Evolution Of Regional Disparities Research Articles

Green Economy from a Regional Perspective – a Polish Case Study

The article presents the elaboration and specification of the green economy concept, where resource scarcity, global climate change and environmental degradation are paving a new path towards sustainable development. The article addresses the issue of implementing the principles of green economy at the regional level. The implementation of a green economy at a regional level provides an excellent space for scientific deliberations. The aim of the research is to identify and assess the level of regional disparities in green economy development across Polish regions using a synthetic measure. The basis for the analysis was a set of substantively and statistically analyzed diagnostic variables from the years 2012-2022. The synthetic indicator of the green economy was calculated for every Polish region (NUTS 2) and the regions were ranked based on their score from highest to lowest. As a result of the analysis, the regional polarization and the ordering of regions in Poland in terms of the synthetic metric - green economy development - were discussed. Keywords: green economy, green growth, sustainable development, taxonomic methods.

The Impacts of Urban Population Growth and Shrinkage on the Urban Land Use Efficiency: A Case Study of the Northeastern Region of China

In the context of rapid urbanization, urban population differentiation has become increasingly pronounced. Regional development strategies based on growth scenarios often lead to continuous expansion, regardless of urban population status. Such “one-size-fits-all” models exacerbate resource waste and negatively impact urban land use efficiency (ULUE). This study aims to explore the mechanisms by which urban population growth and shrinkage (UPGS) affect ULUE, with the goal of enhancing ULUE and promoting sustainable urban development. We analyzed 34 prefecture-level cities in China’s three northeastern provinces. First, we identified UPGS using population data. We then employed a three-stage SBM-DEA model to measure ULUE from 2000 to 2020. Spatial analysis methods were used to examine the spatiotemporal characteristics and correlations between UPGS and ULUE. Additionally, mediating effect models and spatial Durbin models were utilized to empirically test the impact processes, mechanisms, and spatial heterogeneity. Our findings reveal that: (1) Over the past 20 years, urban population shrinkage in northeastern China has intensified, and significant regional disparities in urban development are evident. (2) Population growth positively influences ULUE, while population shrinkage inhibits its improvement. (3) Economic development, technological innovation, and industrial structure upgrading are key factors in enhancing ULUE in this region, while the impact of public services on ULUE varies significantly at different stages of urban development. (4) Economic development, technological innovation, and industrial structure upgrading exhibit spatial spillover effects, whereas public services are constrained by regional limitations, resulting in minimal spatial spillover effects. To foster coordinated regional development, this study proposes policy recommendations, including strengthening support for resource-dependent cities, optimizing the allocation of public resources, and promoting technological innovation and industrial diversification.

The Influence of Policy Investment on the Sustainable Development of Universities in Underdeveloped Regions: An Empirical Analysis of China’s Higher Education Landscape

The regional disparity in higher education development is critical for the sustainable advancement of the national education system. To address this issue, the Chinese government has implemented targeted support policies for higher education in underdeveloped regions, with the “Ministry-Province Co-construction Policy” serving as a notable example. This study investigates the impact of such policies on the development of universities in China’s underdeveloped central and western regions. First, the study analyzes policy documents to identify six primary policy pathways through high-frequency word extraction, social semantic analysis, and path integration. These policy pathways are quantified using representative indicators, which constitute the independent variables of the study. Second, by employing the framework of modern university functions, the study develops a sustainable development indicator system for higher education institutions. The performance scores for the sustainable development of 14 universities, derived using the entropy method, serve as the dependent variables. The study subsequently measures the effects of individual and combined policy pathways through two equations. The results indicate that some pathways are more effective than others. While all combined policy pathways yield positive effects, an excessive number of combinations can lead to diminishing returns. Finally, the study elucidates the measurement results, emphasizing that effective pathways highlight the essential roles of faculty, research, and teaching. Conversely, less effective pathways stem from inadequate inputs or slow responses. Although combined policy pathways generally exert positive impacts, an overabundance of combinations can dilute these benefits. The study suggests that administrative support for higher education in underdeveloped regions is advantageous. It underscores the necessity of distinguishing between more and less effective input methods, concentrating on resource allocation, and ensuring universities’ autonomy in utilizing support resources to achieve sustainable development in higher education within these regions.

The impact of digital economy on energy conservation and emission reduction: evidence from prefecture-level cities in China

In the face of global climate challenges and energy crises, China aimed to enhance energy conservation and emission reduction (ECER). This study explored the role of the digital economy in boosting energy efficiency and supporting sustainable development by constructing an index system, applying principal component analysis, and using spatial econometric models to assess the impact of digital economic development in China's prefecture-level cities on ECER. Findings revealed regional development disparities and complex spatial interactions that influence ECER. The digital economy showed potential to reduce emissions after reaching a particular scale, suggesting policy recommendations for balanced growth.

China's Foreign Exchange Market: Research on Problems and Countermeasures

The foreign exchange derivative market plays a vital role in the global economy. As one of the world's largest economies, China has already recognized the significance of establishing a well-regulated foreign exchange market. However, the Chinese foreign exchange market still faces several challenges. There are four main challenges: regional disparities in development, low level of diversification, high market risks, and inadequate regulation. These issues should draw public’s further attention and get resolution. This paper aims to analyze the four problems above in China's foreign exchange derivatives market and propose feasible solutions, including alleviating the imbalance problem, strengthening market diversification, reducing information asymmetry and strengthening the government supervision, which help to address the identified problems. The research findings are also helpful for some market participants and policymakers to understand the shortcomings of China's foreign exchange derivatives market better, and thus designate more rigorous trading strategies and improve the environment for China's foreign exchange derivatives market.

Assessment of green development level performance in G20 countries: A dynamic evaluation framework

To achieve sustainable development goals and foster future prosperity globally, the promotion of green development is essential. Nevertheless, persistent regional disparities in green development among the G20 nations stem from differing economic and environmental conditions in dynamic contexts. In light of these conditions, it is essential for governments to evaluate their country's current green development performance in comparison with higher-performing nations and to learn from their experiences. This study introduces a new dynamic evaluation framework that integrates the importance of evaluation indicators using the dynamic entropy weighting method, a Dynamic Technique for Order Preference by Similarity to Ideal Solution method, and principal component analysis. This framework serves as a tool for G20 countries to assess their green development levels between 2015 and 2021. A key contribution of this study is the facilitation of the G20's ability to implement relevant reform measures and monitor green development progress in a dynamic environment. This framework can serve as a model for similar evaluations in other regions globally. The study's main findings indicate that G20 countries with high levels of green development possess strong economic foundations and prioritise the balanced development of their economies, societies, environments, and innovation.

The Impact of Digital Economy Development on Improving the Ecological Environment—An Empirical Analysis Based on Data from 30 Provinces in China from 2012 to 2021

The rapid progress in science and technology has ushered in a new era of organized and efficient development within the digital economy. China has repeatedly emphasized the need for high-quality development that prioritizes ecological conservation. The central challenge is to balance economic growth with environmental protection, ensuring sustainable development. Understanding the environmental impact of the digital economy is critical for achieving green growth in China. This paper investigates the relationship between the digital economy and ecological protection, using data from 30 provinces and cities in China between 2012 and 2021. Through empirical analysis, including a two-way fixed effect model, mechanism analysis, regional difference analysis, and robustness tests, the study found a significant negative correlation between the digital economy and environmental pollution. This indicates that the development of the digital economy can effectively improve the ecological environment. In the information age, seizing the opportunities presented by the digital economy is crucial. By deepening the digital industry and leveraging digital technologies, China can enhance enterprise production, promote innovation, and create a positive feedback loop between economic development and environmental optimization. However, it is essential to recognize regional disparities in digital economy development and work to narrow these gaps, ensuring balanced and sustainable growth across the country.

Urban sustainable development goals and ecosystem services: Pathways to achieving coordination

It has been widely recognized that progress toward achieving Sustainable Development Goals (SDGs) must be better harmonized with Ecosystem Services (ESs) to tackle global challenges. In China, the National Key Ecological Function Areas (NKEFAs) were set up as one of the ecological fiscal transfer projects. Despite its significant influences on the SDGs-ESs nexus, there is a lack of empirical studies on the effects and mechanisms of policy. In response, this study provides a synthesized framework that incorporates the coupling coordination degree between the Urban Sustainable Development Goals (USDGs) and Ecosystem Services Scores (ESSs), empirically verifies the policy effect using the difference-in-differences model, and then further investigates the mechanisms of government action to coordinate urban SDGs and ESs. The results show that: (1) The coupling coordination degree between USDGs and ESSs varies significantly across different regions but steadily increases over time, with a faster increasing rate of coordination degree growth in NKEEFAs pilot cities compared to non-pilot cities. (2) The policy has demonstrated benefits in coordinating USDGs and ESSs with a coefficient of 0.005. In detail, the policy enhances ESSs but concurrently exerts a negative influence on USDGs, with coefficients are 0.008 and −0.004 respectively, suggesting an uneven distribution of the policy's impacts. (3) The study unveils the 'technological innovation effect' and the 'industrial agglomeration effect' as crucial mediating pathways for policy effect, laying a solid foundation for USDGs and ESSs coordination. In total, the study highlights the critical need to account for regional development disparities and adequate funding in ecological protection policies to ensure fairness and effectiveness from a central decision-making standpoint. It recommends enhancing transparency in fiscal expenditures and fostering regional joint coordination to address local government challenges. These insights from this study can offer valuable guidance for policymakers to refine policy implementation and promote the coordination of regional ESs and SDGs.

Analysis of the Impact of Urban Infrastructure on Urbanization Processes at Different Levels from a Spatiotemporal Perspective

A comprehensive understanding of the heterogeneity of urbanization development at different levels and its influencing factors is crucial for promoting global urbanization and advancing China’s new urbanization. Using indicators related to urbanization development, a multidimensional index system was constructed based on five dimensions: population, economy, space, society, and ecology. Employing methods such as the Mann–Kendall test, Sen’s trend analysis, multiple linear regression, and spatial autocorrelation analysis, the spatiotemporal evolution characteristics of urbanization from 2000 to 2019 were analyzed comprehensively at national, economic zone, provincial, and prefectural city scales. The results indicate the following. (1) From 2000 to 2019, urbanization levels at all levels showed an overall upward trend, with the national urbanization rate increasing most rapidly at 5.39%. (2) Trend analysis reveals rapid and significant growth trends in urbanization at the national and economic zone scales, while urban-level changes exhibit greater diversity and spatiotemporal heterogeneity. (3) Spatial distribution patterns show that urbanization levels in the eastern coastal economic zones are significantly higher than those in the northeastern economic zones, highlighting pronounced regional disparities in development and agglomeration effects in economically advanced regions and provinces. (4) Regression analysis demonstrates that spatial urbanization significantly influences urbanization development in China, with urban infrastructure playing a crucial role across different levels.

Poverty in the Kazakhstan Regions: Assessing the Influence of Key Indicators on Differences in Its Level

Modern Kazakhstan is characterized by significant regional socioeconomic differences due to climatic conditions, natural resources, migration, and regional specialization. The persistence of these regional differences can lead to increased stratification of society, social tension, and disruption of the country’s economic stability. These issues have intensified under the influence of Industry 4.0 trends and geopolitical processes in the region. Among the various sources of social inequality, we have chosen to focus on the problem of population poverty in our study. Addressing this problem is crucial for taking a comprehensive approach to addressing regional disparities in social development. The purpose of our study is to determine and assess the features of poverty in the regions of Kazakhstan. Our research methodology is based on evaluating the integral poverty index using four indicators: the share of the population with incomes below the subsistence level, the population under 60 years of age, youth aged 15–17 who are not working or studying, and the unemployment rate in the regions of Kazakhstan. Based on these indicators, we grouped the regions according to their poverty level, identified and compared regional differences, and identified the most vulnerable areas in need of intervention. This approach has enabled us to propose appropriate instruments of state support for different territories and promote inclusive regional development to overcome social imbalances.

The Influence of Demonstrative Formal Rules on the Dynamics of the Effectiveness of Institutional Frameworks

Abstract The purpose of this article is to identify the impact of demonstrative formal rules on the dynamics of the effectiveness of institutional frameworks. The importance of forming an effective institutional framework for any country is undeniable. The presence of an effective institutional framework is a prerequisite for ensuring the successful socio-economic development of the country, on the other hand, an ineffective institutional framework can have a wide range of negative consequences, including disparities in regional development. However, the achievement of today’s effectiveness of institutional frameworks cannot guarantee the proper socio-economic development of the country in the long term, because the institutional framework of any country is not unchanged, but is in a state of constant transformation due to the need to adapt the current formal rules to the new challenges facing society. Accordingly, the identification of the factors that determine the dynamics of the effectiveness of formal rules is no less important than the identification of the factors of ineffectiveness of formal rules. It is shown that one of these factors is demonstrative formal rules, that is, rules whose target effectiveness was not taken into account from the very beginning, and the only purpose of their implementation was to increase the political ratings of the initiators of their implementation. It has been proven that an effective measure to prevent the spread of demonstrative formal rules can be an increase in the general education of the population. The main advantages of the proposed measure are the low level of transaction costs and the absence of danger of manipulating public sentiment.

EU experience in regional distribution of science and innovation funding

Regional allocation of R&I funding in the European Union is an important tool for stimulating economic growth and social development in different regions. This article explores the EU's experience in regional funding of science and innovation, identifying key trends, challenges and good practices. The regional approach to funding science and innovation aims to reduce disparities in regional development, support less developed regions, and facilitate the integration of different regions into the European research area. At the same time, there are significant challenges related to the uneven distribution of funding, insufficient institutional capacity of regional bodies and lack of coordination between different funding programmes. The paper analyses the impact of R&I investments on regional development, especially in the context of the growing role of intangible assets and digital technologies. The results of the study highlight the need to further improve funding mechanisms, enhance the institutional capacity of regions, and increase coordination between different funding programmes. This would ensure a more equitable distribution of resources and help to increase the competitiveness of less developed regions. For Ukraine, an understanding of the European regional distribution of funding for science and innovation can be very important for its successful integration into the European Research Area, contributing to improving the quality of education and science, strengthening the innovation ecosystem, optimising resource allocation and increasing Ukraine's competitiveness on the international stage.

Assessing the Regional Socio-Economic Disparities, Evidence from Jordan

Objectives: Regional disparity in development among regions in developing countries is a common issue. Despite being a small, emerging economy, Jordan suffers from this problem. This study aims to identify and explore regional disparities in Jordan between 2010 and 2018 by integrating social and economic factors. Methods: A mixed-methods approach combining statistical analysis and Geographic Information Systems (GIS) techniques was employed to uncover the economic and social disparities in Jordan, and classify the governorates accordingly. This study presents the results of the Lorenz curve and the site quotient and shows the direct interactions between social disparities on economic disparities in Jordan. Results: The results indicated significant differences between the twelve governorates in Jordan. The capital city, Amman, possesses the highest share of social and economic factors in Jordan and is the only governorate with the highest economic growth. The second and third-ranking governorates in terms of ratios are Irbid and Zarqa. Conclusions: The study recommends implementing balanced and obligatory regional development plans, utilizing an integrated team of experts, decision-makers, investors, and local representatives. Emphasizing the importance of decentralization and empowering local councils in the governorates is crucial.

Evaluation of the Performance of SMEs in the Context of Regional Development

Research background: Regional development of the European territory is becoming a key priority area and thus arouses interest in analyzes of the impact of development not only of business activities on economic competitiveness. Entrepreneurship is an important part of every country's economic system and has important implications for the growth of society. The paper focuses on the possibility of identifying the determinants of regional competitiveness of the manufacturing industry with a focus on defining their impact on SME performance, in the sense of EVA in the programming period 2014-2020. Purpose of the article: The presented paper focuses on the performance of companies in the Czech economy in connection with the reflection of national regional policy documents. Purpose of the article is to evaluate the economic performance of small and medium-sized enterprises in the manufacturing industry in connection with the level of development of the regions in the Czech Republic in which they are located. Methods: The evaluation of the achieved level of regional development is performed at the level of regions and administrative districts of municipalities with extended powers. Through multidimensional regression modelling, the determinants of regional development disparities are identified with a focus on defining their impact on the performance of small and medium-sized enterprises expressed by the economic value added (EVA) indicator. Findings & Value Added: Public sector expenditure on science and research was evaluated as the most important parameter of regional disparities, which explains the economic performance of companies. Based on the achieved results, measures are proposed for the cultivation of the business environment for the next programming period. The contribution is the proposals for the formulation of regional policy with a focus on the segment of small and medium-sized enterprises.

Assessing Regional Development Disparities in Wasit Governorate a Descriptive Analysis of Service Delivery and Resource Allocation

Assessing Regional Development Disparities in Wasit Governorate a Descriptive Analysis of Service Delivery and Resource Allocation

Development Level of Digital Government: A Qualitative Comparative Analysis of Fuzzy Sets Based on 31 Provincial Capital Cities in China

The onset of the information era has accelerated the transformation of digital governance, establishing it as a critical component in the modernization of governance frameworks and capabilities worldwide. Despite considerable advancements in the field of digital government, regional disparities in development remain pronounced, emphasizing the necessity for a coordinated and effective approach. This study employs a qualitative comparative analysis (QCA) of fuzzy sets to assess 31 provincial capitals in China, aiming to discern the digital governance ecosystems that promote the development of digital governments. It is grounded in the TOE framework, which examines the dynamics among technological, organizational, and environmental factors. The results provide empirical insights into the architecture of digital governance, offering a detailed comprehension of performance levels and recommending specific policy directions to enhance digital government progression.

Research on Territorial Spatial Development Non-Equilibrium and Temporal–Spatial Patterns from a Conjugate Perspective: Evidence from Chinese Provincial Panel Data

Clarifying the intrinsic nature and formation mechanisms of the territorial spatial development non-equilibrium, optimizing the allocation of territorial resources, promoting regional balanced development, and alleviating regional development disparities have become common endeavors of all countries seeking to enhance development quality. This study, based on the land use and socio-economic data of 31 provinces and cities in China from 2006 to 2020, utilized the kernel density estimation method and ArcGIS spatial analysis to explore the spatiotemporal evolution characteristics of China’s territorial spatial development non-equilibrium. The research findings are as follows: (1) From 2006 to 2020, both the land development intensity and land supply capacity showed an increasing trend, with increases of 21.4% and 8.03%, respectively. However, their spatiotemporal evolutions significantly differed. (2) The state of the territorial spatial development non-equilibrium in China significantly improved, with a rising trend in the territorial spatial equilibrium degree. Regional disparities in the territorial spatial equilibrium degree decreased. The number of provinces and cities in a state of underdevelopment decreased from 23 to 8, while the number in an equilibrium state increased from 7 to 21. The central and western regions showed more significant improvements in the territorial spatial equilibrium degree and a greater reduction in regional disparity when compared to the eastern and northeastern regions. (3) China exhibited distinct regional disparities in the territorial spatial equilibrium degree. The overdeveloped areas were Beijing and Shanghai. The underdeveloped regions were primarily concentrated in western areas, including Sichuan, Yunnan, and Xinjiang. The high-level equilibrium regions were predominantly located in the southeastern coastal provinces and the central plains region, while the low-level equilibrium regions included Inner Mongolia, Ningxia, Qinghai, and the three northeastern provinces. (4) From the perspective of the number of agglomeration types, the order is HH (high–high) > LH (low–high) > LL (low–low) > HL (high–low), and China’s TSED exhibits a spatial proximity peer effect. The innovation of this study consists of the following aspects: (1) The clarification of the fact that the essence of equilibrium does not require an exact 1:1 match, as with “two horses”; rather, it entails the maintenance of a slight surplus of land supply capacity over land development intensity. This approach allows the possibility of future sustainable development by leaving room for expansion. (2) The differentiation between high-intensity conjugation (in terms of both quantity and quality) and low-intensity conjugation (quantity only) from a conjugate perspective. This categorization aids in a more comprehensive and in-depth understanding of the territorial spatial development non-equilibrium and its spatiotemporal patterns. It provides crucial information for the formulation of sustainable national territorial development plans and the promotion of a regional development equilibrium.

Estimating built-up area carbon emissions through addressing regional development disparities with population and nighttime light data

Carbon emission inventories in urban built-up areas are critical for formulating effective emission reduction policies. Nighttime light data, reflecting socioeconomic activities, is routinely used as a proxy for estimating emissions. However, the reliability of this proxy is limited in areas with minimal or absent lighting and demonstrates variability according to the urban development. To address these limitations, a novel approach was developed. Firstly, it enhances the representation of human activities under different light values through integrating light values and population distributions into multidimensional proxy features. Secondly, cities with different socio-economic development were clustered to minimize the development disparities within the same cluster. Four clusters were detected including ‘Agriculture-dependent & Low-density’, ‘Agriculture-dependent & High-density’, ‘Industry-oriented’, and ‘Tertiary-oriented’. Then A multilayer perceptron regressor, refined with a moving average method, was employed to model the nonlinear relationships between emissions and these proxy features. The results show a significant increase in modeling accuracy when regional development disparities are incorporated through this clustering strategy. Additionally, the Shapley Additive Explanatory method was utilized to analyze the influence of regional development heterogeneity on the estimation model. It demonstrated that areas with high light intensity and population significantly influence emission estimates in all clusters, except for the ‘Industry-oriented cluster’. This finding underscores the varying effectiveness of proxy features across different regions, emphasizing the importance of considering regional development disparities. Finally, based on the estimated inventory obtained, spatio-temporal hot spot detection pinpointed eastern and central China as significant emission hot spots. This research not only enhances the data resources for managing carbon emissions but also underscores the need for inter-city cooperation strategies to achieve China's carbon reduction targets.

Growth and distribution regimes under global value chains: Diversification, integration, and uneven development

This study investigates the macroeconomic interactions between productive structure and income distribution in the context of Global Value Chains (GVC). Our research goes beyond the traditional scope by presenting a detailed typology that examines how globalisation has amplified uneven development processes on a global scale. This in-depth exploration provides valuable insights into the intricate interplay between global economic integration and regional development disparities, thereby contributing to the broader understanding of growth and distribution in the context of globalisation. We propose a theoretical framework inspired by the Structuralist literature to identify three distinct regimes in globalised production chains: (1) a structure/diversification regime based on the Balance of Payments Constrained Model (BPCM) literature, (2) an integration regime derived from the GVC literature, and (3) a functional income distribution regime in open economies. We use Principal Component Analysis (PCA) to create indices (proxies) for each regime to then identify country patterns within a structured typology. We then analyse growth trajectories and estimate the causal relationship between these regimes and per-capita growth using multiple regression models – fixed effects (FE), instrumental variables (IV), and generalised method of moments (GMM). Our dataset includes data from 60 countries between 1995 and 2018, sourced from the World Development Indicators (WDI), World Input-Output Database (WIOD), Trade in Value Added (TiVA), and the Penn World Tables (PWT). This study significantly enhances the understanding of structuralist growth models by offering a comprehensive and unified narrative on the variety of economic growth regimes within Global Value Chains (GVCs).

A study of the impact of the digital economy on regional energy efficiency

The digital economy, emerging as a new form of economic system, holds a crucial position in enhancing energy efficiency. It does so by streamlining the distribution of resources with the help of data and augmenting the flow efficiency of production factors. This paper examines the precise role and mechanism of the digital economy in enhancing energy efficiency from both theoretical and empirical perspectives. This paper utilises panel data from China's provinces and cities over a fifteen-year period, ranging from 2006 to 2021. The fixed-effects model is employed to investigate the precise pathway in which the level of digital economy development influences energy efficiency. The study reveals that the digital economy has a notable impact on enhancing energy efficiency. The analytical mechanism indicates that the digital economy effectively improves energy efficiency by advancing regional marketisation, optimising the industrial structure, and fostering innovation and the adoption of new technologies. Owing to considerable disparity among diverse parts of China, the digital economy seems to have a positive impact on the eastern and central regions, while its influence remains restricted in the western regions. Meanwhile, the areas encompassed by the Yangtze River Economic Belt are the most viable for advancement in energy efficiency through the digital economy. The influence of the digital economy on energy efficiency is markedly inconsistent due to the considerable variation in resource allocation among various regions. The role of the digital economy in enhancing energy efficiency is particularly evident in regions with moderate resource endowment. Thus, this study contends that realisation of the digital economy's capacity requires the government to consider the regional development disparities and resource endowment circumstances. To achieve balanced regional growth and comprehensive progress in energy efficiency, the government must develop tailored policies that promote marketisation, optimise industrial structure, and incentivise technological advancement. Therefore, the implementation of these measures is crucial.