Pub Date : 2023-01-01DOI: 10.15826/recon.2023.9.2.012
Jianglin Lu, L. Ruzhanskaya
Relevance: The need to find new sources of growth and structural development in old industrial regions has led to the growing interest in entrepreneurship and the requirements for fostering small and medium-sized businesses. Given the priorities of the Russian migration policy and the substantial number of migrants from China, it becomes evident that this demographic group holds significant importance for the country’s regional development. Research Objective: This study aims to identify the motivations and constraints of Chinese migrants involved in business activities in Sverdlovsk region. The research relied on questionnaires and supplemented them with in-depth interviews. The authors investigated 35 migrant companies across various industries and sizes, representing over 5% of all entrepreneurs in the region from 2016 to 2022. Between January and December 2022, six in-depth interviews were conducted with Chinese entrepreneurs who had been working in Sverdlovsk for 1 to 15 years. The study also uses data from the Ministry of Internal Affairs of the Russian Federation and the Unified Register of Small and Medium-Sized Businesses, which encompassed 638 entrepreneurs and 721 companies owned by Chinese migrants operating in the region from 2016 to 2022. Results: Chinese migrants are driven to engage in business activities in the Sverdlovsk region due to its expansive regional market, growth opportunities, and potential for high profits. However, they face barriers such as cross-cultural communication challenges, limited government support, and regulatory burdens. Conclusion: To support migrant entrepreneurs, regional state regulators should simplify documentation processes, offer legal services or advice, include foreign entrepreneurs in government support policies, and establish effective communication channels. These actions will create a conducive environment for entrepreneurship and business development in the region.
{"title":"Factors Influencing Chinese Migrants’ Entrepreneurial Activity in Russia: A Case Study of Sverdlovsk Region","authors":"Jianglin Lu, L. Ruzhanskaya","doi":"10.15826/recon.2023.9.2.012","DOIUrl":"https://doi.org/10.15826/recon.2023.9.2.012","url":null,"abstract":"Relevance: The need to find new sources of growth and structural development in old industrial regions has led to the growing interest in entrepreneurship and the requirements for fostering small and medium-sized businesses. Given the priorities of the Russian migration policy and the substantial number of migrants from China, it becomes evident that this demographic group holds significant importance for the country’s regional development. Research Objective: This study aims to identify the motivations and constraints of Chinese migrants involved in business activities in Sverdlovsk region. The research relied on questionnaires and supplemented them with in-depth interviews. The authors investigated 35 migrant companies across various industries and sizes, representing over 5% of all entrepreneurs in the region from 2016 to 2022. Between January and December 2022, six in-depth interviews were conducted with Chinese entrepreneurs who had been working in Sverdlovsk for 1 to 15 years. The study also uses data from the Ministry of Internal Affairs of the Russian Federation and the Unified Register of Small and Medium-Sized Businesses, which encompassed 638 entrepreneurs and 721 companies owned by Chinese migrants operating in the region from 2016 to 2022. Results: Chinese migrants are driven to engage in business activities in the Sverdlovsk region due to its expansive regional market, growth opportunities, and potential for high profits. However, they face barriers such as cross-cultural communication challenges, limited government support, and regulatory burdens. Conclusion: To support migrant entrepreneurs, regional state regulators should simplify documentation processes, offer legal services or advice, include foreign entrepreneurs in government support policies, and establish effective communication channels. These actions will create a conducive environment for entrepreneurship and business development in the region.","PeriodicalId":33206,"journal":{"name":"REconomy","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67263975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.15826/recon.2023.9.1.001
G. Chebotareva, A. A. Dvinayninov
Relevance. Structural changes in the Russian market create new trends, including energy supply in remote areas. The government is planning to redirect natural gas to domestic buyers. However, according to the estimates of biogas potential, it can fully meet the energy needs of households with no access to centralized gas supply. Research objective is to choose the optimal scenario of gasification in remote areas by evaluating the economic feasibility of several alternatives, including biogas technologies and the centralized gas supply system. Data and methods. The study focuses on the case of Sverdlovsk region and considers three scenarios of gasification in its remote areas. The method includes the calculation of the full discounted value of energy facilities, the comparison of their productive capacity, the analysis of the key external factors. Results. In terms of cost, the most economically feasible is the scenario of biogas plants using by individual households. However, accounting productivity, the scenarios based on the use of centralized gas supply or collective biogas plants. The economic feasibility of these two scenarios depends on the number of buildings serviced. Conclusions. The optimal scenario is the centralized gas supply. Despite its high costs, it can ensure the uninterrupted supply of the necessary energy amount to private households and does not depend on factors such as the availability of manure and organic waste and weather conditions. One more advantage is that Russia currently has a more elaborate and adequate legal framework regulating its use than for the other two options.
{"title":"Economic feasibility of gasification scenarios in remote areas (the case of Sverdlovsk region, Russia)","authors":"G. Chebotareva, A. A. Dvinayninov","doi":"10.15826/recon.2023.9.1.001","DOIUrl":"https://doi.org/10.15826/recon.2023.9.1.001","url":null,"abstract":"Relevance. Structural changes in the Russian market create new trends, including energy supply in remote areas. The government is planning to redirect natural gas to domestic buyers. However, according to the estimates of biogas potential, it can fully meet the energy needs of households with no access to centralized gas supply. Research objective is to choose the optimal scenario of gasification in remote areas by evaluating the economic feasibility of several alternatives, including biogas technologies and the centralized gas supply system. Data and methods. The study focuses on the case of Sverdlovsk region and considers three scenarios of gasification in its remote areas. The method includes the calculation of the full discounted value of energy facilities, the comparison of their productive capacity, the analysis of the key external factors. Results. In terms of cost, the most economically feasible is the scenario of biogas plants using by individual households. However, accounting productivity, the scenarios based on the use of centralized gas supply or collective biogas plants. The economic feasibility of these two scenarios depends on the number of buildings serviced. Conclusions. The optimal scenario is the centralized gas supply. Despite its high costs, it can ensure the uninterrupted supply of the necessary energy amount to private households and does not depend on factors such as the availability of manure and organic waste and weather conditions. One more advantage is that Russia currently has a more elaborate and adequate legal framework regulating its use than for the other two options.","PeriodicalId":33206,"journal":{"name":"REconomy","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67264221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.15826/recon.2023.9.1.003
S. Pyankova, M. Kombarov
Relevance. Considerable regional disparities in Russia pose a threat to the country’s economic security, which makes the task of identifying and supporting underperforming regions especially urgent. Research objective. The purpose of the study is to identify the struggling regions by using the "volcano" model. This model has not been previously used in studies on economic space features, which determines the novelty of the proposed research. We are also going to describe the possible ways to support these regions. Data and methods. The study uses correlation analysis to investigate the dependence of GRP of 85 Russian regions on the degree of their remoteness from the ‘vent’ region – the Khanty-Mansi Autonomous Area–Yugra. The analysis was carried out on the basis of cross-sectional data for 2018-2020. The study relies on the data on GRP provided by the Federal State Statistics Service (Rosstat). Results. The results of this study showed that, according to H.Giersch’s methodology, the Khanty-Mansi Autonomous Area-Yugra is the "vent" of the "volcano". By applying this methodology, we have also identified 13 struggling regions. An effective measure to support these regions is to transfer the federal component of the corporate income tax and VAT revenues to their budgets. Meanwhile, the volume of transfers provided to them from the federal budget should remain unchanged. Our calculations show that this measure can create a significant increase in GRP of the Russian regions at the aggregate level, exceeding considerably the losses of the federal budget. Conclusions. The study has shown that the ‘volcano’ models is better suited for the analysis of such countries as Russia, because it makes the research less time-consuming in comparison with the growth poles theory. The results of this study can be used by policy-makers developing the state fiscal policy.
{"title":"Giersch’s “Volcano” Model and its Application for the Analysis of Regional Disparities in Russia","authors":"S. Pyankova, M. Kombarov","doi":"10.15826/recon.2023.9.1.003","DOIUrl":"https://doi.org/10.15826/recon.2023.9.1.003","url":null,"abstract":"Relevance. Considerable regional disparities in Russia pose a threat to the country’s economic security, which makes the task of identifying and supporting underperforming regions especially urgent. Research objective. The purpose of the study is to identify the struggling regions by using the \"volcano\" model. This model has not been previously used in studies on economic space features, which determines the novelty of the proposed research. We are also going to describe the possible ways to support these regions. Data and methods. The study uses correlation analysis to investigate the dependence of GRP of 85 Russian regions on the degree of their remoteness from the ‘vent’ region – the Khanty-Mansi Autonomous Area–Yugra. The analysis was carried out on the basis of cross-sectional data for 2018-2020. The study relies on the data on GRP provided by the Federal State Statistics Service (Rosstat). Results. The results of this study showed that, according to H.Giersch’s methodology, the Khanty-Mansi Autonomous Area-Yugra is the \"vent\" of the \"volcano\". By applying this methodology, we have also identified 13 struggling regions. An effective measure to support these regions is to transfer the federal component of the corporate income tax and VAT revenues to their budgets. Meanwhile, the volume of transfers provided to them from the federal budget should remain unchanged. Our calculations show that this measure can create a significant increase in GRP of the Russian regions at the aggregate level, exceeding considerably the losses of the federal budget. Conclusions. The study has shown that the ‘volcano’ models is better suited for the analysis of such countries as Russia, because it makes the research less time-consuming in comparison with the growth poles theory. The results of this study can be used by policy-makers developing the state fiscal policy.","PeriodicalId":33206,"journal":{"name":"REconomy","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67264342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.15826/recon.2023.9.2.013
A. E. Sudakova, Dahel Mustafa Saleh Dahel
Relevance. Education is a significant factor in economic growth. However, the discussion about the principles for distributing higher education funding is still open, and the cases of individual countries are not sufficiently covered in research literature. Research objective. The study aims to determine the principles of financing based on the case studies of Russian universities. Foreign financing mechanisms are analyzed and compared with Russian practice that has similar foundations. Financing mechanisms are classified according to their distribution principle. Data and methods. The statistical base for the study is the data of a large-scale higher education monitoring project of 2019-2021. The study was conducted in more than 650 Russian universities. In order to determine the principles of financing, a correlation analysis is carried out to identify the correlation between the indicators. Universities are grouped by regions with different socio-economic characteristics, subgroups of universities within the regional division were identified. Results. The distribution of funding among Russian universities is based on the principles of quasi-competition and equalization. Universities located in regions with low indicators of socio-economic development are mainly financed to achieve equalization of educational activities, and, as the socio-economic situation in the region improves, funding is channeled into equalization of research activities. Another more obvious conclusion is that research activities of universities that participate in state programs are funded based on competition, while other universities have lower correlation between indicators, which leads us to the assumption that other universities’ research activities are funded based on the principles of equalization. Conclusions. The novelty of the study is the results that enrich the understanding of the principles for funding distribution in the Russian higher education system. Contrary to most studies of the concentration of resources around a limited number of institutions, the study concludes that resources and funding are distributed based on equalization, supporting the less competitive units of the system, and directing funding to regions with less stable socio-economic characteristics.
{"title":"Funding the Higher Education System: International Experience and Russian Practice","authors":"A. E. Sudakova, Dahel Mustafa Saleh Dahel","doi":"10.15826/recon.2023.9.2.013","DOIUrl":"https://doi.org/10.15826/recon.2023.9.2.013","url":null,"abstract":"Relevance. Education is a significant factor in economic growth. However, the discussion about the principles for distributing higher education funding is still open, and the cases of individual countries are not sufficiently covered in research literature. Research objective. The study aims to determine the principles of financing based on the case studies of Russian universities. Foreign financing mechanisms are analyzed and compared with Russian practice that has similar foundations. Financing mechanisms are classified according to their distribution principle. Data and methods. The statistical base for the study is the data of a large-scale higher education monitoring project of 2019-2021. The study was conducted in more than 650 Russian universities. In order to determine the principles of financing, a correlation analysis is carried out to identify the correlation between the indicators. Universities are grouped by regions with different socio-economic characteristics, subgroups of universities within the regional division were identified. Results. The distribution of funding among Russian universities is based on the principles of quasi-competition and equalization. Universities located in regions with low indicators of socio-economic development are mainly financed to achieve equalization of educational activities, and, as the socio-economic situation in the region improves, funding is channeled into equalization of research activities. Another more obvious conclusion is that research activities of universities that participate in state programs are funded based on competition, while other universities have lower correlation between indicators, which leads us to the assumption that other universities’ research activities are funded based on the principles of equalization. Conclusions. The novelty of the study is the results that enrich the understanding of the principles for funding distribution in the Russian higher education system. Contrary to most studies of the concentration of resources around a limited number of institutions, the study concludes that resources and funding are distributed based on equalization, supporting the less competitive units of the system, and directing funding to regions with less stable socio-economic characteristics.","PeriodicalId":33206,"journal":{"name":"REconomy","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67264126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.15826/recon.2022.8.1.003
V. Timiryanova, K. Yusupov, I. Lakman, Aleksandr F. Zimin
Relevance. Regional differences in per capita income are a matter of concern for many countries for many reasons, including the threat that such regional disparities pose to national security. Multiple tools and methods are used to investigate these disparities and fix them. The use of lower level aggregated data and the analysis that takes into account spatial interactions thus become particularly relevant because it allows us to reveal the diversity of interactions at the micro-level. Research objective. This study aims to determine the significance of spatial relationships at different levels of data aggregation and hierarchical dependencies in per capita income and highlight the level of administrative division (regional or municipal) that has the greatest impact on per capita income. Methods and data. The analysis relies on the data from 2,270 municipalities in 85 Russian regions. The Hierarchical Spatial Autoregressive Model (HSAR) was used to distinguish both spatial and hierarchical effects. We used three specifications of the model: with estimates of the spatial interaction on the higher level (spatial error at the regional level), on the lower level (spatial lag at the municipal level), and on both levels. Results. Spatial interactions explain the observed variation of per capita income at the municipal level data at both the higher (regional) and lower (municipal) levels but the model with the estimated spatial interaction on the higher level was better. Conclusion. Despite the importance of spatial interactions at the lower level, models that take into account spatial interactions only at the upper level may better explain the observed differences in some cases. Our findings contribute to the rather scarce research literature on spatial relationships on several levels of administrative division. We have shown that for each specific case it is important to identify not only the factors but also the spatial effects in relation to this or that level of the territorial hierarchy.
{"title":"Regional per capita income differences: Spatial and hierarchical dependencies","authors":"V. Timiryanova, K. Yusupov, I. Lakman, Aleksandr F. Zimin","doi":"10.15826/recon.2022.8.1.003","DOIUrl":"https://doi.org/10.15826/recon.2022.8.1.003","url":null,"abstract":"Relevance. Regional differences in per capita income are a matter of concern for many countries for many reasons, including the threat that such regional disparities pose to national security. Multiple tools and methods are used to investigate these disparities and fix them. The use of lower level aggregated data and the analysis that takes into account spatial interactions thus become particularly relevant because it allows us to reveal the diversity of interactions at the micro-level. Research objective. This study aims to determine the significance of spatial relationships at different levels of data aggregation and hierarchical dependencies in per capita income and highlight the level of administrative division (regional or municipal) that has the greatest impact on per capita income. Methods and data. The analysis relies on the data from 2,270 municipalities in 85 Russian regions. The Hierarchical Spatial Autoregressive Model (HSAR) was used to distinguish both spatial and hierarchical effects. We used three specifications of the model: with estimates of the spatial interaction on the higher level (spatial error at the regional level), on the lower level (spatial lag at the municipal level), and on both levels. Results. Spatial interactions explain the observed variation of per capita income at the municipal level data at both the higher (regional) and lower (municipal) levels but the model with the estimated spatial interaction on the higher level was better. Conclusion. Despite the importance of spatial interactions at the lower level, models that take into account spatial interactions only at the upper level may better explain the observed differences in some cases. Our findings contribute to the rather scarce research literature on spatial relationships on several levels of administrative division. We have shown that for each specific case it is important to identify not only the factors but also the spatial effects in relation to this or that level of the territorial hierarchy.","PeriodicalId":33206,"journal":{"name":"REconomy","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67262564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.15826/recon.2022.8.1.005
I. Savin, Denis K. Letyagin
Relevance. Economic growth can be achieved in two different ways: through technological improvements and reallocation of market shares from less to more productive units. Despite the significant research literature on innovation in Russia, the literature on market selection, especially at the sectoral level, is relatively scarce. This is the research gap that this study aims to address. Research objective. The article assesses how labor resource reallocation between sectors has influenced the dynamics of aggregate labor productivity in the Russian economy over the past two decades. Data and methods. For this purpose, the growth of aggregate labor productivity was decomposed into the growth of productivity within the sectors themselves and the reallocation of labor resources between them. This allowed us to conduct a quantitative estimation of the role of market selection at the sectoral level. For our study, we used data from Rosstat (from 2002 to 2018) and the World Input-Output Database (from 2000 to 2014). Results. For Rosstat data, the ratio of the effect of changes in labor productivity and labor resource reallocation by sector on total labor productivity over the period was 0.71/0.29, and for WIOD data it was 0.44/0.56. This indicates that labor resources are more likely to be reallocated to related sectors (e.g. between manufacturing industries). Conclusions. The results suggest that there is competitive market selection at the sectoral level and that labor has generally been reallocated to more productive sectors of the economy, contributing significantly to the growth of aggregate productivity in the economy. Our study shows the sectors of the economy where this reallocation has taken place, which may help to determine where this process is successful and where it needs additional stimulation.
{"title":"Estimating the role of labor resources reallocation between sectors on the growth of aggregate labor productivity in the Russian economy","authors":"I. Savin, Denis K. Letyagin","doi":"10.15826/recon.2022.8.1.005","DOIUrl":"https://doi.org/10.15826/recon.2022.8.1.005","url":null,"abstract":"Relevance. Economic growth can be achieved in two different ways: through technological improvements and reallocation of market shares from less to more productive units. Despite the significant research literature on innovation in Russia, the literature on market selection, especially at the sectoral level, is relatively scarce. This is the research gap that this study aims to address. Research objective. The article assesses how labor resource reallocation between sectors has influenced the dynamics of aggregate labor productivity in the Russian economy over the past two decades. Data and methods. For this purpose, the growth of aggregate labor productivity was decomposed into the growth of productivity within the sectors themselves and the reallocation of labor resources between them. This allowed us to conduct a quantitative estimation of the role of market selection at the sectoral level. For our study, we used data from Rosstat (from 2002 to 2018) and the World Input-Output Database (from 2000 to 2014). Results. For Rosstat data, the ratio of the effect of changes in labor productivity and labor resource reallocation by sector on total labor productivity over the period was 0.71/0.29, and for WIOD data it was 0.44/0.56. This indicates that labor resources are more likely to be reallocated to related sectors (e.g. between manufacturing industries). Conclusions. The results suggest that there is competitive market selection at the sectoral level and that labor has generally been reallocated to more productive sectors of the economy, contributing significantly to the growth of aggregate productivity in the economy. Our study shows the sectors of the economy where this reallocation has taken place, which may help to determine where this process is successful and where it needs additional stimulation.","PeriodicalId":33206,"journal":{"name":"REconomy","volume":"46 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67262742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.15826/recon.2022.8.1.002
A. Kireyeva, N. Nurlanova, A. Kredina
Relevance. In Kazakhstan, regional disparities present a major challenge to national development. The COVID-19 pandemic and the recent political turmoil exacerbated this situation because smaller towns and settlements in less accessible regions lack the resources to cope with the consequences of the crisis on their own. Research objective. The study aims to propose a methodological approach to assessing the socio-economic performance of vulnerable and depressed territories. Data and methods. The methodological approach is developed taking into account the specifics and peculiarities of territorial development, as well as the availability of statistical information in small towns and settlements. The depressiveness and vulnerability ranking were compiled for monotowns and small towns in Kazakhstan. The study relies on the statistical data provided by the Agency for Strategic Planning and Reforms of the Republic of Kazakhstan. Results. The proposed methodology was applied to analyze the aggregate indicators characterizing the socio-economic performance of towns and settlements in East Kazakhstan, North Kazakhstan, and Zhambyl regions between 2009 and 2019. The towns of Ridder, Semey, Mamlyutka, Sergeevka, Karatau, and Janatas were classified as severely depressed areas. The same towns and the town of Bulaev demonstrated the highest levels of vulnerability. Conclusions. The research findings may be of interest to government agencies of all levels. The methodology can be used for assessing the socio-economic performance of lagging areas for more informed decision- and policy-making.
{"title":"Assessment of the socio-economic performance of vulnerable and depressed territories in Kazakhstan","authors":"A. Kireyeva, N. Nurlanova, A. Kredina","doi":"10.15826/recon.2022.8.1.002","DOIUrl":"https://doi.org/10.15826/recon.2022.8.1.002","url":null,"abstract":"Relevance. In Kazakhstan, regional disparities present a major challenge to national development. The COVID-19 pandemic and the recent political turmoil exacerbated this situation because smaller towns and settlements in less accessible regions lack the resources to cope with the consequences of the crisis on their own. Research objective. The study aims to propose a methodological approach to assessing the socio-economic performance of vulnerable and depressed territories. Data and methods. The methodological approach is developed taking into account the specifics and peculiarities of territorial development, as well as the availability of statistical information in small towns and settlements. The depressiveness and vulnerability ranking were compiled for monotowns and small towns in Kazakhstan. The study relies on the statistical data provided by the Agency for Strategic Planning and Reforms of the Republic of Kazakhstan. Results. The proposed methodology was applied to analyze the aggregate indicators characterizing the socio-economic performance of towns and settlements in East Kazakhstan, North Kazakhstan, and Zhambyl regions between 2009 and 2019. The towns of Ridder, Semey, Mamlyutka, Sergeevka, Karatau, and Janatas were classified as severely depressed areas. The same towns and the town of Bulaev demonstrated the highest levels of vulnerability. Conclusions. The research findings may be of interest to government agencies of all levels. The methodology can be used for assessing the socio-economic performance of lagging areas for more informed decision- and policy-making.","PeriodicalId":33206,"journal":{"name":"REconomy","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67262841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.15826/recon.2022.8.3.017
I. Lazanyuk, David Mambu Diu
Relevance. Africa is the continent most targeted by sanctions. African states were made subject to sanctions by the United Nations and various regional organizations such as the African Union, Economic Community of West African States, and the European Union. There is, however, still a lack of understanding of these sanctions’ intended and unintended effects in the African context, which is the research gap this study seeks to address. Research objective. This paper analyzes the role and mechanisms of the sanctions imposed by Western countries (especially the USA) against Angola and other African states to achieve certain geopolitical goals. Data and methods. This study relies on the comprehensive and recently updated dataset of the Global Sanctions Data Base (GSDB). The GSDB lists over 1,101 sanction cases by country and international organization. Sanctions are classified according to the three parameters: their type, objective and degree of success. The methodological framework of this study comprises the historical-logical, statistical, comparative, and analytical methods. Results. We analyzed the dynamic of the macro-economic indicators targeted by the sanctions against Angola and its political elite in 1995-2021 and found that the effects of these sanctions were not very profound. The UN sanctions, however, had a statistically and economically significant effect on the country's economic growth as they led to a considerable exports shrinkage and decline in GDP. The latter effect was possible because Angola's economy is heavily reliant on oil exports. As the imports curbed, since 1995 Angola’s trade structure has undergone some significant changes: the share of the imports from China grew by 12% between 1995 and 2019 while the share of France decreased by 8.2%, Portugal, by 9.6%, and the USA, by 10.8% Conclusions. Analysis of the GSDB data has led us to the following conclusions: first, sanctions are becoming an increasingly popular tool of international relations; second, European countries are the most frequent users of sanctions and African countries are their most frequent targets; third, sanctions are becoming increasingly diverse; and, finally, the share of trade sanctions is decreasing while the share of financial and travel sanctions is growing. At the current stage, the effect of the sanctions is weak in comparison with the declared goals although they have a negative impact on the living standards in the target countries.
{"title":"Angola’s economy under sanctions: problems and solutions","authors":"I. Lazanyuk, David Mambu Diu","doi":"10.15826/recon.2022.8.3.017","DOIUrl":"https://doi.org/10.15826/recon.2022.8.3.017","url":null,"abstract":"Relevance. Africa is the continent most targeted by sanctions. African states were made subject to sanctions by the United Nations and various regional organizations such as the African Union, Economic Community of West African States, and the European Union. There is, however, still a lack of understanding of these sanctions’ intended and unintended effects in the African context, which is the research gap this study seeks to address. Research objective. This paper analyzes the role and mechanisms of the sanctions imposed by Western countries (especially the USA) against Angola and other African states to achieve certain geopolitical goals. Data and methods. This study relies on the comprehensive and recently updated dataset of the Global Sanctions Data Base (GSDB). The GSDB lists over 1,101 sanction cases by country and international organization. Sanctions are classified according to the three parameters: their type, objective and degree of success. The methodological framework of this study comprises the historical-logical, statistical, comparative, and analytical methods. Results. We analyzed the dynamic of the macro-economic indicators targeted by the sanctions against Angola and its political elite in 1995-2021 and found that the effects of these sanctions were not very profound. The UN sanctions, however, had a statistically and economically significant effect on the country's economic growth as they led to a considerable exports shrinkage and decline in GDP. The latter effect was possible because Angola's economy is heavily reliant on oil exports. As the imports curbed, since 1995 Angola’s trade structure has undergone some significant changes: the share of the imports from China grew by 12% between 1995 and 2019 while the share of France decreased by 8.2%, Portugal, by 9.6%, and the USA, by 10.8% Conclusions. Analysis of the GSDB data has led us to the following conclusions: first, sanctions are becoming an increasingly popular tool of international relations; second, European countries are the most frequent users of sanctions and African countries are their most frequent targets; third, sanctions are becoming increasingly diverse; and, finally, the share of trade sanctions is decreasing while the share of financial and travel sanctions is growing. At the current stage, the effect of the sanctions is weak in comparison with the declared goals although they have a negative impact on the living standards in the target countries.","PeriodicalId":33206,"journal":{"name":"REconomy","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67263421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.15826/recon.2022.8.2.012
D. Sandler, D. Gladyrev, Dmitry Kochetkov, A. Zorina
Relevance. One of the main goals of state university support programs in Russia is to increase the number of scientific publications. In 2021, Project 5-100 was replaced by the program PRIORITY 2030 (Strategic Academic Leadership Program). The new program increased the significance of the factors affecting the number of publications in universities and the issue of the optimal allocation of funding among research groups. Research objective. This study examines the factors that affect the productivity of research groups at the university. Unlike the majority of other studies on this topic, this study analyzes scientific productivity at the level of research groups. Data and methods. The study was possible due to the availability of data for 79 research groups at the Ural Federal University for the period from 2014 to 2020. The total number of articles and the number of articles in journals with an impact factor of more than two were used as indicators of research groups’ performance. To determine the factors influencing these indicators, we used econometric models for panel data. We used two separate samples: for social sciences and humanities and for other sciences. Results. We identified the following factors affecting the performance of research groups: the number of participants, the age of the research group, the supervisor’s scientific age, and the amount of funding (the possibility of obtaining more funds or being denied funds). The most interesting result is the following: the supervisor's scientific age and increased funding have a negative impact on the group’s performance. The article provides possible explanations for these results. Conclusion. Since the purpose of creating and funding research groups is primarily to increase their productivity, the results may be in favor of younger supervisors. University managers may also be interested in the ambiguous impact of increased funding: we suppose that research groups are more motivated not by the actual funding but by the prospective amount they may get.
{"title":"Factors of research groups’ productivity: The case of the Ural Federal University","authors":"D. Sandler, D. Gladyrev, Dmitry Kochetkov, A. Zorina","doi":"10.15826/recon.2022.8.2.012","DOIUrl":"https://doi.org/10.15826/recon.2022.8.2.012","url":null,"abstract":"Relevance. One of the main goals of state university support programs in Russia is to increase the number of scientific publications. In 2021, Project 5-100 was replaced by the program PRIORITY 2030 (Strategic Academic Leadership Program). The new program increased the significance of the factors affecting the number of publications in universities and the issue of the optimal allocation of funding among research groups. Research objective. This study examines the factors that affect the productivity of research groups at the university. Unlike the majority of other studies on this topic, this study analyzes scientific productivity at the level of research groups. Data and methods. The study was possible due to the availability of data for 79 research groups at the Ural Federal University for the period from 2014 to 2020. The total number of articles and the number of articles in journals with an impact factor of more than two were used as indicators of research groups’ performance. To determine the factors influencing these indicators, we used econometric models for panel data. We used two separate samples: for social sciences and humanities and for other sciences. Results. We identified the following factors affecting the performance of research groups: the number of participants, the age of the research group, the supervisor’s scientific age, and the amount of funding (the possibility of obtaining more funds or being denied funds). The most interesting result is the following: the supervisor's scientific age and increased funding have a negative impact on the group’s performance. The article provides possible explanations for these results. Conclusion. Since the purpose of creating and funding research groups is primarily to increase their productivity, the results may be in favor of younger supervisors. University managers may also be interested in the ambiguous impact of increased funding: we suppose that research groups are more motivated not by the actual funding but by the prospective amount they may get.","PeriodicalId":33206,"journal":{"name":"REconomy","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67262955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.15826/recon.2022.8.1.007
I. Chernenko, N. Kelchevskaya, I. Pelymskaya
Objective. The purpose of this article is to identify the regional determinants of the low carbon transition in Russian companies. These determinants are related to human capital and digital technologies development in local economic ecosystems. Methods. The study relies on linear regression methods and examines the impact of education, wages, the use of the broadband Internet, cloud technologies and ERP (Enterprise Resource Planning) systems in Russian regions on companies’ motivation to manage their carbon dioxide emissions. Results. The results show that human capital has an ambiguous effect on the behavior of companies that support the low carbon transition. On the contrary, the digitalization of regions is significantly and positively associated with the implementation of environmental and energy management practices in Russian companies, especially among service companies. Conclusion. Low carbon transition is becoming an essential component of the national development strategy, as climate resilience issues directly affect the economic performance of production systems. The study considers two types of factors that influence the implementation of management practices for the low-carbon transition: these are human capital and the digitalization of regions.
{"title":"Regional determinants of low carbon transition in Russian companies: the impact of human capital and digitalization on corporate carbon management practices","authors":"I. Chernenko, N. Kelchevskaya, I. Pelymskaya","doi":"10.15826/recon.2022.8.1.007","DOIUrl":"https://doi.org/10.15826/recon.2022.8.1.007","url":null,"abstract":"Objective. The purpose of this article is to identify the regional determinants of the low carbon transition in Russian companies. These determinants are related to human capital and digital technologies development in local economic ecosystems. Methods. The study relies on linear regression methods and examines the impact of education, wages, the use of the broadband Internet, cloud technologies and ERP (Enterprise Resource Planning) systems in Russian regions on companies’ motivation to manage their carbon dioxide emissions. Results. The results show that human capital has an ambiguous effect on the behavior of companies that support the low carbon transition. On the contrary, the digitalization of regions is significantly and positively associated with the implementation of environmental and energy management practices in Russian companies, especially among service companies. Conclusion. Low carbon transition is becoming an essential component of the national development strategy, as climate resilience issues directly affect the economic performance of production systems. The study considers two types of factors that influence the implementation of management practices for the low-carbon transition: these are human capital and the digitalization of regions.","PeriodicalId":33206,"journal":{"name":"REconomy","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67262975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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