Pub Date : 2022-01-01DOI: 10.17059/ekon.reg.2022-3-6
V. Loginov
Numerous studies have been examining the influence of coronavirus on economic and demographic indicators of various countries and regions in the period from 2020 to 2021. However, little attention is paid to the consequences of the Covid-19 pandemic for Northern and Arctic regions. The present study aims to identify the characteristics of population reproduction in the northern oil and gas regions and consider factors affecting the morbidity and mortality from Covid-19 in the post-Soviet and coronavirus periods. In particular, Khanty-Mansi Autonomous Okrug — Yugra (KhMAO) and Yamalo-Nenets Autonomous Okrug (YaNAO), the Northern and Arctic regions of the Ural Federal District, were examined. The impact of the pandemic on population reproduction in the Ural North was assessed taking into account the regional demographic potential. To this end, the methods of retrospective and statistical analysis, aggregation, grouping, averaging and analogy approaches were utilised. The conducted retrospective analysis revealed the dependence of demographic processes on the time of settlement and development of the territory. In most regions and subregions of the Russian North and Arctic, with the exception of KhMAO and YaNAO, a gradual decrease in the population was observed. In 2020, mortality among patients with Covid-19 in the Ural North was lower than the national average, while the proportion of infected people to total population, on the contrary, was higher. This can be explained by the lower proportion of elderly in Yugra and YaNAO compared to other Russian regions. The research demonstrated that the mortality and birth rates in the most reproductive groups (people aged 20-29 and 30-39) were not affected by the Covid-19 pandemic. The main risk group is the older population aged 60-65 and over, determining the rate and number of deaths from coronavirus. The statistical analysis confirmed the existence of an eight-month cycle of Covid-19 waves from the lowest point to the peak. Future studies will focus on assessing the consequences of the pandemic for the population of the Arctic region at the municipal level.
{"title":"Characteristics of Population Reproduction in the Ural North","authors":"V. Loginov","doi":"10.17059/ekon.reg.2022-3-6","DOIUrl":"https://doi.org/10.17059/ekon.reg.2022-3-6","url":null,"abstract":"Numerous studies have been examining the influence of coronavirus on economic and demographic indicators of various countries and regions in the period from 2020 to 2021. However, little attention is paid to the consequences of the Covid-19 pandemic for Northern and Arctic regions. The present study aims to identify the characteristics of population reproduction in the northern oil and gas regions and consider factors affecting the morbidity and mortality from Covid-19 in the post-Soviet and coronavirus periods. In particular, Khanty-Mansi Autonomous Okrug — Yugra (KhMAO) and Yamalo-Nenets Autonomous Okrug (YaNAO), the Northern and Arctic regions of the Ural Federal District, were examined. The impact of the pandemic on population reproduction in the Ural North was assessed taking into account the regional demographic potential. To this end, the methods of retrospective and statistical analysis, aggregation, grouping, averaging and analogy approaches were utilised. The conducted retrospective analysis revealed the dependence of demographic processes on the time of settlement and development of the territory. In most regions and subregions of the Russian North and Arctic, with the exception of KhMAO and YaNAO, a gradual decrease in the population was observed. In 2020, mortality among patients with Covid-19 in the Ural North was lower than the national average, while the proportion of infected people to total population, on the contrary, was higher. This can be explained by the lower proportion of elderly in Yugra and YaNAO compared to other Russian regions. The research demonstrated that the mortality and birth rates in the most reproductive groups (people aged 20-29 and 30-39) were not affected by the Covid-19 pandemic. The main risk group is the older population aged 60-65 and over, determining the rate and number of deaths from coronavirus. The statistical analysis confirmed the existence of an eight-month cycle of Covid-19 waves from the lowest point to the peak. Future studies will focus on assessing the consequences of the pandemic for the population of the Arctic region at the municipal level.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91397891","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: 10.17059/ekon.reg.2022-2-8
B. Kheyfets, V. Chernova
Consumer globalisation is a fundamentally new stage in modern economic development. The Internet and digital technologies are becoming key drivers of consumer globalisation. To assess these processes, a quantitative evaluation method was developed that distinguishes consumer globalisation twofold — actual and potential. The example of the EU countries was analysed for consumer globalisation. The results obtained allow concluding that consumers in countries with high per capita income and higher prevalence and availability of Internet technologies are more globalised. The highest growth rates of globalisation were noted in countries with basically low globalisation indicators — among consumers in Cyprus, Bulgaria, Greece, Slovenia and Romania. There are differences between the EU countries in the intensity of globalisation processes due to different levels of economic development, different provision of infrastructure and information and communication technologies. The assessment of consumer globalisation showed that consumers of all EU countries in 2018 became more globalised in comparison with 2014. The results obtained make it possible to speak with confidence about the beginning of a new stage of economic globalisation, which will be determined by new technologies and consumer networks. The research findings contribute to the better understanding of the ongoing globalisation processes. The consumer globalisation index can serve as a tool for studying the involvement of consumers in international relations, exploring the potential for these relations’ development, as well as the differences in consumer globalisation between different countries, particular regions within the same country and between various social groups of population.
{"title":"Consumer Involvement in the Globalisation of Trade: Case of the European Union","authors":"B. Kheyfets, V. Chernova","doi":"10.17059/ekon.reg.2022-2-8","DOIUrl":"https://doi.org/10.17059/ekon.reg.2022-2-8","url":null,"abstract":"Consumer globalisation is a fundamentally new stage in modern economic development. The Internet and digital technologies are becoming key drivers of consumer globalisation. To assess these processes, a quantitative evaluation method was developed that distinguishes consumer globalisation twofold — actual and potential. The example of the EU countries was analysed for consumer globalisation. The results obtained allow concluding that consumers in countries with high per capita income and higher prevalence and availability of Internet technologies are more globalised. The highest growth rates of globalisation were noted in countries with basically low globalisation indicators — among consumers in Cyprus, Bulgaria, Greece, Slovenia and Romania. There are differences between the EU countries in the intensity of globalisation processes due to different levels of economic development, different provision of infrastructure and information and communication technologies. The assessment of consumer globalisation showed that consumers of all EU countries in 2018 became more globalised in comparison with 2014. The results obtained make it possible to speak with confidence about the beginning of a new stage of economic globalisation, which will be determined by new technologies and consumer networks. The research findings contribute to the better understanding of the ongoing globalisation processes. The consumer globalisation index can serve as a tool for studying the involvement of consumers in international relations, exploring the potential for these relations’ development, as well as the differences in consumer globalisation between different countries, particular regions within the same country and between various social groups of population.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83699977","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: 10.17059/ekon.reg.2022-4-19
N. Starodubets, V. Derbeneva
Currently, Russia is going through a global transformation in the field of waste management, which is mainly caused by the exhaustion of the capacities of existing landfills. The country’s goal is to reduce landfill and ensure 36 % recycling of all municipal solid waste (MSW) by 2024. Meanwhile, the discussion about the choice of disposal methods continues. We propose to look at the choice of the optimal MSW management strategy at the regional level through the prism of its total greenhouse gas (GHG) emissions. In this regard, the purpose of the article is to determine the total carbon footprint of the regional MSW management system in order to consider the “contribution” of each of the methods of waste management and make the considered criterion suitable for assessing the sustainability of the whole regional waste management system under various scenarios of its development. To achieve this goal, the methodology of the Intergovernmental Panel on Climate Change was used to assess the current situation in the field of MSW management in the Sverdlovsk region. Further, the study developed the conditions for three industry development scenarios (basic, inertial, innovative); substantiated the factors of direct and prevented GHG emissions; calculated GHG emissions from the MSW management sector in the Sverdlovsk region for 2023-2030 for each of the three scenarios. The calculations showed that, by 2030, the basic scenario (“as is”, business-as-usual) has the maximum carbon footprint of 1558.5 thousand tonnes of CO2-eq. The innovative scenario has minimum net emissions of 82.6 thousand tonnes of CO2-eq. by creating a full-fledged separate waste collection and recycling more waste. The findings can be useful in the formation of regional strategies for waste management, considering GHG emissions.
{"title":"Formation of a Regional Strategy for Municipal Solid Waste Management Considering Greenhouse Gas Emissions","authors":"N. Starodubets, V. Derbeneva","doi":"10.17059/ekon.reg.2022-4-19","DOIUrl":"https://doi.org/10.17059/ekon.reg.2022-4-19","url":null,"abstract":"Currently, Russia is going through a global transformation in the field of waste management, which is mainly caused by the exhaustion of the capacities of existing landfills. The country’s goal is to reduce landfill and ensure 36 % recycling of all municipal solid waste (MSW) by 2024. Meanwhile, the discussion about the choice of disposal methods continues. We propose to look at the choice of the optimal MSW management strategy at the regional level through the prism of its total greenhouse gas (GHG) emissions. In this regard, the purpose of the article is to determine the total carbon footprint of the regional MSW management system in order to consider the “contribution” of each of the methods of waste management and make the considered criterion suitable for assessing the sustainability of the whole regional waste management system under various scenarios of its development. To achieve this goal, the methodology of the Intergovernmental Panel on Climate Change was used to assess the current situation in the field of MSW management in the Sverdlovsk region. Further, the study developed the conditions for three industry development scenarios (basic, inertial, innovative); substantiated the factors of direct and prevented GHG emissions; calculated GHG emissions from the MSW management sector in the Sverdlovsk region for 2023-2030 for each of the three scenarios. The calculations showed that, by 2030, the basic scenario (“as is”, business-as-usual) has the maximum carbon footprint of 1558.5 thousand tonnes of CO2-eq. The innovative scenario has minimum net emissions of 82.6 thousand tonnes of CO2-eq. by creating a full-fledged separate waste collection and recycling more waste. The findings can be useful in the formation of regional strategies for waste management, considering GHG emissions.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85162596","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: 10.17059/ekon.reg.2022-3-15
I. Manaeva
Global climate change is an important factor determining the dynamics and significant parameters of the development of the world economy in general and Russian economy in particular. Thus, specific methodological approaches and models should be developed to assess the climate — economy relationship in order to make science-based management decisions. The research aims to create and test a methodology for analysing the relationship between climate and urban economic development in Russian cities. Data of the Federal State Statistics Service was examined; the average annual temperature was calculated according to the information presented on the Weather and Climate portal. The study considers Russian cities with a population of over 100 thousand people in the period from 2009 to 2019. A communication coordination coefficient (CCC), determining the existence and extent of the relationship between climate and economy in Russian cities, can be obtained using the calculations presented in the author’s methodology. Moscow and Saint Petersburg are characterised by stably high values of CCC. The coefficient values range from uncoordinated to base level. The best communication coordination is observed in economically developed cities. Generally, the climate — economy relationship in Russian cities is characterised by a high differentiation and spatial heterogeneity of the communication coordination coefficient, since the Gini coefficient for this indicator varies from 0.56 (Ural Federal District in 2019) to 0.88 (Central Federal District in 2017, 2019). The lack of significant changes in the dynamics of communication coordination in the period 2009-2019 indicates the stability of Russian urban systems. The obtained quantitative estimates may become a prerequisite for the creation of an environmental and economic development management section in urban strategies and part of the environmental policy of Russian regions.
{"title":"Analysis of the Climate — Economy Relationship in Russian Cities","authors":"I. Manaeva","doi":"10.17059/ekon.reg.2022-3-15","DOIUrl":"https://doi.org/10.17059/ekon.reg.2022-3-15","url":null,"abstract":"Global climate change is an important factor determining the dynamics and significant parameters of the development of the world economy in general and Russian economy in particular. Thus, specific methodological approaches and models should be developed to assess the climate — economy relationship in order to make science-based management decisions. The research aims to create and test a methodology for analysing the relationship between climate and urban economic development in Russian cities. Data of the Federal State Statistics Service was examined; the average annual temperature was calculated according to the information presented on the Weather and Climate portal. The study considers Russian cities with a population of over 100 thousand people in the period from 2009 to 2019. A communication coordination coefficient (CCC), determining the existence and extent of the relationship between climate and economy in Russian cities, can be obtained using the calculations presented in the author’s methodology. Moscow and Saint Petersburg are characterised by stably high values of CCC. The coefficient values range from uncoordinated to base level. The best communication coordination is observed in economically developed cities. Generally, the climate — economy relationship in Russian cities is characterised by a high differentiation and spatial heterogeneity of the communication coordination coefficient, since the Gini coefficient for this indicator varies from 0.56 (Ural Federal District in 2019) to 0.88 (Central Federal District in 2017, 2019). The lack of significant changes in the dynamics of communication coordination in the period 2009-2019 indicates the stability of Russian urban systems. The obtained quantitative estimates may become a prerequisite for the creation of an environmental and economic development management section in urban strategies and part of the environmental policy of Russian regions.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79723989","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: 10.17059/ekon.reg.2022-2-6
K. Sohag, S. Husain, K. Chukavina, Md. Al Mamun
The Russian economy is emerging, meaning that natural resources play a dominant role in economic development. Given the considerable volatility in resource prices, we investigate the volatility spillovers among policy uncertainty, international oil prices, exchange rate, stock index and metal prices covering the period of 2 July 2008 to 15 May 2020 for the Russian economy applying Dynamic Connectedness based on Time-Varying Parameter Vector Autoregression (TVP-VAR). Our empirical investigation demonstrates that gold price, Russian policy uncertainty, oil price and stock index are net volatility contributors, whereas palladium, platinum, silver and exchange rate are net volatilities receivers. Market capitalisation and silver market are found to be the highest net contributor and net receiver, respectively. The palladium appears as a net volatility receiver initially, just after the global financial crisis. The Russian economic policy uncertainty appears to be the dominant volatility contributor from 2008 to 2014, but onward it turned to be a net volatility receiver. Over the year 2014, gold price was the prominent volatility contributor to another market when the oil price dropped significantly. The total connectivity of the markets are highly anchored with several exogenous shocks, including economic sanction, adoption of floating exchange rate, oil price plunge. Our empirical findings provide several policy implications to portfolio managers and Russian regional stakeholders.
{"title":"Policy Uncertainty, Oil Price, Stock Market and Precious Metal Markets Volatility Spillovers in the Russian Economy","authors":"K. Sohag, S. Husain, K. Chukavina, Md. Al Mamun","doi":"10.17059/ekon.reg.2022-2-6","DOIUrl":"https://doi.org/10.17059/ekon.reg.2022-2-6","url":null,"abstract":"The Russian economy is emerging, meaning that natural resources play a dominant role in economic development. Given the considerable volatility in resource prices, we investigate the volatility spillovers among policy uncertainty, international oil prices, exchange rate, stock index and metal prices covering the period of 2 July 2008 to 15 May 2020 for the Russian economy applying Dynamic Connectedness based on Time-Varying Parameter Vector Autoregression (TVP-VAR). Our empirical investigation demonstrates that gold price, Russian policy uncertainty, oil price and stock index are net volatility contributors, whereas palladium, platinum, silver and exchange rate are net volatilities receivers. Market capitalisation and silver market are found to be the highest net contributor and net receiver, respectively. The palladium appears as a net volatility receiver initially, just after the global financial crisis. The Russian economic policy uncertainty appears to be the dominant volatility contributor from 2008 to 2014, but onward it turned to be a net volatility receiver. Over the year 2014, gold price was the prominent volatility contributor to another market when the oil price dropped significantly. The total connectivity of the markets are highly anchored with several exogenous shocks, including economic sanction, adoption of floating exchange rate, oil price plunge. Our empirical findings provide several policy implications to portfolio managers and Russian regional stakeholders.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77224084","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: 10.17059/ekon.reg.2022-3-11
O. Zhdaneev
Considering the current geopolitical situation, the issues of technological sovereignty and fuel and energy sector development became urgent. In order to determine priorities for the implementation of public-private partnership (since these problems cannot be solved only through budgetary funding), areas largely depending on the import of equipment, technologies and software should be identified. The article presents a new methodology for assessing product localisation in the fuel and energy sector. The study reviews the existing approach (based on the Government Decree No. 719) and current challenges of implementing the local content policy in the Russian fuel and energy sector. The proposed methodology is based on the relevant experience of various countries in calculating the local content value, as well as the best practices of some Russian companies. Particular attention is paid to the complete value chain for products, services and software. The basic formula for calculating the product localisation includes estimations for each cost item in the value chain. Cost data taken from the appendix to the balance sheet, invoices and annual reports of enterprises were used as input. The total costs and import costs were considered for each cost item. According to the results of a comparative analysis of existing Russian and international methodologies, the developed approach was evaluated by the industry community and was considered to be the most relevant. The main risks of deploying the methodology in the import substitution programme, as well as risk management measures were described. The fuel and energy sector companies could use the research findings to assess the actual dependence on imported equipment and technologies.
{"title":"Assessment of Product Localization during the Import Substitution in the Fuel and Energy Sector","authors":"O. Zhdaneev","doi":"10.17059/ekon.reg.2022-3-11","DOIUrl":"https://doi.org/10.17059/ekon.reg.2022-3-11","url":null,"abstract":"Considering the current geopolitical situation, the issues of technological sovereignty and fuel and energy sector development became urgent. In order to determine priorities for the implementation of public-private partnership (since these problems cannot be solved only through budgetary funding), areas largely depending on the import of equipment, technologies and software should be identified. The article presents a new methodology for assessing product localisation in the fuel and energy sector. The study reviews the existing approach (based on the Government Decree No. 719) and current challenges of implementing the local content policy in the Russian fuel and energy sector. The proposed methodology is based on the relevant experience of various countries in calculating the local content value, as well as the best practices of some Russian companies. Particular attention is paid to the complete value chain for products, services and software. The basic formula for calculating the product localisation includes estimations for each cost item in the value chain. Cost data taken from the appendix to the balance sheet, invoices and annual reports of enterprises were used as input. The total costs and import costs were considered for each cost item. According to the results of a comparative analysis of existing Russian and international methodologies, the developed approach was evaluated by the industry community and was considered to be the most relevant. The main risks of deploying the methodology in the import substitution programme, as well as risk management measures were described. The fuel and energy sector companies could use the research findings to assess the actual dependence on imported equipment and technologies.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74048575","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: 10.17059/ekon.reg.2022-3-5
L. Leonova, V. Lakshina, A. Aladyshkina
Health is a comprehensive phenomenon with many determinants. The influence of environmental conditions on human health poses challenges for public health scientists. One of the main issues is the availability and relevance of the data on public health, including such indicators as morbidity and decease prevalence. In this study, we overcome this obstacle by using micro data on self-reported health from the Russia Longitudinal Monitoring Survey of Higher School of Economics. The study analyses the influence of environmental conditions on individual self-rated health in Russia, taking into account the heterogeneity of coefficients among self-rated health levels. We used generalised ordered probit model with random effects and embedded procedure for parallel line assumption violation testing. The characteristics of air, water and the quantity of pollutants in each region were considered as independent factors. The study showed significant negative influence of environmental factors on self-rated health throughout Russia. It is also demonstrated that higher self-rated health estimates are given by respondents whose level of education is no lower than that of vocational or trade school, who are married, and who are regularly engaged in physical activity. The results obtained can be used to improve regional state programmes aimed at improving the quality of life of the population in groups with different levels of health, for example, to the development and targeting of a set of health policy measures. Additionally, these findings can be utilised in programmes to improve the quality of the environment, which can increase the overall level of self-assessment of health in a particular region.
{"title":"Heterogeneous Effects of Individual Socio-Economic Characteristics and Regional Environmental Conditions on Self-Reported Health","authors":"L. Leonova, V. Lakshina, A. Aladyshkina","doi":"10.17059/ekon.reg.2022-3-5","DOIUrl":"https://doi.org/10.17059/ekon.reg.2022-3-5","url":null,"abstract":"Health is a comprehensive phenomenon with many determinants. The influence of environmental conditions on human health poses challenges for public health scientists. One of the main issues is the availability and relevance of the data on public health, including such indicators as morbidity and decease prevalence. In this study, we overcome this obstacle by using micro data on self-reported health from the Russia Longitudinal Monitoring Survey of Higher School of Economics. The study analyses the influence of environmental conditions on individual self-rated health in Russia, taking into account the heterogeneity of coefficients among self-rated health levels. We used generalised ordered probit model with random effects and embedded procedure for parallel line assumption violation testing. The characteristics of air, water and the quantity of pollutants in each region were considered as independent factors. The study showed significant negative influence of environmental factors on self-rated health throughout Russia. It is also demonstrated that higher self-rated health estimates are given by respondents whose level of education is no lower than that of vocational or trade school, who are married, and who are regularly engaged in physical activity. The results obtained can be used to improve regional state programmes aimed at improving the quality of life of the population in groups with different levels of health, for example, to the development and targeting of a set of health policy measures. Additionally, these findings can be utilised in programmes to improve the quality of the environment, which can increase the overall level of self-assessment of health in a particular region.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88148496","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: 10.17059/ekon.reg.2022-4-24
D. Al-Najjar, H. Al-Najjar, N. Al-Rousan
Stock markets are an essential backbone for the economy worldwide; their indices provide all interested parties with indicators regarding the performance of firms listed in the financial market due to tracking the daily transactions. This study aims to investigate factors that affect the stock exchange directly so that it simplifies building a prediction model for the exchange index in Jordan’s financial market. The study hypothesis assumes that some sub-sectors are most influential in creating the stock market prediction model. Therefore, this study applies four feature selection methods on 23 sub-sectors and Amman Stock Exchange Index (ASEI100) for the period 2008–2018. The top 10 attributes from each selection method are combined, and the frequency table is used to find the highly trusted attributes. Moreover, linear regression with ordinary least square regression is used to test the validity of the top factors that frequently occurred in the four methods and their effect on ASEI. The results found that there are six main sub-sectors directly affecting the general index in Jordan: Health Care Services, Mining and Extraction Industries, Textiles, Leather and Clothing, Real Estate, Financial Services and Transportation. These sectors can be utilised to predict the movements of the Amman Stock Exchange Index in Jordan. Also, the linear regression model output showed a statistically significant relationship between the six sub-sectors (independent variables) and ASEI (dependent variable). Investors can use this paper’s findings to signal the most important sectors in Jordan. Thus, it helps in taking investment decisions.
{"title":"Long-Term General Index Prediction Based on Feature Selection and Search Methods: Amman Stock Exchange Market","authors":"D. Al-Najjar, H. Al-Najjar, N. Al-Rousan","doi":"10.17059/ekon.reg.2022-4-24","DOIUrl":"https://doi.org/10.17059/ekon.reg.2022-4-24","url":null,"abstract":"Stock markets are an essential backbone for the economy worldwide; their indices provide all interested parties with indicators regarding the performance of firms listed in the financial market due to tracking the daily transactions. This study aims to investigate factors that affect the stock exchange directly so that it simplifies building a prediction model for the exchange index in Jordan’s financial market. The study hypothesis assumes that some sub-sectors are most influential in creating the stock market prediction model. Therefore, this study applies four feature selection methods on 23 sub-sectors and Amman Stock Exchange Index (ASEI100) for the period 2008–2018. The top 10 attributes from each selection method are combined, and the frequency table is used to find the highly trusted attributes. Moreover, linear regression with ordinary least square regression is used to test the validity of the top factors that frequently occurred in the four methods and their effect on ASEI. The results found that there are six main sub-sectors directly affecting the general index in Jordan: Health Care Services, Mining and Extraction Industries, Textiles, Leather and Clothing, Real Estate, Financial Services and Transportation. These sectors can be utilised to predict the movements of the Amman Stock Exchange Index in Jordan. Also, the linear regression model output showed a statistically significant relationship between the six sub-sectors (independent variables) and ASEI (dependent variable). Investors can use this paper’s findings to signal the most important sectors in Jordan. Thus, it helps in taking investment decisions.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84831690","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: 10.17059/ekon.reg.2022-4-9
V. Koksharov, G. Agarkov, A. Melnik
Training of a new generation of graduate students plays a key role in ensuring a country’s sustainable socio-economic development and active enhancement of human capital by continuous reproduction of cutting-edge knowledge in the form of research and development (R&D) for industry. In this context, it becomes important to examine the development dynamics of doctoral studies in Russian regions, as well as the graduate students’ financial well-being affecting their educational mobility and general opportunities to receive education (in particular, necessity of employment). The development of doctoral studies is analysed taking into account the distribution of resources (financial, intellectual) by regions and universities. The study also considers the concentration of resources in Russian universities capable of generating breakthrough ideas and technologies, which can be seen as centres of attraction for proactive youth. The methods of secondary data analysis, comparison, classification, and infographics were applied to process information. Such data as the monitoring of the effectiveness of Russian universities in 2014-2020 and sociological surveys of graduate students of a leading Russian university for 2017-2020 were analysed. As a result, the study presents a map showing the concentration of graduate students in certain regions, which takes into consideration their number, inflow and outflow. In addition to the capital regions (their share is 47.9 %), the Republic of Tatarstan (3.2 %), Tomsk oblast (2.4 %) and Sverdlovsk oblast (2.1 %), where leading Russian universities are located, were revealed to be the centres for attraction of graduate students. The top 7 regions also include Belgorod (the share of graduate students is 2.7 %) and Rostov oblasts (2.4 %) characterised by the presence of strong research and federal universities. However, due to the lack of funding (85 % of graduate students have to combine work and studies), the outflow to foreign universities is increasing even in the regions that attract a large number of scholars. The obtained findings can be used to improve the mechanisms for supporting graduate students in order to contribute to sustainable development of regions.
{"title":"University and Regional Landscape of Doctoral Studies in Russia: Financial Trajectories of Graduate Students","authors":"V. Koksharov, G. Agarkov, A. Melnik","doi":"10.17059/ekon.reg.2022-4-9","DOIUrl":"https://doi.org/10.17059/ekon.reg.2022-4-9","url":null,"abstract":"Training of a new generation of graduate students plays a key role in ensuring a country’s sustainable socio-economic development and active enhancement of human capital by continuous reproduction of cutting-edge knowledge in the form of research and development (R&D) for industry. In this context, it becomes important to examine the development dynamics of doctoral studies in Russian regions, as well as the graduate students’ financial well-being affecting their educational mobility and general opportunities to receive education (in particular, necessity of employment). The development of doctoral studies is analysed taking into account the distribution of resources (financial, intellectual) by regions and universities. The study also considers the concentration of resources in Russian universities capable of generating breakthrough ideas and technologies, which can be seen as centres of attraction for proactive youth. The methods of secondary data analysis, comparison, classification, and infographics were applied to process information. Such data as the monitoring of the effectiveness of Russian universities in 2014-2020 and sociological surveys of graduate students of a leading Russian university for 2017-2020 were analysed. As a result, the study presents a map showing the concentration of graduate students in certain regions, which takes into consideration their number, inflow and outflow. In addition to the capital regions (their share is 47.9 %), the Republic of Tatarstan (3.2 %), Tomsk oblast (2.4 %) and Sverdlovsk oblast (2.1 %), where leading Russian universities are located, were revealed to be the centres for attraction of graduate students. The top 7 regions also include Belgorod (the share of graduate students is 2.7 %) and Rostov oblasts (2.4 %) characterised by the presence of strong research and federal universities. However, due to the lack of funding (85 % of graduate students have to combine work and studies), the outflow to foreign universities is increasing even in the regions that attract a large number of scholars. The obtained findings can be used to improve the mechanisms for supporting graduate students in order to contribute to sustainable development of regions.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86200910","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: 10.17059/ekon.reg.2022-4-23
T. Sarkhanov
Since oil plays an important role in the economy of Azerbaijan, the events in the global oil market deeply affect the national economy. Moreover, the COVID-19 pandemic influenced the economy of Azerbaijan, in which oil and gas have a significant place. In April 2020, the price of one barrel of oil on the world market fell to $1. One reason for this was the decrease in oil demand due to the lockdown regime implemented by many countries due to the rapid outbreak of the COVID-19 pandemic, and another reason was that the OPEC (Organization of the Petroleum Exporting Countries) countries could not agree on reducing oil production. The aim of this research is to show the impacts of oil prices on gross domestic product (GDP) of Azerbaijan, the growth rate of GDP, and the amount of oil production in Azerbaijan in 2009-2018. The hypothesis of the research is that oil prices seriously influence the economy of Azerbaijan and there is a correlation between the growth rate of Azerbaijan’s gross domestic product and the oil prices. The study starts with a brief description of the history of Azerbaijan’s oil industry, followed by oil industry’s importance in the economy of Azerbaijan, the role in foreign economic relations, and the effects on the economy of country. The quantitative method was used as a key research method. The data used in the analysis of this study were collected according to the literature scanning method, which is one of the data collection techniques. Further, descriptive statistics technique, which is a quantitative data analysis technique, was used to analyse the data. The findings show that the changes in oil prices in 2009-2018 directly affect the Azerbaijan’s gross domestic product, the growth rate of GDP, and the amount of oil production in Azerbaijan. Thus, as oil prices increase, the growth rate of the country’s gross domestic product and GDP increase and decrease as oil prices decrease.
{"title":"The Effect of Oil Prices on Azerbaijan’s Economy","authors":"T. Sarkhanov","doi":"10.17059/ekon.reg.2022-4-23","DOIUrl":"https://doi.org/10.17059/ekon.reg.2022-4-23","url":null,"abstract":"Since oil plays an important role in the economy of Azerbaijan, the events in the global oil market deeply affect the national economy. Moreover, the COVID-19 pandemic influenced the economy of Azerbaijan, in which oil and gas have a significant place. In April 2020, the price of one barrel of oil on the world market fell to $1. One reason for this was the decrease in oil demand due to the lockdown regime implemented by many countries due to the rapid outbreak of the COVID-19 pandemic, and another reason was that the OPEC (Organization of the Petroleum Exporting Countries) countries could not agree on reducing oil production. The aim of this research is to show the impacts of oil prices on gross domestic product (GDP) of Azerbaijan, the growth rate of GDP, and the amount of oil production in Azerbaijan in 2009-2018. The hypothesis of the research is that oil prices seriously influence the economy of Azerbaijan and there is a correlation between the growth rate of Azerbaijan’s gross domestic product and the oil prices. The study starts with a brief description of the history of Azerbaijan’s oil industry, followed by oil industry’s importance in the economy of Azerbaijan, the role in foreign economic relations, and the effects on the economy of country. The quantitative method was used as a key research method. The data used in the analysis of this study were collected according to the literature scanning method, which is one of the data collection techniques. Further, descriptive statistics technique, which is a quantitative data analysis technique, was used to analyse the data. The findings show that the changes in oil prices in 2009-2018 directly affect the Azerbaijan’s gross domestic product, the growth rate of GDP, and the amount of oil production in Azerbaijan. Thus, as oil prices increase, the growth rate of the country’s gross domestic product and GDP increase and decrease as oil prices decrease.","PeriodicalId":51978,"journal":{"name":"Ekonomika Regiona-Economy of Region","volume":null,"pages":null},"PeriodicalIF":0.5,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86928720","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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