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Limited research exists on the role of information access as a key success factor for rural entrepreneurs. The purpose of this study is to examine the importance of information access, among other inequality forms, in shaping entrepreneurial outcomes.

The authors used a qualitative, inductive research methodology. They conducted interviews with rural entrepreneurs and gained insights into the role of information access and basic tangible resources in shaping their ventures.

The authors identified two critical factors that impact rural entrepreneurs: inequalities in access to information and basic tangible resources. They found that inequalities in rural entrepreneurship are often interrelated, rather than isolated. The authors demonstrated that the relationship between entrepreneurship and inequality is not solely characterized by a positive or negative correlation but is a dynamic interplay where certain inequality forms may create barriers to opportunities for some individuals while creating opportunities for others.

The authors uncovered key barriers in rural entrepreneurship and constructed a roadmap to effectively address these challenges, providing valuable insights to policymakers and support initiatives and enabling the target of high-impact resources. This research supports efforts to provide rural entrepreneurs with equal opportunities to grow and succeed.

This research significantly contributes to the field by examining the complexities of entrepreneurship in emerging economies, with a particular focus on rural areas. The authors introduced a comprehensive conceptual model linking inequality and entrepreneurship, explored the challenges faced by rural entrepreneurs and offered strategic policy recommendations for development initiatives.

This paper aims to illustrate the trends of income growth and income inequality and examines the dynamics and determinants of income mobility in rural China from 2003 to 2006.

The authors decomposed the Gini coefficient by different sources and analyzed income mobility using the method of income transition matrix. The authors then estimated the effects of demographic variables, labor migration, and other household characteristics on income growth using a dynamic panel data model.

The study obtained important findings on income mobility and income inequality in rural China. First, annual income inequality in rural China was smoothed during this period after a decline from 2003, with the largest contribution from the income of migration work. Second, income mobility remained rather stable and relatively high, with higher mobility in the interior provinces than in the coastal provinces. Third, the income levels of the poor and the wealthy households converged during this period after controlling other factors. Fourth, income growth depends on in the households' demographic composition, their human capital accumulation, and their chances of getting migration jobs.

The sound econometric methods applied to the most current rural household survey data provide important contributions to the literature of income inequality and income mobility in China.

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.

Since 1978, China has made tremendous economic achievements through industrial upgrading. However, these achievements are accompanied by an expanding income gap between rural and urban areas. The purpose of this paper is to examine the relationship between industrial structure and urban–rural income inequality in China.

Using the fixed-effects model and provincial data for the period 1985–2019, this paper estimates a linear relationship between industrial structure and urban–rural income inequality. By decomposing total income inequality into four components, the paper then analyzes how industrial structure affects each component.

The results show that industrial structure imbalance and industrial upgrading are positively associated with urban–rural income inequality. The positive effect of industrial imbalance mainly comes from widening the wage gap, while that of industrial upgrading mainly comes from aggravating business income inequality and property income inequality. Moreover, industrial balance and upgrading are conducive to increasing the share of wage income at the cost of property income.

By progressively examining the total inequality and the inequality of income components, this paper provides a better understanding of how industrial structure affects urban and rural income inequality. The findings of this study highlight the “inequality cost” associated with industrial structure adjustment, which provide policy-related insights on the balance development of urban and rural areas.

Fast growth in China has led to significant improvement in people's living standards and average income. However, it has also brought about a huge rise in inequality. The purpose of this paper is to analyse regional and rural‐urban inequality using a few income and consumption indicators.

Data are collected from official statistical sources for all the Chinese provinces over 1978‐1995. Both parametric and non‐parametric methods are used to study the inequality between regions and between the rural and urban sub‐populations. The parametric approach is to test whether per capita incomes among provinces converged over time. The non‐parametric approach is the calculation and decomposition of the Gini coefficient by population sub‐group and income source.

The results show no evidence of growth convergence in per capita GDP, income and expenditure across provinces, but clear evidence of divergence in per capita rural (and urban) incomes and total expenditures. Three‐quarters of inter‐provincial income inequality are explained by inter‐rural/urban inequality. Inter‐provincial inequality explains more than half of rural inequality and less than half of urban inequality in most years.

This paper uses one of the most complicated datasets for the Chinese regions. It studies inequality using different economic indicators. It considers the different dimensions of inequality in China using two different approaches. The results are important for regional development policies.

The purpose of this paper is to investigate the impact of financial development on the rural‐urban income inequality in India using annual data from 1965 to 2008.

The Ng‐Perron unit root test is utilised to check for the order of integration of the variables. The long run relation is examined by implementing the ARDL bounds testing approach to cointegration.

The results confirm a relation among the variables. Evidence suggest that financial development, economic growth and consumer prices aggravate rural‐urban income inequality in the long run.

The present study offers fresh insights to policy makers on crafting appropriate policies that reduce rural‐urban income inequality in India.

The contribution of this paper is lies in extending the literature in the context of India towards an extensively researched area of rural‐urban divide but in time series framework and utilization of a better approach of time series approach, i.e. ARDL. Specifically, to the best of the authors' knowledge, this is the first empirical study to test poverty‐finance nexus using the basic principles of the GJ hypothesis and provide evidence of short‐ and long‐run dynamics on the postulated relation for India.

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.

The purpose of this paper is to apply a poverty level decomposition approach to decompose the poverty by income sources and investigate the impact of government transfers on income inequality and rural poverty.

This paper uses the decomposition method of inequality and the decomposition method of poverty level by resource endowments to decompose the overall inequality and the overall poverty by income sources.

It is found that unequal income distribution rather than income endowments is mainly responsible for the existence of poverty. Government transfers and relief income, aiming at the poor, help alleviate inequality and poverty, but are not targeting the poorest. Unequal distribution of production subsidies actually lead to higher poverty incidence.

This paper has revealed that the poverty issue cannot be resolved with economic development alone if the issues including the inequality in income distribution are not solved. It is important to make government transfers/subsidies pro-poor.

A poverty level decomposition approach is first used to decompose the poverty by income sources in China.

The purpose of this paper is to identify the structure of household income and examine the effects of non-farm incomes on the income distribution of farm households in a relatively developed rural area of the Malaysian rice bowl.

The non-farm incomes were disaggregated into different components to determine the contribution of each income source to total household income and overall inequality. The income distribution and decomposition was examined using the Gini decomposition method.

It was found that almost 71 percent of the households in the sample had at least one source of non-farm income. On average, non-farm incomes contributed about 33 percent to total household income. Non-farm wage employment was the dominant source of non-farm income, accounting for almost 26 percent of overall household income. The farm incomes, especially the paddy incomes were found to be the inequality-decreasing income source. The study also confirmed the proposition that the non-farm incomes were the inequality-increasing income source as they contributed up to 35 percent of the overall income inequality.

Previous studies have found that non-farm incomes have different effects on income inequality of rural communities, especially those in the rice granary areas situated in less developed states of Malaysia, where poverty is still a problem. This study is significant because it identifies the effect of certain incomes on the overall income inequality among farm households in the granary areas located in a relatively developed rural area. The studied areas are characterized by an intensive paddy production and a rapid development in business and industrial activities, and hence, providing non-farm employment opportunities to the rural farmers. Therefore, this study shows the income structure and how farm and non-farm incomes affect the overall income distribution of the paddy farmers.