2015 to December 2022. The simulation results show that the European Central Bank (ECB) needs to maintain a policy of high interest rates for a period of 12 to 14 months, which will help to bring inflation down to 2–3 percent in the future and move to a stage and phase of sustainable economic growth. [ABSTRACT FROM AUTHOR]

The evolution of the socio-economic systems is a non-linear process and it contains periods with smooth changes and subsequent periods of sharp jump transformation. The general design of new prospects opens at a stage of the birth of evolutionary processes, their forecasting requires the analysis of the historical prerequisites and risks, which are closely integrated to the change of moods in society. With the collapse of the Soviet Union, the newly independent states have passed the transformational and evolutional stage of development from the regional economy (they actually were the regions) to the economy of the state; the Central and Eastern European countries have experienced a dramatic “drift” to the European Union. In the article, the results of almost 25 years’ transformation of these states are considered. New states, formed as a result of the collapse of the USSR, passed throughout three types of transformation. Firstly, it is the transformation at the ideological level. The transformation of the second type was purely economic. The third type can be characterized as the institutional (including structural and financial) transformation. It is shown that one of the important reasons for the modest economic performance in the post-Soviet space is that newly independent states ignore and do not use in the practice the principles of regional policy and regional modernization. One of the important characteristic of the social and economic evolution of the countries of Eastern Europe after 1990 became the process of stratification and social differentiation of society with an insufficiently strong middle class and the polarization in income levels between the different regions. The increasing polarization in the income levels of the various regions acts as the dominating trend of the growing economic inequality

At the present moment, leading industrial countries and such new and quickly growing economies as China and India that also actively use the possibilities provided by new technological platforms, form a new type economy known as “digital economy” or “economy of joint use”. As the new technological platform is based on information technologies, the best synergetic effect is achieved through using electronic platforms, with their number and variety quickly growing, so they are actually creating a new infrastructure for communication between the primary economic agents. A new ecosystem also provides new possibilities, including instrumental ones, for conduct of business, searching for jobs and developing the business environment. This article analyzes new trends in development of business in the conditions of a newly forming digital economy.

The industry development over the last hundred years has had a huge impact on the development of technological infrastructure and life change. Three main components of this development are related to personalization: a car as a personal vehicle and greater personal freedom; a personal computer as a means of intellectual autonomy; a personal phone as a means of freedom of communication and access to information. These three development factors significantly changed the employee psychology and created the conditions for diffusion of qualitatively new, synthesized (cyber-physical) technologies that became the basis of the Industry 4.0 and the Internet of Things – two main working concepts of industrial and infrastructural development for the next 20 years. The conventional or classical industrial systems that are dominant to the present day have mainly been based on the principles of human muscle energy replacement, but the technological changes of our days raise the question of the substantial scale of displacement of the living manpower both in production and in management and services. The process of technological and industrial transformation that has already begun will inevitably lead to the transformation of social and economic systems, and here the key problem will not only be the provision of a new quality of economic growth, but also the solution of the employment problem interfacing a new technological platform, the information and social infrastructure of society.

Seventeen sustainable development goals were formulated to create a harmonious world order for the benefit of different nations and peoples. At the same time, economic practice provides a lot of examples of conflicts of an economic nature between individual sustainable development goals. One of these conflicts is the need for environmental imperatives and economic growth when a massive assessment of land used for crop production and green energy projects is needed. The present paper considers a non-traditional approach to the mass evaluation of land plots on the condition that geographic information systems provide the main source of information, such as the case of land allocation for green energy facilities and evaluation of agricultural plots. The novelty of the proposed approach firstly means the development of a comparative approach, which receives much less attention in the valuation literature than cost and income approaches, as it can give an adequate picture of the current state of the market. The model includes the study of the entire dataset, the selection of model distributions and the construction of estimates based on model distributions. The methodology of multivariate lognormal distribution of factors and prices of analogues is used. The peculiarity of the market evaluation of land plots in such cases is, as a rule, the absence of rank predictors and sufficient number of continuous predictors, which provides a base for the application of a novel approach. The method of express testing of hypotheses about joint normality of logarithms of values of pricing factors and prices is proposed. The market value is estimated as an estimate of the modal value of conditional lognormal price distribution. Secondly, the problem of market valuation is solved in case of the almost complete absence of information about price-forming factors in the areas being assessed, and thirdly, the factors are determined based on geoinformation databases (distance to the nearest large city, regional center, federal highway, large rivers, lakes, and solid waste landfills), which allow for market assessment in the absence of information on pricing factors for land plots, except for the offer price and the plot area. The research was necessitated by the claim to determine on a specific date the cadastral value of agricultural land for the purposes of taxation, corresponding to the market value, in the almost complete absence of information on pricing factors in the assessed areas. The value of land reflects a complex combination of factors, so the use of the proposed mathematical toolkit allows for building a consistent model for the evaluation of land where improvements are absent or have no value in terms of land acquisition purposes. [ABSTRACT FROM AUTHOR]

The outburst of the COVID-19 pandemic and its rapid spread throughout the world in 2020 shed a new light on mathematic models describing the nature of epidemics. However, as the pandemic shocked economies to a much greater extent than earlier epidemics, the recovery potential of economies was emphasized and its inclusion in epidemic models is becoming more important. The present paper deals with the issues of modeling the recovery of economic systems that have undergone severe medical shocks, such as COVID-19. The proposed mathematical model considers the close relationship between the dynamics of pandemics and economic development. This distinguishes it from purely "medical" models, which are used exclusively to study the dynamics of the spread of the COVID-19 pandemic. Unlike standard SIR models, the present approach involves the introduction of the "vaccine" equation to the SIR model and introduces correction components that include the possibility of re-infection and other nuances such as the number of people at risk of infection (not sick with COVID but not vaccinated); sick with COVID; recovered; fully vaccinated (two doses) citizens; the rate of COVID infection; the rate of recovery of infected individuals; the vaccination coefficients, respectively, for those who have not been ill and recovered from COVID; the coefficient of revaccination; the COVID re-infection rate; and the population fluctuation coefficient, which takes into account the effect of population change as a result of births and deaths and due to the departure and return of citizens. The present model contains governance so that it not only generates scenario projections but also models specific governance measures as well to include the pandemic and restore economic growth. The model also adds management issues, so that it not only generates scenario forecasts but simultaneously models specific management measures as well, aiming to suppress the pandemic and restoring economic growth. The model was implemented on specific data on the dynamics of the spread of the COVID-19 pandemic in selected developing economies. [ABSTRACT FROM AUTHOR]

The article presents the main stages and ongoing results in the Republic of Kyrgyzstan in 1990-2008. Basic directions of reforms in agriculture, industry, and the financial sector as well as the establishment of market-oriented democratic institutions are analyzed. [ABSTRACT FROM AUTHOR]