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This paper examines the impact of residents’ human capital investment inequality on the urban–rural income gap, using China’s provincial panel data from 1997 to 2013. The results show that, at the national level as well as at the regional level, residents’ overall human capital investment inequality has a positive significant impact on the urban–rural income gap. In addition, the impact of overall human capital investment inequality increased monotonically from the eastern region inward to the western region. In terms of the relative impact of each component of human capital investment inequality on the urban–rural income gap, migration investment inequality appears to have the greatest impact at the national level, whereas health investment inequality has the greatest impact on the urban–rural income gap in the eastern region, and education investment inequality exhibits the greatest impact in the central and western regions. We also investigate the impact of human capital investment inequality on the urban–rural income gap over different periods. The results show that residents’ overall human capital investment inequality had a positive impact on the urban–rural income gap in the period 1997–2008, but the impact rapidly shrunk in 2009–2013. Furthermore, the impact of residents’ health investment inequality on the urban–rural income gap shows a downward trend, and the impact of residents’ education investment inequality trended slightly upward from 1997 to 2008, and then rapidly shrunk in 2009–2013. Finally, the impact of residents’ migration investment inequality was only significant in 1997–2002.

In the United States, there is little difference in annual income inequality and income mobility between the rural and urban sectors of the economy. This forms a sharp contrast with China where income inequality is greater and income mobility lower among rural households than among urban households. When incomes are averaged over three years and when adjustments are made for the size and composition of households, income inequality among all households differs little between China and the United States in the 1990s. Moreover when pooling rural households and urban households and when measuring annual income inequality and income mobility of the pooled households, the mobility of incomes of households in the United States differs little from that in China. Social welfare functions are posited that allow for a trade-off between increases in income and increases in income inequality. These suggest strong increases in well-being for urban households in China. The corresponding changes in rural China and in the United States are smaller. Four sets of data on households are drawn on to document these findings.

To explore income inequality in urban China, this paper investigates disparities between- and within-urban locals and rural migrants from 2002 to 2013, using three waves of the China Household Income Project (CHIP) data. While the existing literature concentrates on the wage disparity between these two groups, our results show that the Gini among the migrants increased by 17.86% between 2007 and 2013 and that among the locals increased by 15.54% from 2002 to 2007. The urban–migrant average income gap decreased during the whole period mainly due to higher growth in migrants’ average income. Estimates based on Mincerian earnings functions for both groups reveal the significant role of the education, occupation and type of contract in determining the within-group inequality. In addition, using a recentred influence function (RIF), we observe that short-term and other types of contracts, duration of the job, in-system ownership, marriage and skill have inequality-enhancing effects for migrants. The variation of skills has a larger impact on the income disparity among migrants than on that among urban locals. The RIF-based Blinder–Oaxaca decomposition of the mean difference of incomes shows that labour market discrimination between the two groups is not significant; however, both pure explained and unexplained differences are significant when applying the RIF decomposition to the variance of the logarithms of incomes. While the type of contract significantly reduces the pure explained difference between migrants and urban locals, occupation has a positive impact on this difference between these two groups. The heterogenity analysis shows that the factors influencing incomes in these two groups are different. We recommend labour market intervention to reduce unreasonable occupational and sectoral disparities, especially in the net inflow provinces, to mitigate urban inequality in China effectively.

Wellbeing evaluation using ordered categorical response data is hazardous given the scale dependent nature of most measures of wellbeing and inequality. Here, scale independent instruments for measuring levels of wellbeing and inequalities between groups in multidimensional ordered categorical environments are introduced and applied in a study of health and consumption wellbeing and the aging process in twenty‐first century China. Urban/rural location, gender, age and the availability of welfare support were considered circumstances in what is in essence a study of equality of opportunity in the acquisition of health and consumption wellbeing in Chinas’ aging population. Older populations are found to experience diminished and increasingly diverse wellbeing outcomes that are, to some extent, ameliorated by welfare support.

Most poverty research has explored monetary poverty. This chapter presents and analyzes the global multidimensional poverty index (MPI) estimations for China. Using China Family Panel Studies (CFPS), we find China’s global MPI was 0.035 in 2010 and decreased significantly to 0.017 in 2014. The dimensional composition of MPI suggests that nutrition, education, safe drinking water, and cooking fuel contribute most to overall non-monetary poverty in China. Such analysis is also applied to subgroups, including geographic areas (rural/urban, east/central/west, provinces), as well as social characteristics such as gender of the household heads, age, education level, marital status, household size, migration status, ethnicity, and religion. We find the level and composition of poverty differs significantly across certain subgroups. We also find high levels of mismatch between monetary and multidimensional poverty at the household level, which highlights the importance of using both complementary measures to track progress in eradicating poverty.

This chapter uses the Ghana Living Standards Survey (GLSS) 7 datasets to investigate and examine the effect of rural non-farm diversification and its implications on agricultural (tree-crop) farming sector inequalities and sustainable development in Ghana. Applying a Gini-decomposition method and/or technique within a quantitative approach, the study outcome indicates the average non-farm income thus, increased income inequality among tree-crop smallholder rural livelihoods and households. Income diversification by farm households has gained the attention of governments, policy makers, and researchers because of its commonness and contribution to socio-economic development especially in developing countries. Aggregationally, non-farm self-employment reduced income inequality, and non-farm wage employment income led to an increase in income inequality. Increased rate of educational enrollment and achievement is the most important variable of non-farm income inequality. Government effort at expanding tree-crop acreages and improve yields have to degree achieved its intended policy implementation, increased rate of educational achievement could undermine the socio-economic policy cohesion and sustainable development of rural livelihood, communities, and national economy. Tree crop policies should take account of the spatial distribution of tree-crop commodity production and in particular, the implication and effect of rural non-farm diversification on agricultural sector inequalities.

This study investigated four different economic level areas of China (Shanghai, Shandong, Shaanxi, and Guizhou) to analyze the eastern and western urban and rural media service status at different development stages. This set of data comes from the comparison of regional urban and rural areas and indicates the various aspects of differences in the survey area, including the media use habits, media resources, media consumer demand, evaluation of media services, the role of media in public life, public knowledge level, and so on. On analyzing data comprehensively, one thing can be found that there is a positive correlation between the public media contact degree and the public knowledge level. The media plays an extremely important role in public life and regional public knowledge gap between urban and rural areas exists. Furthermore, this gap is positively correlated to the media resources and media exposure. The trend of media using on mobile phone and computer in urban areas increases significantly greater than in rural areas. Then, how to narrow the urban–rural and regional public knowledge gap and reduce the negative impact of the digital divide will be an important urgent task.

This chapter examines the trend in school enrollment and transitions to senior high school and to college in China for selected young cohorts since the 1990s, based on the analyses of the sample data from population censuses in 1990 and 2000 and the mini-census in 2005. We pay particular attention to educational inequality based on gender and the household registration system (hukou) in the context of educational expansion. Results show a substantial increase in educational opportunities over time at all levels. In particular, women have gained relatively more; gender inequality has decreased over time, and the gap in college enrollments was even reversed to favor women in 2005. However, rural–urban inequality was enlarged in the 1990s. The educational expansion has mainly benefited females and urban residents.

Citizens are substantial stakeholders in every e-government system, thus their willingness to use and ability to access the system are critical. Unequal access and information and communication technology usage, which is known as digital divide, however has been identified as one of the major obstacles to the implementation of e-government system. As digital divide inhibits citizen’s acceptance to e-government, it should be overcome despite the lack of deep theoretical understanding on this issue. This research aimed to investigate the digital divide and its direct impact on e-government system success of local governments in Indonesia as well as indirect impact through the mediation role of trust. In order to get a comprehensive understanding of digital divide, this study introduced a new type of digital divide, the innovativeness divide.

The research problems were approached by applying two-stage sequential mixed method research approach comprising of both qualitative and quantitative studies. In the first phase, an initial research model was proposed based on a literature review. Semi-structured interview with 12 users of e-government systems was then conducted to explore and enhance this initial research model. Data collected in this phase were analyzed with a two-stage content analysis approach and the initial model was then amended based on the findings. As a result, a comprehensive research model with 16 hypotheses was proposed for examination in the second phase.

In the second phase, quantitative method was applied. A questionnaire was developed based on findings in the first phase. A pilot study was conducted to refine the questionnaire, which was then distributed in a national survey resulting in 237 useable responses. Data collected in this phase were analyzed using Partial Least Square based Structural Equation Modeling.

The results of quantitative analysis confirmed 13 hypotheses. All direct influences of the variables of digital divide on e-government system success were supported. The mediating effects of trust in e-government in the relationship between capability divide and e-government system success as well as in the relationship between innovativeness divide and e-government system success were supported, but was rejected in the relationship between access divide and e-government system success. Furthermore, the results supported the moderating effects of demographic variables of age, residential place, and education.

This research has both theoretical and practical contributions. The study contributes to the developments of literature on digital divide and e-government by providing a more comprehensive framework, and also to the implementation of e-government by local governments and the improvement of e-government Readiness Index of Indonesia.