Scientific reviews. Рубрика в журнале - Economic and Social Changes: Facts, Trends, Forecast
Economy, standard of living and quality of life in the region (reflections on the dictionary-reference book regional economics Vologda Research Center of the Russian Academy of Sciences)
At the new stage of Russia’s development, it becomes especially important to find solutions to urgent economic and social issues of regional development so as to ensure full economic sovereignty and decent living standards and quality of life for Russian citizens. The article discusses the issues related to increasing the role of scientific support in addressing these problems through the prism of a notable scientific and practical phenomenon - the publication of the dictionary-reference book Regional Economics in 2021; the book was prepared by a team of authors at RAS Vologda Research Center and contains the results of the 30-year work of VolRC RAS on providing scientific and practical support to regional and local authorities of the Vologda Oblast, which contributed to the development of the region’s economy, raising the standard of living and improving the quality of life. The published scientific and practical methods for solving regional demographic, economic and social problems and improving the performance of regional and local government bodies represent the main achievements of the book. The article shows that theoretical, methodological and practical solutions to topical regional issues, using the example of the Vologda Oblast, provide scientific and practical communities of other Russian regions with tools for addressing similar problems, taking into account Russia’s spatial features. We outline a number of considerations to develop the theoretical, methodological and practical base of the book so that its methods could be applied creatively in other regions of Russia.
Implications of precarization in the context of generational groups: direct and indirect effects
The effects of employment precarization are the subject of active discussion in the scientific literature. Despite the novelty of the topic, the negative impact of this process on the labor and daily life has been subject of a large number of works over the previous decade. At the same time, age specifics have not been widely reflected in studies: as a rule, authors focus on the population as a whole or its individual categories, for example, youth. The purpose of the article is to analyze and generalize the existing experience of studying the impact of employment precarization on generational groups of the economically active population. For this purpose, we have examined the situation of young, middle-aged and older workers involved in unstable labor relations. The information base is the Russian and foreign sources of empirical orientation; in the work we have used general scientific methods. The results show that the impact of employment precarization on generational groups has serious specifics. For young people, job instability mainly affects the planning of their own future forcing them to postpone the issues of starting a family and having children, leaving the parental home, etc. Prolonged transition to stable employment harms mental health, which is most pronounced in adulthood, when instability becomes part of everyday life. It can be difficult to get out of the “precarity trap” because low earnings and social insecurity limit the ability to change the current situation. The effects of employment precarization for older people are ambiguous. Even taking into account all the disadvantages of unstable labor relations, having at least some work is often a necessity to maintain a habitual lifestyle. The main limitation of the research is the generalization of information obtained using various conceptual constructions and methodological tools.
Investigating the Approaches to National Innovation Systems Modeling
The article analyzes some modern approaches to modeling national innovation systems that are presented in scientific literature. We use modern methods for analyzing bibliography and preparing literature reviews: co-occurrence, and the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) method. With the help of this approach we conduct relational analysis of documents by systematizing and arranging keywords into special semantic clusters that reflect interest in modeling national innovation systems. The research focuses on mathematical models of national innovation systems and models that use empirical quantitative data analyzed with the help of various econometric methods based on the Russian specifics of economic development. In this regard, when searching for and analyzing relevant sources, we used the filters “Russian innovation system”, “national innovation system and Russia”. We have revealed that the majority of publications focuses on such aspects as digitalization, neo-industrialization, innovation policy and technology. We identify four directions for modeling national innovation systems: macroeconomic modeling of innovation systems, modeling of growth based on the development of innovation systems, modeling of innovative activity of firms, modeling of institutional factors contributing to the development of innovation systems. The national innovation system is modeled mainly through the use of indicators related to patenting, the volume of exports and the production of innovations. Factors determining the development of national innovation systems in this context include R&D and innovation expenses, investment in technology, education, infrastructure, human resources and the quality of human capital. Conclusions on the analyzed models often do not coincide regarding the role of the state in financing innovations, the role of various elements of the institutional structure of the economy, such as intellectual property rights and mechanisms for their protection, as well as the role of political factors. On the other hand, the conclusions are consistent in terms of the impact of innovation on economic growth and development: we note a positive correlation with indicators reflecting the development of national innovation systems.
Modern ways to boost economic growth in regions
The paper reviews Russian and foreign research on modern ways to boost regional economic growth on the example of regional development institutions. We have chosen project management and regional development agencies as the most promising institutions for regional development. The growing interest in project management is confirmed by the data of the international database ScienceDirect, in which the number of articles on this topic for 1996-2019 was 19.5 thousand, and their annual number has increased 3.8-fold during this period. There is a similar trend in Russia: according to the electronic library eLIBRARY.RU the number of articles on this topic for the period from 2000 to 2019 has increased 87.5-fold, and their total number for this period was 1.2 thousand. Our main research method is cross-country comparative analysis. We investigate advantages and disadvantages of project financing on the examples of the Sydney Opera House (Australia), the Olympic Stadium in Montreal (Canada), the Concorde supersonic airliner (France-UK), the Suez Canal (Egypt), the Hubble Space Telescope (USA-EU), the Humber Bridge (UK). While studying international experience of regional development agencies, we have classified them into three types: agencies for ensuring regional leveling within the country (Scotland, Australia, Canada); agencies for ensuring economic leveling within an international association of countries (EU-Poland, Romania, Portugal); agencies that help countries join the world’s leading nations on the basis of the innovative economy (China, Malaysia, Botswana). A summary analysis of the works that study the activities of regional development agencies has allowed us to present the institutions under consideration on a system-wide basis and to identify their weak and strong points that should be taken into account in the development of this tool that helps enhance economic growth in Russia’s regions.