Evolution Of Regional Inequality Research Articles

Study on the Synergistic Development of Chinese Traditional Villages Protection and Landscape Development Facilitated by Rural Revitalization

Abstract To establish the comparative advantage of rural development, the mechanism of policy environment on the synergistic development of village gardens is brought into play. In the design of this paper, the coupling degree model of synergistic development is determined by the degree of influence of the coupling elements of village conservation and landscape gardening on each other. The entropy value method was used to eliminate the difference in the scale between the index data and determine the weight of synergistic indexes. The Dagum Gini coefficient method was used to decompose the total Gini coefficient into intra-regional variance contribution, inter-regional variance and super-variance density, effectively measuring regional development inequality. To verify the actual effect of the synergistic development strategy of traditional village protection and landscape development, the results of the simulation analysis show that after the government of region A implemented the strategy, the peak wave of its synergistic development curve increased from 7.2 points in 2017 to 9.6 points in 2022, the total operating income remained above 45.16 billion yuan, and the index of livability and livability was higher than the weighted value of 0.64 on average. It can be seen that with the help of the rural revitalization strategy, the synergistic development of traditional village protection and landscape development can improve the modernization of the countryside and realize the natural symbiosis of the ecological environment and humanistic development.

Determinants of Government Spending on Regional Development Inequality in the East Indonesia Area

This research aims to analyze the economic conditions specifically in Eastern Indonesia (KTI), which is a maritime-based economic area. The research uses government spending variables with three area, namely education, health and infrastructure on development inequality variables. The research method approach used is panel data regression analysis from 2015 to 2020. The results of this study indicating that there are four variables in this study that influence regional development inequality, these variables are local government spending on education, health and infrastructure, and the human development index. The regional government spending variable in the infrastructure sector has no effect on economic growth variables and the economic growth variable has no effect on development inequality. Analysis of the three variables that have an indirect effect on development inequality, namely local government spending on education and health through the human development index and economic growth, and the human development index variable has an indirect effect on regional development inequality through economic growth. Meanwhile, the variable local government spending on infrastructure does not have an indirect effect on regional development inequality through the human development index and economic growth in Eastern Indonesia.

Extracting Patterns of Proximity in Regional Development Inequality Using Hierarchical Agglomerative Clustering

Equitable regional development is still difficult to implement. Many interests in determining regional development priorities make it difficult to realize the main goals of national development. Political interests and the underutilization of regional statistical data are often other obstacles in carrying out regional development. This study aims to classify regional development data to be used to analyse existing development inequalities. Gross regional domestic income (GRDP) data is the main data in this study. The researcher used the hierarchical agglomerative clustering (HAC) technique. The results of the cluster can be used as a consideration for local governments to determine future regional development priorities. In addition, visualized cluster results in the form of a dendrogram can show the proximity of development inequality between regions.

Can renewable energy technology innovation promote mineral resources’ green utilization efficiency? Novel insights from regional development inequality

Strengthening the mineral resource's green utilization efficiency is the key to achieving high-quality development and sustainable mining in China. Moreover, exploring the impact of renewable energy technology innovation (RETI) on mineral resources' green utilization efficiency is integral to boosting the mining industry's overall efficiency and facilitating the energy transition. However, the ability and way of different regions to develop and utilize RETI may depend on their geographical location. Using the dataset covering 30 provinces from 2001 to 2020, this study empirically reveals novel evidence of regional inequality of the impact of RETI on mineral resources' green utilization efficiency. Results show that RETI significantly affects mineral resources' green utilization efficiency. Study results still hold after replacing the explanatory variables, using the instrumental variables technique to solve the endogeneity problem, removing extreme values, and excluding the effects of extreme events. In addition, the impact of RETI on mineral resources' green utilization efficiency depends on the regional location in terms of both significance and marginal effects. RETI significantly promotes mineral resources' green utilization efficiency in the central and western regions, while the opposite is true for eastern regions. Finally, the impact of RETI on mineral resources' green utilization efficiency has various effects depending on the industrial structure and human capital level changes. These findings can provide partial enlightenment for accelerating RETI to facilitate mineral resources' green utilization efficiency.

Does Agroindustry Accelerate Convergence of Economic Growth in East Java?

In most areas of East Java, the economic development still relies on the agricultural sector. Meanwihle, since 2008, agroindustry has grown fast in East Java. This situation should have impact towards higher economic growth in lieu with lower regional development disparity, or speed of convergence improvment. However, the reality seems to be different, where the level of regional development inequality in East Java is still far above the National level. Thus, this study aims to estimate the magnitude of agroindustry in the acceleration of convergence in East Java. This study uses least squares and spatial models as estimation methods as well as the Barro convergence model as the basis of model analysis. The data used is panel data from 38 regions from 2010 to 2019. The estimation results show that agroindustry development has played a role in accelerating convergence improvement, but not too big. One reason is that there is still no spillover effect arising from agroindustry development.

The Effect of Regional Government Expenditures on Regional Development Inequality in Eastern Indonesia, 2015-2020

The existence of differences in resources and processes in the implementation of development in a region causes the ability of each region to encourage the development process also to be different, which causes problems of development inequality between regions. Therefore, an analysis of regional development disparities needs to be carried out. This study aims to analyze the effect of local government spending, the Human Development Index (HDI), and economic growth on regional development inequality in Eastern Indonesia in 2015-2020. This research approach uses a quantitative approach. The data type used is panel data, 12 Provinces in Eastern Indonesia for six years (2015-2020). The analysis tool uses panel data regression with a Fixed Effect Model approach. The results indicate that the variables of government spending on education, health, infrastructure, and human development index directly affect regional development inequality. Meanwhile, the economic growth variable does not affect regional development inequality.

PRC: history of regional inequality

The purpose of the article is to review the historical trends in the regional inequality of the PRC in the period before and after the start of the policy of reforms and opening up (1978). The history of China is characterized by regional inequality of provinces, autonomous regions and cities of central subordination of the main regions of the PRC: Eastern, Northeastern, Central and Western. Chinese researchers Wang Feng, Wang Yunhui, Gan Chunhui, Liang Longbin, Xiao Jincheng, Zhan Zhang conduct a comprehensive analysis of the causes and evolution of regional inequality before and after the start of the reform and opening policy. The consistent implementation of regional spatial transformation strategies has had a particular impact on regional inequality in China. After the founding of the PRC in 1949, industrialization was officially launched. There was a strengthening of the Eastern and North-Eastern regions, while the Central and Western parts of China lagged behind. In the mid 1960-ies taking into account the preparations for war, Mao Zedong proposed to carry out a three-line construction, which involved the placement of the main production facilities of the PRC in Central and Western China. Since the beginning of the reform and opening up policy, Chinas economic development has entered a stage of rapid growth. However, the economic growth of the territory of the PRC was extremely uneven, and the rates of economic growth in different regions varied significantly. Analysis of regional inequality indicators from 1978 to 2000 shows that 1990 marked a turning point in the evolution of regional inequality. It was not until 2003 that disproportionality in the PRC showed a downward trend.

Economic Growth, Investment, Economics Agglomeration, And Regional Development Inequality In West Java Province

Abstract— High economic growth is not always followed by equitable development in a region. This study aims to see the effect of economic growth, investment, and economic agglomeration on regional development inequality in West Java Province. Timeseries data regression analysis West Java Province in the period of 2004–2018 to estimate the effect of economic growth, investment and economic agglomeration on regional development inequality. The results obtained are that economic growth has a significant positive effect on development inequality, amd economic agglomeration has a positive effect on regional development but not significant, while investment has a significant negative effect on development inequality in Java. Keywords— Economic Growth, Investment, Economic agglomeration, Regioanl Development Inequlity.

Dampak IPM, tingkat pengangguran dan tingkat kemiskinan terhadap ketimpangan pendapatan di Sumatera Bagian Selatan

This study aims to analyze the development of the Human Development Index (HDI), Unemployment Rate, Poverty Levels in the Southern Sumatra Region, analyze the condition of regional development inequality in the Southern Sumatra Provinces and analyze the influence of the Human Development Index (IPM), Unemployment Rate, Level of Poverty on income inequality in southern Sumatra in 2010-2019. This research is a quantitative research. The data used is a cross section of 5 provinces in Southern Sumatra and time series for 2010-2019. The data is processed by panel data analysis with fixed effect regression model. Based on the results of the HDI panel data regression test, the unemployment rate and poverty rate have a significant effect on income in Southern Sumatra. All research variables have a simultaneous effect on income inequality. Partially, the HDI variable and the poverty level have no effect on income inequality, while from the research variable only the Unemployment Rate has a negative effect on income inequality.

ANALISIS KETIMPANGAN PEMBANGUNAN REGIONAL WILAYAH KABUPATEN/KOTA PROVINSI SULAWESI TENGGARA TAHUN 2016-2020

The purpose of this study was to determine the level of regional development inequality in the regency/City of southeast Sulawesi Province. The analytical tool used is quantitative in the from of descriptive data analysis and secondry data with the Williamson Indeks analysis method, which is to compare the level of per capita income and population during 2016-2020. Based on the result of calculations using the Development Inequalty Analysis, it fluctuates and decreases, in 2016 it has an inequality of 0.99 while in 2020 it has decreased by o.88. however, if the data are averenged, the regional development inequality level of the regency/city of southeast Sulawesi Provinceis in the range of the high development inequality level category From year to year. And the factor that cause inequality are the increasing number of people who are increasing but the available business fields are still inadequate so that the low level of community income will affect the inequality of development. In addition, the management of natural resource content, demographic conditions, smooth mobility of goods and services, developing all the potensials in each sector and so on can be a solution to reduce development inequality in the disctricts/cities of southeast Sulawesi Province.

Spatial Change in Bulgaria’s Political Elite, 1878–2014

Abstract The question of who should, and who actually does, govern has long been at the centre of empirical and theoretical analyses. This article focuses on the evolution of regional inequality in Bulgaria in terms of political representation. A specially created gis data set facilitated the assessment of changes in the composition of different Bulgarian governments during a long period of political transformation. The database incorporates information about the positions occupied, the time spent in government, the political affiliations, and the places of birth of more than 600 individuals who held cabinet positions in more than 1500 ministerial tenures. Combining different layers of information within the gis allowed the authors to map the evolution of the Bulgarian political elite, to identify historical centres of political influence, and to visualize the transition of power from the provinces of the interior to the capital, Sofia.

Analisis ketimpangan pembangunan wilayah antar provinsi di Pulau Sumatera

Regional development inequality is a strategic issue that is currently being discussed. Sumatra Island has the highest development value when compared to other islands in Indonesia, so this purpose is to measure and analyze development assessments between provinces on Sumatra Island. As well as the influence of government participation, support, investment, labor and GRDP on regional development between provinces on the island of Sumatra. The research method used in this research is descriptive- quantitative analysis method. The value of regional development between provinces on the island of Sumatra from 2010 - 2019 has decreased every year. The results of panel data regression analysis using the Fixed Effect Model (FEM) approach, the results show that the variables of government expenditure, investment and labor have a negative and significant effect on KPW. While the GRDP variable has a positive and significant effect on KPW.

KETIMPANGAN PEMBANGUNAN REGIONAL DAN INVESTASI DI KABUPATEN BANJARNEGARA

This study aims to determine the level of development inequality and investment factors that influence development inequality in Banjarnegara Regency. This research is a descriptive and quantitative research. The data used in this study are secondary data in the form of times series data, namely Gross Regional Domestic Product (GRDP), population, Foreign Investment (PMA) and Domestic Investment (PMDN) from Central Agency Statistics (BPS) of Banjarnegara Regency. The descriptive analysis technique is the Williamson Index inequality, while quantitative analysis is used to use panel data regression analysis of the Fixed Effect model. The results show the Williamson Index in 2002-2020 in Banjarnegara Regency that in 2013 it had a value of 0.580 (the highest than other years). This indicates that development inequality in Banjarnegara Regency is still occurring. The results also show that the Foreign Investment variable has no significant effect on regional development inequality with a probability of 0.964. Meanwhile the Domestic Investment variable (PMDN) has significant effect to development inequality with a probability of 0.000. Considering the policies related to investment, development should be focused on sectors that have multiplier effects for the welfare of the people in Banjarnegara Regency.Keywords: Investment Development, Data Panel, Banjarnegara Regency

Fiscal Decentralization, Economic Growth and Regional Development Inequality in Eastern Indonesia

This study analyzes the relations between fiscal decentralization, economic growth, and regional development inequality in Eastern Indonesia using 2016-2019 panel data of thirteen Eastern Indonesia provinces obtained from Statistics Indonesia and the Directorate General for Fiscal Balance. Using simultaneous equations estimated through the Three-Stage Least Squares, this study finds that fiscal decentralization has not fully supported economic growth and correct the inequality in eastern Indonesia’s regional development. The mandate for managing the budget has not been optimally used by the local governments, indicated by poor allocation for productive expenditures and its decreasing proportion during the research period. It is caused by poor human resource quality in budget planning and management, which finally hinders the quality of public service and economic growth. Supports from physical and human capital are required to keep up with the occurring economic activities so that inequality in regional development in the area can be reduced.

Kemiskinan dan Ketimpangan Pembangunan kabupaten/Kota di Provinsi Lampung

The analysis results used in the problem of poverty are increasingly developing as the understanding of the problem of poverty becomes more complex in the spatial and temporal patterns, seeing the patterns and characteristics of a phenomenon with spatial imaging and study of patterns is the main objective of this study by looking at the pattern of the percentage of poor people and the level of inequality. The method used is processing Moran's I spatial data, Moranscatterplot and LISA, testing development inequality with the Williamson Index, The research area covers 15 districts/cities in 2015-2019. Spatial linkages The percentage of poor people between districts/cities in Lampung Province has a positive Moran's I value, has a spatial pattern with the same characteristics and is clustered. Development inequality is negative Moran's I, Development inequality has a spatial pattern with different characteristics in 2015 -2019. Poverty analysis indicates that during the 5-year study period, 5 districts in Lampung Province were still trapped in high poverty levels, The results of regional development inequality with the Williamson index indicate 3 regions with high levels of inequality, 4 areas of moderate inequality and 8 regions with low levels of inequality.

Development Inequality Analysis Between District and Identification of the Leading Economic Sector

Development inequality between urban areas and rural areas occurs because development is more focused on urban areas than on rural areas development which results in obstruction of the development of rural areas. To determine the level of regional development inequality based on the Williamson Index during the period 2011 - 2017, the pattern of development inequality, an overview of development inequality, the pattern of shifting economic structures, potential economic sectors, an overview of leading and potential sector conditions. We collected data for 7 years from 2014 to 2020 which are in the central Lombok district and kecamatan that have economic and development advantages. This study is a mixed methods study, which is a research step by combining two approaches in qualitative and quantitative research. This study shows that the inequality index of PDRB per capita between districts in Central Lombok Regency is based on Williamson Index with moderate disparities. Klassen typology analysis indicates that the income of the kecamatan is still relatively low in comparison. The inequality picture between sub-districts in Central Lombok Regency based on the Klassen typology analysis of the 12 existing Districts shows that only Pujut District is included in the sub-district with rapid growth region. with the results of the research the sub-districts in Central Lombok district have relatively low income and development levels, but Pujut sub-district has an attraction for investors by seeing the high income from the tourism sector.

Perkembangan Wilayah, Keselarasan Penggunaan Lahan Dengan Pola Ruang, Dan Arahan Rencana Pengembangan Wilayah Kabupaten Tangerang

Tangerang Regency has an economic structure dominated by the industrial sector. Population distribution, settlement location and industrial influenced land use patterns and regional development levels in Tangerang Regency. The objectives of this research are: to analyze the level of regional development and regional development inequality and factors that influence regional development; to analyze regional typology; to evaluate the consistency of land use with the Spatial Planning; and to formulate direction of the Tangerang Regency regional development plan. The method used are scalogram analysis, theil entrophy index analysis, cluster analysis, overlay and descriptive analysis. The results showed that the regional development level of the southern part of the region was higher than the northern part and the level of regional development inequality in the northern part of the region was higher than the southern part. Factors that influence the level of regional development are the percentage of settlement and industry areas, and the value of economic index, education index, and health index. Concerning typology of the area, in the northern part land use is dominated by agriculture, while in the southern region dominated by settlements and industries. The inconsistency of land use with spatial plan found mostly in the northern region. Thus, the first priority of regional development direction is to be located in the northern part that has a low level of regional development, high inequality value, high percentage of inconsistency of land use with spatial plan, and land use that is dominated by agriculture.

РЕГИОНАЛЬНОЕ НЕРАВЕНСТВО В СОЦИАЛЬНО-ЭКОНОМИЧЕСКОМ РАЗВИТИИ РОССИИ

The topic of regional inequality in socio-economic development is becoming more relevant every year. Ensuring the uniform development of the Russian regions is complicated by the high degree of heterogeneity of the country's economic space, which is expressed in socio-economic inequality between the regions. Currently, there is a differentiation of the subjects of the Russian Federation by the sectoral structure of GRP, by the level and quality of life of the population, etc., there are imbalances in budget security. This leads to a decrease in the attractiveness and competitiveness of the regions and generally weakens the national economy. According to the World Bank, Russia ranks 3rd in the world in terms of regional inequality. Government documents indicate that the state's goal is to reduce the differentiation of socio-economic development in regions with a reduced standard of living by 2022. The spatial development of most economic entities is characterized by significant differences. Economists point out that interregional asymmetryarises due to competitive advantages and features of the institutional environment. Reducing the inequality of regional development is possible if the standard of living in the depressed regions of the Russian Federation is increased. An important area for assessing the differentiation of regions is the development of a system of indicators that assess regional inequality. The assessment of the role of the region in the production of GRP can be obtained by calculating localization indicators and relative position indices, the dynamics, variation and depth of regional inequality are characterized by dispersion coefficients, as well as the differentiation of the population of regions by income, the analysis of the uniformity of the distribution of regions can be obtained from the analysis of income concentration indicators. In general, it can be noted that regional inequality in the socio-economic development of Russia tends to increase.

Regional Development and the Education System in the Context of Digital Transformation

The paper aims to assess how the existing imbalance between the education system and the regional economy influences the formation of spatial inequality and uneven economic development. Based on the structural and comparative analysis of data on Russia and China as the members of the Organization for Economic Co-operation and Development, we demonstrate that the technologies of the 4th Industrial Revolution shift the demand for highly skilled labour force. This situation leads to the gap between labour demand and supply, as the education systems are oriented to the economic needs of the 3rd Industrial Revolution. We consider cross-country differences in the quantity of STEM graduates and researchers (science, technology, engineering, and mathematics) as a possible cause of spatial inequality in the context of digital transformation. Further, on the example of Russia, we apply correlation and regression analysis to show that the discrepancy between the skill level of graduates and market expectations contributes to regional development inequality. We demonstrate the strong relationship between the share of unemployed persons among the economically active population and the skills of the labour force for all federal districts of the Russian Federation. On average, an increase in the share of employees with higher or secondary vocational education by 1 % decreases unemployment by 0.32 %. Additionally, in all federal districts of Russia, there is a discrepancy between the economic need for highly qualified workers with higher education and the education system producing too many specialists with secondary vocational education. The discrepancy between the structure of skilled labour force produced by the education system and the employment structure in the labour market by 10 % increases unemployment by almost 1 %. The results of the study can be used by the government for creating the development strategy of the education system and reducing spatial inequality.

Energy infrastructure investment and regional inequality: Evidence from China's power grid

Effective energy infrastructure investment strategy could optimize the reallocation of energy resources, promote the coordinated development across regions, and narrow the regional development inequality. This paper, from the perspective of inclusive growth, investigates how the energy infrastructure investment could affect the regional economic growth, based on the evidence of China's power grid during 2000–2014. The “Effective Cost Index” (ECI) is formulated to measure the development degree of power grid infrastructure (PGI) at first. After that, the economic growth convergence model is adopted to analyze the impact of PGI on regional economic convergence by the method of system GMM. Moreover, different PGI investment scenarios are simulated to discuss what the optimal investment distribution is. The results present that the ECI can impact the regional economic growth negatively, and the PGI investment may generate higher marginal benefits for the less developed inland areas than the developed coastal areas. In China, the most effective way to narrow regional inequality is to distribute the PGI investment to the central hub provinces.