Pub Date : 2023-01-01DOI: 10.15826/recon.2023.9.1.006
Azamat Valei, S. Mamman
Relevance. Foreign investment is likely to be attracted to resource-rich countries because of their wealth of natural resources. However, the fact that foreign direct investment (FDI) contributes less than 10% of these countries’ GDP indicates that FDI has a non-proportional impact when compared to the size of the natural resources. Hence, it is critical to identify the missing link impeding resource optimization through FDI. Research objective. Given the significance of FDI, the study seeks to ascertain whether the quality of institutions in resource-rich countries influences FDI inflows. This is significant because resource-rich countries may have other factors that encourage FDI but do not result in resource optimization. Data and methods. The study employed panel data analysis to analyze the impact of FDI on economic growth in resource-rich countries and the role of institutions in attracting FDI. The study relies on the Augmented Mean Group Estimator and on the annual data from the World Bank's World Development Indicator and the World Bank's World Governance Indicator for the top ten resource-rich countries. Results. Our preliminary evidence indicated that FDI had a positive and significant effect on economic growth in resource-rich countries. The extent of the influence, on the other hand, is minimal for all categories of countries. Our main results revealed that institutional quality has a significant pull effect on FDI, with trade openness playing a key role, particularly in resource-rich nations with well-developed institutions. Conclusions. We found that institutional quality plays a critical role in attracting FDI, which could have hampered natural resource optimization. Furthermore, countries with high institutional quality and less restrictive investment policies attract more foreign direct investment (FDI) than countries with low institutional quality and with investment policies ranging from moderate to restrictive. In general, resource-rich countries, particularly those with weak institutional qualities, should address the gap in institutional quality to attract more inward investment.
{"title":"FDI Flows in resource-rich countries: does the quality of institutions matter?","authors":"Azamat Valei, S. Mamman","doi":"10.15826/recon.2023.9.1.006","DOIUrl":"https://doi.org/10.15826/recon.2023.9.1.006","url":null,"abstract":"Relevance. Foreign investment is likely to be attracted to resource-rich countries because of their wealth of natural resources. However, the fact that foreign direct investment (FDI) contributes less than 10% of these countries’ GDP indicates that FDI has a non-proportional impact when compared to the size of the natural resources. Hence, it is critical to identify the missing link impeding resource optimization through FDI. Research objective. Given the significance of FDI, the study seeks to ascertain whether the quality of institutions in resource-rich countries influences FDI inflows. This is significant because resource-rich countries may have other factors that encourage FDI but do not result in resource optimization. Data and methods. The study employed panel data analysis to analyze the impact of FDI on economic growth in resource-rich countries and the role of institutions in attracting FDI. The study relies on the Augmented Mean Group Estimator and on the annual data from the World Bank's World Development Indicator and the World Bank's World Governance Indicator for the top ten resource-rich countries. Results. Our preliminary evidence indicated that FDI had a positive and significant effect on economic growth in resource-rich countries. The extent of the influence, on the other hand, is minimal for all categories of countries. Our main results revealed that institutional quality has a significant pull effect on FDI, with trade openness playing a key role, particularly in resource-rich nations with well-developed institutions. Conclusions. We found that institutional quality plays a critical role in attracting FDI, which could have hampered natural resource optimization. Furthermore, countries with high institutional quality and less restrictive investment policies attract more foreign direct investment (FDI) than countries with low institutional quality and with investment policies ranging from moderate to restrictive. In general, resource-rich countries, particularly those with weak institutional qualities, should address the gap in institutional quality to attract more inward investment.","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":"67264092","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.2023.9.2.008
O. Chernova, Li Liu, X. Wang
Relevance. Digital technologies can bring regional logistics outsourcing in the automotive industry to a new level of performance. However, the digitalization of logistics outsourcing and its role in improving the sustainability of the automotive industry are poorly understood. Research objective. To develop the conceptual framework of the digital ecosystem of regional logistics outsourcing in the automotive industry. The object of the study is the automotive industry in China. Data and methods. Prospects for the digitalization of regional logistics outsourcing of the automotive industry and its impact on the sustainability of the industry are considered in terms of the economics of transaction costs and a resource-based approach. The data sources involved the national policy documents reflecting the strategic directions of digital development of China, statistical data provided by the National Bureau of Statistics of China, as well as research papers presented in the Scopus database. Results. The authors analyzed the trends of digital transformations in the geographic clusters of production of the automotive industry in China. The digitalization of regional logistics outsourcing was determined to influence the sustainability of the automotive industry development in the context of its economic, social, environmental and technological components. The logistics ecosystem model developed by Capgemini was supplemented by the conceptual framework of the digital logistics outsourcing ecosystem for the Chinese automotive industry. The key components of this framework were determined. Conclusions. It can be concluded that digitalization of regional logistics outsourcing will contribute to increasing the sustainability of the automotive industry. However, this requires the formation of a digital landscape of logistics outsourcing, which involves changes in the entire supply chain management system. The results of the study can be used to improve the efficiency of supply chain management in the automotive industry.
{"title":"Role of digitalization of logistics outsourcing in sustainable development of automotive industry in China","authors":"O. Chernova, Li Liu, X. Wang","doi":"10.15826/recon.2023.9.2.008","DOIUrl":"https://doi.org/10.15826/recon.2023.9.2.008","url":null,"abstract":"Relevance. Digital technologies can bring regional logistics outsourcing in the automotive industry to a new level of performance. However, the digitalization of logistics outsourcing and its role in improving the sustainability of the automotive industry are poorly understood. Research objective. To develop the conceptual framework of the digital ecosystem of regional logistics outsourcing in the automotive industry. The object of the study is the automotive industry in China. Data and methods. Prospects for the digitalization of regional logistics outsourcing of the automotive industry and its impact on the sustainability of the industry are considered in terms of the economics of transaction costs and a resource-based approach. The data sources involved the national policy documents reflecting the strategic directions of digital development of China, statistical data provided by the National Bureau of Statistics of China, as well as research papers presented in the Scopus database. Results. The authors analyzed the trends of digital transformations in the geographic clusters of production of the automotive industry in China. The digitalization of regional logistics outsourcing was determined to influence the sustainability of the automotive industry development in the context of its economic, social, environmental and technological components. The logistics ecosystem model developed by Capgemini was supplemented by the conceptual framework of the digital logistics outsourcing ecosystem for the Chinese automotive industry. The key components of this framework were determined. Conclusions. It can be concluded that digitalization of regional logistics outsourcing will contribute to increasing the sustainability of the automotive industry. However, this requires the formation of a digital landscape of logistics outsourcing, which involves changes in the entire supply chain management system. The results of the study can be used to improve the efficiency of supply chain management in the automotive industry.","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":"67264316","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.2023.9.2.009
R. Dmitriev, S. Gorokhov, M. M. Agafoshin
Relevance. The development of central place theory has been hindered by its static nature, as it fails to capture transitions between equilibrium states in central place systems. This long-standing problem remains unsolved since the theory's inception 90 years ago. This article presents a solution by examining the cases of system unification and system breakup, where previously independent systems merge or split. Research objective: The study aims to identify the conditions under which central place systems resume continual development following revolutionary transformations in their structure. Data and methods: The research analyzes census data from India (1947-2011) and Yemen (1973-2004) using equations based on the axioms of central place theory. The study also considers isostatic equilibrium as the foundation of central place system structures. Results: The effect of intermittence on the steady evolution of a central place system diminishes rapidly after the unification of two independent systems. In contrast, the adaptation of elements from a previously unified system to new conditions, including reinstating the former hierarchy and spatial structure, takes significantly longer after a system breakup. The study introduces a novel perspective, highlighting that the unification of central place systems tends to lead to progress, whereas the breakup of a unified system results in degradation. Conclusions: The true benefit to a central place system lies not solely in achieving isostatic equilibrium but in maintaining a secure and optimal structure. While these concepts share similarities, they may appear more distinct when examining the central place system as a whole. Equilibrium represents an optimal state for individual hierarchy levels rather than the entire system.
{"title":"Intermittent Development of Central Place Systems: The Dynamics of Unification and Breakup","authors":"R. Dmitriev, S. Gorokhov, M. M. Agafoshin","doi":"10.15826/recon.2023.9.2.009","DOIUrl":"https://doi.org/10.15826/recon.2023.9.2.009","url":null,"abstract":"Relevance. The development of central place theory has been hindered by its static nature, as it fails to capture transitions between equilibrium states in central place systems. This long-standing problem remains unsolved since the theory's inception 90 years ago. This article presents a solution by examining the cases of system unification and system breakup, where previously independent systems merge or split. Research objective: The study aims to identify the conditions under which central place systems resume continual development following revolutionary transformations in their structure. Data and methods: The research analyzes census data from India (1947-2011) and Yemen (1973-2004) using equations based on the axioms of central place theory. The study also considers isostatic equilibrium as the foundation of central place system structures. Results: The effect of intermittence on the steady evolution of a central place system diminishes rapidly after the unification of two independent systems. In contrast, the adaptation of elements from a previously unified system to new conditions, including reinstating the former hierarchy and spatial structure, takes significantly longer after a system breakup. The study introduces a novel perspective, highlighting that the unification of central place systems tends to lead to progress, whereas the breakup of a unified system results in degradation. Conclusions: The true benefit to a central place system lies not solely in achieving isostatic equilibrium but in maintaining a secure and optimal structure. While these concepts share similarities, they may appear more distinct when examining the central place system as a whole. Equilibrium represents an optimal state for individual hierarchy levels rather than the entire system.","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":"67264372","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.2023.9.2.014
I. Naumov, N. Nikulina
Relevance. Extensive research has focused on evaluating and modeling innovative processes in territorial systems. However, an underexplored aspect is the assessment of spatial effects resulting from neighboring territories and the modeling of inter-territorial interactions in enterprise innovation. The existing regression models have limitations in accounting for spatial effects, indicating the presence of unaccounted factors. Research objective. This study aims to develop a methodological approach to evaluate the influence of factors on the dynamics of shipped innovative goods in Russian regions, taking into account spatial effects. Additionally, it aims to test the hypothesis that territories located near innovatively developing regions exhibit faster progress. Data and methods. The study utilizes regression analysis of panel data, employing combined least squares, fixed effects, and random effects methods to evaluate the influence of enterprise costs on innovation, the number of research personnel (researchers and technicians), advanced production technologies developed and used, the number of research organizations, as well as the internal costs of fundamental and applied research and development on the volume of shipped innovative goods in Russian regions from 2000 to 2021. To account for spatial effects, spatial econometrics techniques such as Spatial Autoregressive (SAR) models considering spatial lag and Spatial Autoregressive Conditional Heteroscedasticity (SAC) models considering both spatial lag and spatial error are employed. The Generalized Method of Moments (GMM) with the White period weight matrix is used to address heteroscedasticity, and data transformation techniques including orthogonal deviations and the inclusion of dummy variables for each spatial unit and time period are applied. Results. The study reveals deepening spatial heterogeneity in innovation processes during economic downturns, which smooth out during economic recovery. Regions with high and low concentrations of shipped innovative goods are identified. Regression analysis establishes the impact of various factors on shipped innovative goods. Spatial models utilizing the Cobb-Douglas SAR and SAC frameworks demonstrate positive spatial effects, wherein neighboring regions exert influence on innovative development. Regions with high enterprise innovation activity, including Moscow, St. Petersburg, and others, exhibit the highest spatial effects. Conclusions. The innovative development of a single region depends not only on its own production factors but also on the innovative activity of enterprises in the surrounding regions. These findings highlight the importance of considering spatial effects in assessing and modeling regional innovation dynamics.
{"title":"Exploring the Innovative Development of Russian Regions: A Spatial Regression Analysis Using the Cobb-Douglas Model","authors":"I. Naumov, N. Nikulina","doi":"10.15826/recon.2023.9.2.014","DOIUrl":"https://doi.org/10.15826/recon.2023.9.2.014","url":null,"abstract":"Relevance. Extensive research has focused on evaluating and modeling innovative processes in territorial systems. However, an underexplored aspect is the assessment of spatial effects resulting from neighboring territories and the modeling of inter-territorial interactions in enterprise innovation. The existing regression models have limitations in accounting for spatial effects, indicating the presence of unaccounted factors. Research objective. This study aims to develop a methodological approach to evaluate the influence of factors on the dynamics of shipped innovative goods in Russian regions, taking into account spatial effects. Additionally, it aims to test the hypothesis that territories located near innovatively developing regions exhibit faster progress. Data and methods. The study utilizes regression analysis of panel data, employing combined least squares, fixed effects, and random effects methods to evaluate the influence of enterprise costs on innovation, the number of research personnel (researchers and technicians), advanced production technologies developed and used, the number of research organizations, as well as the internal costs of fundamental and applied research and development on the volume of shipped innovative goods in Russian regions from 2000 to 2021. To account for spatial effects, spatial econometrics techniques such as Spatial Autoregressive (SAR) models considering spatial lag and Spatial Autoregressive Conditional Heteroscedasticity (SAC) models considering both spatial lag and spatial error are employed. The Generalized Method of Moments (GMM) with the White period weight matrix is used to address heteroscedasticity, and data transformation techniques including orthogonal deviations and the inclusion of dummy variables for each spatial unit and time period are applied. Results. The study reveals deepening spatial heterogeneity in innovation processes during economic downturns, which smooth out during economic recovery. Regions with high and low concentrations of shipped innovative goods are identified. Regression analysis establishes the impact of various factors on shipped innovative goods. Spatial models utilizing the Cobb-Douglas SAR and SAC frameworks demonstrate positive spatial effects, wherein neighboring regions exert influence on innovative development. Regions with high enterprise innovation activity, including Moscow, St. Petersburg, and others, exhibit the highest spatial effects. Conclusions. The innovative development of a single region depends not only on its own production factors but also on the innovative activity of enterprises in the surrounding regions. These findings highlight the importance of considering spatial effects in assessing and modeling regional innovation dynamics.","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":"67264196","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.2023.9.2.010
J. Varlamova, N. Larionova, J. Kolesnikova
Relevance. The outflow of funds from the Russian economy, including remittances, can have a significant impact on the country's economic development. The influence of digital technologies and the heterogeneity of Russian regions further complicate the study of factors affecting remittance outflows. This study aims to address this research gap by examining the spatial effects of remittance outflows from Russia at the regional level within the context of digital transformation. Research Objective. The primary objective of this paper is to investigate whether spatial effects exist in the outflow of remittances from Russia at the regional level and how digitalization affects this phenomenon. By exploring spatial autocorrelation and fitting spatial models, we aim to understand the mutual influence and interdependence of regions in cross-border remittances. Data and Methods. The study utilizes open annual data from the Bank of Russia on cross-border remittances and data from the Federal State Statistics Service of the Russian Federation. The research methodology includes spatial autocorrelation estimation and the application of spatial models. Results. Our findings indicate that the digitalization of business transactions leads to a decline in cross-border remittances that do not involve payment systems. This finding primarily relates to the relatively low share of non-resident remittances within formal remittances. The results underscore the importance of considering spatial differentiation among regions in terms of remittance volume when formulating regional policies. Furthermore, the study reveals a shifting trend towards the emergence of major centers for outgoing transfers in the Far Eastern part of Russia and an increase in remittance volumes from border regions in the European part of Russia. Conclusions. The policy implications of this study highlight the need to encourage the participation of the population's savings in the domestic economy. This can be achieved through measures aimed at facilitating internal investment and financial inclusion.
{"title":"Modelling Outflow Remittances in the Digital Era: A Subnational Analysis of Russia","authors":"J. Varlamova, N. Larionova, J. Kolesnikova","doi":"10.15826/recon.2023.9.2.010","DOIUrl":"https://doi.org/10.15826/recon.2023.9.2.010","url":null,"abstract":"Relevance. The outflow of funds from the Russian economy, including remittances, can have a significant impact on the country's economic development. The influence of digital technologies and the heterogeneity of Russian regions further complicate the study of factors affecting remittance outflows. This study aims to address this research gap by examining the spatial effects of remittance outflows from Russia at the regional level within the context of digital transformation. Research Objective. The primary objective of this paper is to investigate whether spatial effects exist in the outflow of remittances from Russia at the regional level and how digitalization affects this phenomenon. By exploring spatial autocorrelation and fitting spatial models, we aim to understand the mutual influence and interdependence of regions in cross-border remittances. Data and Methods. The study utilizes open annual data from the Bank of Russia on cross-border remittances and data from the Federal State Statistics Service of the Russian Federation. The research methodology includes spatial autocorrelation estimation and the application of spatial models. Results. Our findings indicate that the digitalization of business transactions leads to a decline in cross-border remittances that do not involve payment systems. This finding primarily relates to the relatively low share of non-resident remittances within formal remittances. The results underscore the importance of considering spatial differentiation among regions in terms of remittance volume when formulating regional policies. Furthermore, the study reveals a shifting trend towards the emergence of major centers for outgoing transfers in the Far Eastern part of Russia and an increase in remittance volumes from border regions in the European part of Russia. Conclusions. The policy implications of this study highlight the need to encourage the participation of the population's savings in the domestic economy. This can be achieved through measures aimed at facilitating internal investment and financial inclusion.","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":"67263935","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.2023.9.1.007
L. Matveeva, E. Kaplyuk, Ekaterina A. Likhatskaia, Nikita V. Nizov
Relevance. Recent practice has convincingly tested the fact that the transition to a circular economy is an important goal for society and individual companies, especially in resource-intensive manufacturing industries. Research objective. The purpose of the study is to develop a theoretical and methodological basis for the creation of innovative solvates in regional industry, based on the concept of circular economy. Data and methods. The research methodology is represented by the convergence of system-synergetic, resource-efficient and cluster approaches, which makes it possible to identify regions where integrating industrial enterprises and related fields of activity form conditions and produce values in the concept of the circular economy. Results. The theoretical and methodological basis for the creation of new structures for the innovative development of regional industry on the platform of circularity, principles of inclusiveness, resilience and environmental friendliness has been formed; a new concept - innovative solvates has been introduced into scientific circulation. Based on the cluster analysis, the zones of localization of innovative solvates in the regions of Russia were identified. This made it possible to single out a cluster group with a high scientific and innovative potential, as well as a cluster of regions with the potential to localize innovative solvates, which included regions of industrial and resource specialization. Conclusions. The article presents the directions of solving the problem of achieving the conditions imposed by the circular economy in the innovative solvates of the industrial sector of the region. The study is motivated by several considerations. The first is the formation of an integral conceptual and terminological apparatus, theoretical and methodological basis of research. The second is the establishment of partnerships necessary for the implementation of circularity conditions in an innovative solvate, and the analysis of ways in which a solvate can switch to a circular economy.
{"title":"The circular economy model and the role of solvates in regional innovative development (the case of Russian regions)","authors":"L. Matveeva, E. Kaplyuk, Ekaterina A. Likhatskaia, Nikita V. Nizov","doi":"10.15826/recon.2023.9.1.007","DOIUrl":"https://doi.org/10.15826/recon.2023.9.1.007","url":null,"abstract":"Relevance. Recent practice has convincingly tested the fact that the transition to a circular economy is an important goal for society and individual companies, especially in resource-intensive manufacturing industries. Research objective. The purpose of the study is to develop a theoretical and methodological basis for the creation of innovative solvates in regional industry, based on the concept of circular economy. Data and methods. The research methodology is represented by the convergence of system-synergetic, resource-efficient and cluster approaches, which makes it possible to identify regions where integrating industrial enterprises and related fields of activity form conditions and produce values in the concept of the circular economy. Results. The theoretical and methodological basis for the creation of new structures for the innovative development of regional industry on the platform of circularity, principles of inclusiveness, resilience and environmental friendliness has been formed; a new concept - innovative solvates has been introduced into scientific circulation. Based on the cluster analysis, the zones of localization of innovative solvates in the regions of Russia were identified. This made it possible to single out a cluster group with a high scientific and innovative potential, as well as a cluster of regions with the potential to localize innovative solvates, which included regions of industrial and resource specialization. Conclusions. The article presents the directions of solving the problem of achieving the conditions imposed by the circular economy in the innovative solvates of the industrial sector of the region. The study is motivated by several considerations. The first is the formation of an integral conceptual and terminological apparatus, theoretical and methodological basis of research. The second is the establishment of partnerships necessary for the implementation of circularity conditions in an innovative solvate, and the analysis of ways in which a solvate can switch to a circular economy.","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":"67264172","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.2023.9.2.011
Dhyani Mehta
Relevance: With Russia's economy and trade growing significantly since 2014, there is a need to examine the impact of economic openness on government expenditure, given the country's fiscal and trade reforms. Research Objective: This study aims to measure the impact of economic openness on government expenditure (government size) by categorizing it into trade and capital openness. The Auto Regressive Distributed Lag (ARDL) model is used to measure the long-run and short-run impact of economic openness on government size. Data and Methods: Annual time series data from the World Bank Open Data on World Development Indicators (WDI) from 1997 to 2021 is used. The study examines the relationship between government expenditure, trade openness, and capital openness. Results: The findings show that higher trade openness leads to a significant increase in government size, while more capital openness results in a reduction in the size of the government. The study also highlights the impact of current account deficits and national income on government size, with liberal trade policies leading to a widening current account deficit. The positive correlation between national income and government size supports Wagner's Law of "Increasing State Activity." Conclusion: The study suggests that policymakers should adopt a careful approach to liberal policies that encourage trade and capital openness, as an overly liberalized approach could harm macroeconomic factors such as fiscal and current account balances. The study also underscores the challenges that nations like Russia face when entering the global markets for goods beyond oil exports.
{"title":"Impact of Trade and Capital Openness on the Government Size of Russia","authors":"Dhyani Mehta","doi":"10.15826/recon.2023.9.2.011","DOIUrl":"https://doi.org/10.15826/recon.2023.9.2.011","url":null,"abstract":"Relevance: With Russia's economy and trade growing significantly since 2014, there is a need to examine the impact of economic openness on government expenditure, given the country's fiscal and trade reforms. Research Objective: This study aims to measure the impact of economic openness on government expenditure (government size) by categorizing it into trade and capital openness. The Auto Regressive Distributed Lag (ARDL) model is used to measure the long-run and short-run impact of economic openness on government size. Data and Methods: Annual time series data from the World Bank Open Data on World Development Indicators (WDI) from 1997 to 2021 is used. The study examines the relationship between government expenditure, trade openness, and capital openness. Results: The findings show that higher trade openness leads to a significant increase in government size, while more capital openness results in a reduction in the size of the government. The study also highlights the impact of current account deficits and national income on government size, with liberal trade policies leading to a widening current account deficit. The positive correlation between national income and government size supports Wagner's Law of \"Increasing State Activity.\" Conclusion: The study suggests that policymakers should adopt a careful approach to liberal policies that encourage trade and capital openness, as an overly liberalized approach could harm macroeconomic factors such as fiscal and current account balances. The study also underscores the challenges that nations like Russia face when entering the global markets for goods beyond oil exports.","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":"67263968","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.2023.9.1.002
E. Karanina, V. Karaulov
Relevance. Given the volatile global economy, unfriendly policy towards Russia and other external challenges, it is necessary to improve tools for predicting threats and risks to regional economic security and resilience. To this end, individual projections and indicators, as well as complex models should be examined. Research objective. The study aims to develop a new differentiated approach to diagnostics of indicators (projections) of economic security and resilience at the regional level, which can help visualize and evaluate threats to economic meso-systems. Data and Methods. Comparative and indicative approaches, ranking, piecewise linear approximation (scaling) and correlation analysis were used in the study. Results. As a result, the study presents the author's system of indicators of economic security and risks to the regional economy based on a differentiated approach. 36 indicators were grouped into 4 projections – general economic, social, technological and financial – and divided into sub-projections. In order to provide adequate and comparable estimates in the regional and temporal context, various methodological principles were used: application of relative indicators; assessment of cost indicators of regional development using the number of fixed market baskets (FMB) of the region (ratio of the regional cost indicator and the cost of a fixed market basket). Such approach allowed us to evaluate regional economic security in dynamics. The diagnostics of resilience of regional economic systems was performed in the context of individual projections by comparing crisis and relatively stable periods. Conclusions. The methodology was tested using data from regions of the Volga Federal District. The study revealed specific projections, sub-projections and indicators affected by threats, as well as demonstrated the ability of regions of the Volga Federal District to face the crisis and, in particular, resist sanctions.
{"title":"Differentiated approach to the diagnostics of economic security and resilience of Russian regions (case of the Volga federal district)","authors":"E. Karanina, V. Karaulov","doi":"10.15826/recon.2023.9.1.002","DOIUrl":"https://doi.org/10.15826/recon.2023.9.1.002","url":null,"abstract":"Relevance. Given the volatile global economy, unfriendly policy towards Russia and other external challenges, it is necessary to improve tools for predicting threats and risks to regional economic security and resilience. To this end, individual projections and indicators, as well as complex models should be examined. Research objective. The study aims to develop a new differentiated approach to diagnostics of indicators (projections) of economic security and resilience at the regional level, which can help visualize and evaluate threats to economic meso-systems. Data and Methods. Comparative and indicative approaches, ranking, piecewise linear approximation (scaling) and correlation analysis were used in the study. Results. As a result, the study presents the author's system of indicators of economic security and risks to the regional economy based on a differentiated approach. 36 indicators were grouped into 4 projections – general economic, social, technological and financial – and divided into sub-projections. In order to provide adequate and comparable estimates in the regional and temporal context, various methodological principles were used: application of relative indicators; assessment of cost indicators of regional development using the number of fixed market baskets (FMB) of the region (ratio of the regional cost indicator and the cost of a fixed market basket). Such approach allowed us to evaluate regional economic security in dynamics. The diagnostics of resilience of regional economic systems was performed in the context of individual projections by comparing crisis and relatively stable periods. Conclusions. The methodology was tested using data from regions of the Volga Federal District. The study revealed specific projections, sub-projections and indicators affected by threats, as well as demonstrated the ability of regions of the Volga Federal District to face the crisis and, in particular, resist sanctions.","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":"67264278","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.2023.9.1.004
V. Akberdina, E. Kozonogova, Yulia V. Dubrovskaya
Relevance. This article addresses the need for a comprehensive approach to the analysis of socio-economic data on territorial units. The existing statistical observation system provides a vast amount of data on the socio-economic development of countries, macro-regions, sub-regions, and municipalities. Despite the wealth of data available, research efforts often remain narrowly focused on specific scientific tasks. In the field of regional economy, many research methods have been developed, but there are almost no approaches to the combined use of these methods. Digital research platforms can solve these problems by providing a mechanism for complex analysis of data. Research objective. This study aims is to examine the essence of platformization in scientific research and to present a detailed overview of the functionality of existing digital research platforms on regional and spatial development to substantiate the methodology of distributed regional research. The authors examine and systematize the features of 40 digital platforms worldwide that are related to regional research, using methods such as comparative analysis, extended case method, and cross-case analysis. Data and methods. The authors examine and systematize the features of 40 digital platforms worldwide that are related to regional research by using methods such as comparative analysis, extended case method, and cross-case analysis. Results. The proposed methodology includes a system of criteria and a typology that includes five main types of platforms for regional research: information and communication platforms, distributed work and data storage platforms, service platforms, computing platforms, and transaction platforms. These types are described and their advantages and disadvantages are highlighted. Conclusions. Digital platforms should become the key form of organizing scientific research in the field of regional economics, as they allow for a comprehensive analysis of socio-economic data and scenario experiments on the "digital twins" of regions. The study proposes a general methodology for conducting distributed regional studies. This methodology provided a foundation for RegScienceGRID platform. Overall, this study highlights the potential of digital research platforms in regional studies and provides a useful methodology for evaluating and utilizing these platforms.
{"title":"Digital platforms for regional economic research: a review and methodology proposal","authors":"V. Akberdina, E. Kozonogova, Yulia V. Dubrovskaya","doi":"10.15826/recon.2023.9.1.004","DOIUrl":"https://doi.org/10.15826/recon.2023.9.1.004","url":null,"abstract":"Relevance. This article addresses the need for a comprehensive approach to the analysis of socio-economic data on territorial units. The existing statistical observation system provides a vast amount of data on the socio-economic development of countries, macro-regions, sub-regions, and municipalities. Despite the wealth of data available, research efforts often remain narrowly focused on specific scientific tasks. In the field of regional economy, many research methods have been developed, but there are almost no approaches to the combined use of these methods. Digital research platforms can solve these problems by providing a mechanism for complex analysis of data. Research objective. This study aims is to examine the essence of platformization in scientific research and to present a detailed overview of the functionality of existing digital research platforms on regional and spatial development to substantiate the methodology of distributed regional research. The authors examine and systematize the features of 40 digital platforms worldwide that are related to regional research, using methods such as comparative analysis, extended case method, and cross-case analysis. Data and methods. The authors examine and systematize the features of 40 digital platforms worldwide that are related to regional research by using methods such as comparative analysis, extended case method, and cross-case analysis. Results. The proposed methodology includes a system of criteria and a typology that includes five main types of platforms for regional research: information and communication platforms, distributed work and data storage platforms, service platforms, computing platforms, and transaction platforms. These types are described and their advantages and disadvantages are highlighted. Conclusions. Digital platforms should become the key form of organizing scientific research in the field of regional economics, as they allow for a comprehensive analysis of socio-economic data and scenario experiments on the \"digital twins\" of regions. The study proposes a general methodology for conducting distributed regional studies. This methodology provided a foundation for RegScienceGRID platform. Overall, this study highlights the potential of digital research platforms in regional studies and provides a useful methodology for evaluating and utilizing these platforms.","PeriodicalId":33206,"journal":{"name":"REconomy","volume":"558 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67263950","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.2023.9.1.005
Mehmet Özcan
Relevance. Inflation inertia refers to the persistence of inflation over time and can be caused by a variety of factors, including expectations about future inflation, the structure of the economy, and the behavior of economic agents. Over the past two decades, the European economy has grappled with a range of challenges and currently seeks to mitigate the negative impacts of the global pandemic. Research objective. Persistent inflation can lead to uncertainty, decreased investment, and a loss of confidence in an economy. Non-eurozone economies can also face challenges in controlling inflation due to such factors as the lack of monetary integration with the eurozone, limited access to the European Central Bank's resources, and the lack of a unified currency. Hence, for a more effective monetary policy in these countries, it is necessary to measure and understand the inflation inertia. This paper offers a novel empirical study of the dynamics of inflation inertia for seven EU economies that are not part of the eurozone. Data and methods. To achieve the research objective, three non-linear unit root tests are employed to consider both structural changes and regime switching. These tests allowed for the inclusion of almost all non-linear dynamics observed in the inflation series. In addition, the tests involve the use of the dynamic rolling windows sample approach in order to provide more sensitive measurements of the effect of time-varying shocks on inflation inertia. Results. According to the static sample analysis of 200 observations, Bulgaria, Croatia, and the Czech Republic have inflation inertia. Sweden, Romania, Hungary, and Poland do not have inflation inertia when non-linear regime switching dynamics and structural change are considered. However, Croatia and the Czech Republic show a mostly non-stationary inflation in dynamic rolling windows sampling. Hungary has persistent inflation even though it was not detected in the static sample analysis. The shocks of inflation fade out in Bulgaria, Poland, Romania, and Sweden with non-linear dynamics. If non-linear dynamics is ignored, it can lead to misleading results in economic time series. Conclusions. Inflation inertia can be influenced by a variety of factors, including the global pandemic, global or regional conflicts and monetary policy preferences. The successful management of inflation inertia in Romania and Sweden may serve as a model for other economies that have demonstrated an ability to effectively address and mitigate the challenges posed by inflation inertia.
{"title":"Asymmetric Dynamics of Inflation Inertia in Some Selected Non-Eurozone European Countries","authors":"Mehmet Özcan","doi":"10.15826/recon.2023.9.1.005","DOIUrl":"https://doi.org/10.15826/recon.2023.9.1.005","url":null,"abstract":"Relevance. Inflation inertia refers to the persistence of inflation over time and can be caused by a variety of factors, including expectations about future inflation, the structure of the economy, and the behavior of economic agents. Over the past two decades, the European economy has grappled with a range of challenges and currently seeks to mitigate the negative impacts of the global pandemic. Research objective. Persistent inflation can lead to uncertainty, decreased investment, and a loss of confidence in an economy. Non-eurozone economies can also face challenges in controlling inflation due to such factors as the lack of monetary integration with the eurozone, limited access to the European Central Bank's resources, and the lack of a unified currency. Hence, for a more effective monetary policy in these countries, it is necessary to measure and understand the inflation inertia. This paper offers a novel empirical study of the dynamics of inflation inertia for seven EU economies that are not part of the eurozone. Data and methods. To achieve the research objective, three non-linear unit root tests are employed to consider both structural changes and regime switching. These tests allowed for the inclusion of almost all non-linear dynamics observed in the inflation series. In addition, the tests involve the use of the dynamic rolling windows sample approach in order to provide more sensitive measurements of the effect of time-varying shocks on inflation inertia. Results. According to the static sample analysis of 200 observations, Bulgaria, Croatia, and the Czech Republic have inflation inertia. Sweden, Romania, Hungary, and Poland do not have inflation inertia when non-linear regime switching dynamics and structural change are considered. However, Croatia and the Czech Republic show a mostly non-stationary inflation in dynamic rolling windows sampling. Hungary has persistent inflation even though it was not detected in the static sample analysis. The shocks of inflation fade out in Bulgaria, Poland, Romania, and Sweden with non-linear dynamics. If non-linear dynamics is ignored, it can lead to misleading results in economic time series. Conclusions. Inflation inertia can be influenced by a variety of factors, including the global pandemic, global or regional conflicts and monetary policy preferences. The successful management of inflation inertia in Romania and Sweden may serve as a model for other economies that have demonstrated an ability to effectively address and mitigate the challenges posed by inflation inertia.","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":"67264040","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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