Changing Regional Inequality Patterns in Western China: A Case Study of Xinjiang

Regional inequality in western China has been rarely examined and has risen as an important issue in the Chinese academic circle. This study, taking Xinjiang as a case, investigated regional inequality in Xinjiang since the 1990s. The results show that the interregional inequality became more prominent, while the overall regional disparities among counties and cities have experienced an inverted U-shape path and have been mainly caused by the inequality of the intra-north part of the province. Counties with high economic development levels were mainly located in northern Xinjiang and had a high probability of further moving economic levels. We further found that the regional development pattern in Xinjiang was significantly associated with spatial accessibility, followed by population density and urbanization factors. This paper deepens our understanding of the complex pattern and mechanism of regional inequality in western China, and local specific policies, therefore, are needed to solve the problem.

Spatial Analysis of Regional and Income Inequality in the United States

Understanding the spatial or geographical dependence of income inequality and regional inequality is crucial in the study of inequality. This paper employs a multi-scale, multi-mechanism framework to map and analyze historical patterns of regional and income inequality in the United States (US) by using state and regional panel data spanning over a century. To explore the patterns systematically and see the role of spatial partitioning, we organize the data around several established geographical partitions before conducting various geographical information system (GIS) analyses and statistical techniques. We also investigate the spatial dependence of income inequality and regional inequality. We find that spatial autocorrelation exists for both types of inequality in the US. However, the magnitude of spatial dependence for regional inequality is declining whereas it is volatile for income inequality over time. While income inequality has been at its peak in the most recent decades, we also notice that regional inequality is at its lowest point. As for the choice of partitioning, we observe that within inequality dominates for Census Divisions and Bureau of Economic Analysis (BEA) regions. Conversely, we see that between inequality overall contributes the most to the inequality among Census Regions.

The Impact of the State Policy of Regional Development on the Socio-Economic Alignment of the Regions of the Russian Federation

The state policy of regional development, being part of the internal policy of the state, has its own priorities, principles, goals and objectives aimed, inter alia, at reducing regional inequality. The authors of the study pay special attention to the consideration of public-private partnership mechanisms.

Private Healthcare Expenditure in China: A Regional Comparative Analysis

Private (out-of-pocket) healthcare expenditure (PHCE) is a complex phenomenon that is shaped by many different factors. In this paper, we analyzed the influencing factors of PHCE in China, with a specific focus on regional differences. We found that old-age dependency ratio, income, and education have significant impacts on PHCE in all regions, whereas public HCE, number of beds in medical institutions, and economic development levels have significant impacts only in some regions. The results indicate that the government should pay attention to regional inequality and implement targeted adjustments for improving the health service system. In particular, we recommend: (1) monitoring regional inequality in PHCE and other healthcare issues to unmask geographical differences in healthcare interventions; (2) adopting regional-specific policy measures—the government should divert some resources from eastern to western and central regions to increasing the support for public health undertakings and improve the quality of the local health services while providing matching medical resources by targeting the needs of the residents; (3) paying more attention to the healthcare demand of the elderly population; and (4) improving the education level of residents to improve public health and avoid high PHCE.

Analysis of the Relationship between Human Development Index and Regional Development of West Sulawesi Province

This study aims to analyze the relationship between the human development index and the regional development of West Sulawesi Province. This study uses panel data analysis that combines time series-cross section data and uses the Two Stage Least Square (2SLS) method. The type of data in this study is secondary data taken from the Central Statistics Agency (BPS) of West Sulawesi. The variables of the human development index are life expectancy, average length of schooling, expected length of schooling and purchasing power index. While the variables of regional development are poverty, unemployment, regional inequality and GRDP. The results of the analysis using the 2SLS method. In the HDI equation, the PW variable partially has a negative but not significant effect on the HDI for =5%. However, if for =20% PW has a negative and significant effect on HDI. While in the PW equation, the HDI variable partially has a negative but not significant effect on PW for = 5%. The R2 in the HDI equation is 97.5% and the remaining 2.5% which shows that the influence of PW, Life Expectancy, Average Years of Schooling, Expected Years of Schooling, and Purchasing Power Index together have an effect on HDI. While in the PW equation, the determination of R2 is 99.2% and the remaining 0.8% which shows HDI, Poverty Level, Unemployment Rate, Regional Inequality and Gross Regional Domestic Product together affect PW. So, there is a simultaneous relationship between the Human Development Index and Regional Development

A Collaborative Trans-Regional R&D Strategy for the South Korea Green New Deal to Achieve Future Mobility

In response to the COVID-19 pandemic, South Korea is moving to establish a national industry strategy to reduce regional inequalities within the country through the Green New Deal. Thus, it is important to closely integrate the aim of reducing greenhouse gas emissions from the Green New Deal with that of reducing deepening regional inequality from the Regionally Balanced New Deal. To accomplish these dual aims, this study provides a collaborative trans-regional R&D strategy and a precise framework with three key dimensions: regional, technological, and organizational. We demonstrate that future mobility is the most important project of the Green New Deal, comprising 1963 nationally funded projects worth USD 1285.4 million. We also illustrate the level of government investment in nationally funded research projects related to future mobility for 17 different regions and seven different technology clusters related to future mobility, and determine which research organizations played an important role in each cluster for all 17 regions between 2015 and 2020. Our results indicate that the capital region and Daejeon have high innovation capability in many future mobility-related research fields, whereas some regions have capabilities in specific research fields such as hydrogen infrastructure, indicating their relative competitiveness.

Voter Heuristics and Group Politics in Global Focus

In this chapter I summarize and extend the argument that many people use ethnic and regional heuristics to make inferences about their own future incomes. That, in turn, leads them to think about redistribution differently depending on their ethnic or regional group’s income. I argue that understanding politics requires understanding groups and how people relate to them. I highlight the role of institutions and political actors, and raise the possibility of a progressive’s dilemma in which highlighting ethnic or regional inequality may cause a backlash against redistribution among richer groups. I close by highlighting some paths for future research.