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Objective: to conduct a comprehensive macroeconomic assessment of the state of the Russian small and medium enterprises (SMEs) sector through the prism of a multicomponent model of well-being.Methods: general scientific methods of structural and comparative analysis, as well as specific scientific methods (static analysis for processing data from Rosstat, the Russian Federal Tax Service, the Public Opinion Foundation; expert assessments for interpreting surveys; graphical analysis for visualizing dynamic series; modeling for developing a conceptual model of the SMEs well-being).Results: the research substantiated the need to apply a comprehensive approach to the analysis of small and medium enterprises (SMEs) as part of the concept of economic agents’ well-being. The author performed a theoretical analysis of the well-being phenomenon and formulated a definition of the small and medium businesses’ well-being. Based on the adaptation of C. Ryff’s six-factor model, the author developed and tested a seven-component model of the SME sector well-being at the macro level. The model components analysis revealed a contradiction: while national projects formally achieve some of the targets (number of employees, share in non-resource exports), the key indicator (SMEs’ share in GDP) remains stagnant at 20-22%. At the same time, there is pessimism in business sentiment, high tax and administrative pressure, a shortage of qualified personnel, a reduction in government support and a low level of trust in institutions.Scientific novelty: it consists in the development of an original macroeconomic model of the SME sector well-being, expanded with the “Involvement in digitalization processes” component, which adequately reflects the modern economy challenges and allows overcoming the fragmented research in this sector.Practical significance: the obtained results and the proposed model can be used by government authorities to adjust economic policies and support programs for SMEs, focusing them on solving systemic problems identified during the component analysis. The article materials are also applicable in scientific and educational activities for the interdisciplinary study of the phenomenon of economic agents’ well-being.

The study is extremely necessary for the economy of Ukraine. In the period of war, it is necessary to have an effective strategy of economic development, regulating the activities at all levels of economic development of the state. The study used the correlation and regression analysis and the method of SWOT-analysis, which allowed to evaluate the National economic strategy developed by the state until 2030 with its adjustment during the war. The economic development strategy is divided into micro-, meso-, macroeconomic levels. At each level, the directions of development of all systems are defined. Ukraine has a very large potential for economic development. Military actions allow the state to attract foreign investment and find reliable partners among foreigners. But the war has taken away the industrial regions and there is a need to specialize production in safer regions of the state. A successful economic development strategy will select the most promising and significant factors.The purpose of the research of the article was to determine the strategy of economic development of Ukraine during the war. The selected areas of research: assessment of the National economic strategy by 2030 and its possible application for the period of war; the main directions of economic development strategy for use during the war; the effectiveness of the proposed directions of development strategy of economic development. The conclusion reflects the main directions of the economic development strategy proposed for use in the war with certain vectors of development at the micro-, macro-,and meso-economic levels. The results of the SWOT-analysis are clearly described and compared with the strategic directions in the National Economic Strategy until 2030. Proposed directions for the implementation of actions in each development environment.

Since carbon price volatility is critical to the risk management of the CO2 emissions trading market, research has focused on energy prices and macroeconomic drivers which cause changes in carbon prices and make the carbon market more volatile than other markets. However, they have ignored whether the impact of carbon price determinants changes when the carbon price is at different levels. To fill this gap, this paper applies a semiparametric quantile regression model to explore the effects of energy prices and macroeconomic drivers on carbon prices at different quantiles. The model combines the advantages of parameter estimation, nonparametric estimation and quantile regression to describe the nonlinear relationship between carbon price and its fundamentals, which do not need to make any assumptions about the random error. Carbon prices are high–tailed and exhibit higher kurtosis, the traditional models which tend to assume that data are normally distributed can’t perform well. Furthermore, the semiparametric model doesn’t need to assume that the data are normally distributed. Therefore, the semiparametric model can effectively model the data. Some new evidence from China’s emission trading scheme (ETS) pilots shows that energy prices and macroeconomic drivers have different effects on carbon prices at high or low quantiles. First, the negative impact of coal prices on carbon prices was greater at the lower quantile of carbon prices in the Shenzhen ETS pilot. However, the effects of coal prices were positive in the Beijing ETS pilot, which may be attributed to great demand for coal. Second, oil prices had greater negative effects on carbon prices at higher quantiles in Beijing and Hubei ETS pilots. This can be attributed to the fact that businesses use less oil when carbon prices are high. For the Shenzhen ETS pilot, the effects of oil prices were positive. Third, natural gas prices have a stronger effect on carbon prices as quantiles increased in the Beijing and Hubei ETS pilots. Lastly, the effects of macroeconomic drivers on carbon prices at low quantiles were stronger in the Shenzhen ETS pilots and higher at the medium quantiles in Beijing and Hubei ETS pilots. These findings suggest that the impact of determinants on the carbon prices at different levels is not constant. Ignoring this issue will lead to a missed warning about the risks of the carbon market. This study will be of positive significance for China’s emission trading scheme (ETS) pilots, in order to accurately monitor the effects of carbon prices determinants and effectively avoid carbon market risks.

Empirical research of intellectual capital in term of regional development of the Republic of Serbia aims to show and explain the function of intellectual capital in the regional development of the Republic of Serbia, and point out the disparities of national regions in terms of economic development and intellectual capital resources. Intellectual capital today is one of the most important social subsystems, which, by its scope and influence, is gaining an increasing importance in the development of modern society. As a complex, dynamic human process of knowledge use, intellectual capital is tied to the notion of “new knowledge-based economy”. Intellectual capital at the macroeconomic level is a new area of research that focuses on understanding, measuring, and reporting on intangible assets that may have an impact on the creation of national wealth. The concept of intellectual capital is abstract, unambiguous and complex, which leads to numerous differences in the interpretation of this economic category. The results of empirical research confirmed that intellectual capital is in a significant linear functional relationship with economic growth in the Republic of Serbia - in 63.5% of cases, economic growth is explained by intellectual capital resources in the period 2012-2018. Also, the research confirmed significant inequalities in the development and available resources of intellectual capital in the regions of the Republic of Serbia.

A joint effort led by the African Development Bank and the World Bank, 'Leveraging Migration for Africa' is the first comprehensive publication on harnessing migration, remittances, and other diaspora resources for the development of Africa. It comes at a time when countries in Africa and elsewhere are grappling with difficult choices on how to manage migration.Policy makers can help leverage the contributions of migrants to the development of Africa, reduceremittance costs, improve the efficiency of remittance markets in both origin and destination countries, and address the needs of the origin countries without restricting the emigration of high-skilled professionals. Innovative financing mechanisms such as issuance of diaspora bonds and securitization of future remittance flows can help finance big-ticket projects, such as railways, roads, power plants, and institutions of higher learning that will, step by step, help to transform Africa. This volume contributes to a greater understanding of migration and its potential role in Africa?s development.

We build an aggregate model with different size houses and liquid assets. Typical households are born, are subject to idiosyncratic earnings risk, and save for both life-cycle reasons and housing reasons. Typically, a subset of these households, after accumulating some assets, make a down payment and buy a small starter's house or flat. As time passes, some households upgrade to a larger and nicer house. Households with houses may also eventually downgrade to a flat or even to no house and flat owners may sell. Our specification attempts to replicate some important features of modern aggregate economies: The distribution of earnings and of housing and nonhousing wealth as well as some macroeconomic aggregates, including features of the mortgage issuing sector.

Competitiveness is a broad subject with applications at the level of the firm, industry, region, nation, and global economy. Each one of these aspects has a rich literature drawn on by academics and policy makers over a long period. This book seeks to present a broad overview of the main ideas underlying competitiveness and its applications, highlighting, and discussing in greater depth the topics that are of relevance currently. The book draws out the experiences of and lessons for developing economies and examines in detail the role for policy. This paper is structured as follows: chapter one addresses competition and competition policy; chapter two examines competitiveness by analyzing its many different indicators; chapter three looks further at indexes of national competitiveness that describe international competitive performance; chapter four addresses innovation, an increasingly important aspect of competitiveness; and chapter five discusses competitiveness and clusters.

We evaluate the asset pricing implications of a class of models in which risk sharing is imperfect because of limited enforcement of intertemporal contracts. Lustig (2004) has shown that in such a model the asset pricing kernel can be written as a simple function of the aggregate consumption growth rate and the growth rate of consumption of the set of households that do not face binding enforcement constraints. These unconstrained households have lower consumption growth rates than all other households in the economy. We use household data on consumption growth from the U.S. Consumer Expenditure Survey to identify unconstrained households, to estimate the pricing kernel implied by these models, and to evaluate their performance in pricing aggregate risk. We find that with low risk aversion these models cannot generate a substantial equity premium. On the positive side for high values (over 30) of the relative risk aversion coefficient, the limited enforcement pricing kernel generates a market price of risk that is substantially closer.

This article analyzes the impact of stochastic skill-biased technological change on earnings inequality in a general equilibrium OLG model. Wage dispersion is determined by the heterogeneity of skills by allowing for productivity differences due to education, ability, and age. The model performs well in reproducing stylized facts on the time pattern of the U.S. wage distribution and human capital accumulation. In particular, it shows that slow adjustment of the supply of educated labor can itself explain the nonmonotonic time pattern of the college premium.

Arecession can be defined as “a general, unwanted, self-perpetuating but temporary, mutual reduction in exchange.”1 In a recession, people want to buy and sell more than they are actually able to. The Great Recession of 2008– 2009 is an example; another one is the Great Depression, which started in 1929 (a depression is a deeper and longer recession). Less exchange implies fewer jobs and employment available on the market. Since the reduction in exchange is unwanted, the consequent unemployment is involuntary. In a recession, society is stuck under its production frontier. In these circumstances, Keynesians argue, the state can increase aggregate demand by creating jobs for the unemployed or with other forms of spending. Jobs created in the process would not have existed otherwise and are thus efficient, for they bring society back onto, or closer to, its production frontier. Does this objection, which was already alluded to in the previous chapter, make sense?