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Though Indian economy since 1980s has expanded very rapidly, yet the benefits of growth remain very unequally distributed. The purpose of this paper is to provide new evidence about the shape, intensity and decomposition of inequality change between 2005 and 2012. The authors find that Gini, as a measure of income inequality, has increased irrespective of geographic regions.

Based on a recent distribution analysis tool, “ABG,” the paper focuses on local inequality, and summarizes the shape of inequality in terms of three inequality parameters (α, β and γ) to examine how the income distributions have changed over time. Here, the central coefficient (α) measures inequality at the median level, with adjustment parameters at the top (β) and bottom (γ).

The results reveal that at the middle of distribution (α), there is almost the same inequality in both the periods, but the coefficients on the curvature parameters β and γ show that there is increasing inequality in the subsequent period. Finally, an analysis of decomposition of inequality change suggests that though income growth was progressive, however, this equalizing effect was more than offset by the disequalizing effect of income reranking.

This paper shows how it can be possible both for “the poor” to fare badly relatively to “the rich” and for income growth to be pro-poor.

This paper stresses the significance of inequality reduction.

Inequality reduction is very much imperative in ending poverty and boosting shared prosperity.

Perhaps, this research work is first of its kind to examine the shape and decomposition of change in income inequality in India in recent years.

Globalization is a process of interaction and integration among the countries, their people, their businesses, and their governments. It is a change driven by international trade, implemented by various policies and aided by modern technology. It has impacts on the environment, culture, political systems, economic development and prosperity, and human physical well-being in societies around the world. But there can be some negative impacts as well. One possible outcome of globalization of all sorts can be the income inequalities. Objective of this chapter is to search for any such connection. Gini coefficient, unemployment rate, Below Poverty Line (BPL) is taken to understand the extent of inequalities in different countries. Outcome shows some countries do not show any association between globalization and income inequalities; some do. Therefore, there are some other variables which influence the above relationship. This chapter tries to identify all such background factors. It reveals that factors like level of development, demographic structure, urbanization, adult and tertiary level of education and government expenditure share in higher education play important roles. All these have different magnitudes of impacts on change in income distribution due to the initial process of globalization.

Purpose – Evidence suggests that during the 1990s, many US metropolitan areas saw fundamental changes in the spatial distribution of household income. Following two decades of increasing economic segregation, many metropolitan neighborhoods saw declines in economic segregation, particularly those neighborhoods located within central cities and rural areas. This paper adapts the Spatial Ordering Index proposed by Dawkins (2007b) to explore these trends.

Methodology/Approach – Using US Census data, I calculate economic segregation indices for a sample of 205 US metropolitan areas in 1990 and 2000 and decompose changes in the indices into portions attributable to changes in the spatial distribution of households and portions capturing changes in the spatial distribution of aggregate income. I also examine regional variations in the decompositions.

Findings – The results suggest that changes in the spatial distribution of households and of income each influenced metropolitan economic segregation in different ways during the 1990s. Furthermore, the spatial dynamics of income segregation exhibited significant regional heterogeneity.

Originality/Value of paper – This paper presents a new approach to measuring the dynamics of economic segregation.

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.

Measures of inequality determine the effectiveness of social and economic policies aimed at reducing inequality and to design effective intervention policies. The purpose of this paper is to focus on poverty reduction and welfare improving impacts of reducing income inequality in the case of Fiji. Using Fiji's Household Income and Expenditure Survey 2002‐2003, a comprehensive analysis is used to measure the level of inequality by household income, quintile income distribution, decomposition of inequality by ethnicity and regional groups, and the household income inequality by source of income.

Several statistical techniques have been applied to investigate the degree of inequality in the household income. These include the Gini coefficient, the Nelson ratio, the concentration index and the Atkinson index. An evaluation by ethnicity, regions and household income sources reflects the level of inequality, and concerns for policies and governance.

The results show that urban households, in particular, experience greater inequalities, in both positive and normative terms. The Indo‐Fijian households experience greater income inequalities than the Fijian households. Decomposition results for the separate factor income components also indicate major sources of inequality. These findings clearly establish that Fiji still has a long way to go in reducing the income gaps between the rich and the poor in both rural and urban households.

The paper is a first study that estimates various measures of inequality in the case of Fiji. The implication of the empirical findings suggests that Fiji is unlikely to achieve its Millennium Development Goal of halving poverty rate by 2015 due to the large income differentials by ethnicity and in the urban‐rural areas.

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 paper aims to study the pricing strategies of an online trading platform with indirect network externalities by considering heterogeneous trading behavior in the downstream market and the long tail.

The game theory, optimization and comparative static are used in this research. The equilibria are derived from the game theory, and with them, the authors optimize the platform’s profit function. Comparative static is used to study pricing strategies.

It is found that with heterogeneous trading behavior, the transaction-based model is more profitable than the subscription-based model by reason of the feasibility of “price discrimination”. However, with certain advantages of subscription fees such as avoiding offline transactions, the subscription-based model is better with a concentrated distribution of sellers’ revenues (the Gini coefficient is small). With a lucrative long tail, the platform should set a low price to attract small sellers in the long tail. Besides, if the Gini coefficient is large, the effects of the market entry barrier of sellers on the optimal price in each model may be opposite.

It implies that the choice of revenue models and pricing strategies are influenced by the Gini coefficient or the long tail. The exogenous setting in which buyers can use the platform for free needs further extension.

The authors provide insights on how to choose revenue models and how to price the sellers with the long tail phenomenon.

This paper emphasizes the role of the long tail on pricing strategies and the effect of heterogeneous trading behavior on model selection.

After‐tax income distributions in the UK for a period of 12 years have been used for estimating the coefficient of inequality‐aversion ε implicit in the income distributions, the change in ε during the period, as well as Atkinson's index of inequality corresponding to the different ε. The method used is non‐linear regression analysis.

This study analyses income inequality and distribution patterns among key actors in the cassava value chain. The study also identifies factors that influence profit of key actors in the cassava value chain.

The study was conducted in Oyo State, Nigeria, using primary data from 620 actors, consisting of 400 farmers, 120 processors and 100 traders in the cassava value chain. The Gini coefficient was used to estimate income inequalities within and between actors. Multiple linear regression was applied to identify factors that influence the profit of the actors in the cassava value chain.

The result shows a gender pattern in the participation in the cassava value chain: men dominate in the production, whereas women mostly engage in processing and marketing of processed cassava products. We also find that incomes are unequally distributed among actors, favouring traders and processors more than farmers in the value chain. Women are better off in processing and trading of value-added products than in the raw cassava production. Spatial differences also contribute to income inequality among farmers in the cassava value chain. An increase in farmers and processors’ incomes reduces inequality in the value chain while an increase in traders’ income widens inequality. Age is significantly negatively correlated with actors’ profit at 1%, while educational level significantly increases their profit at 5%. Processors and traders with large households have a higher profit. We also find that farm size, experience and labour input have significant positive effects on farmers’ profit only at 5%. Membership in an association increases farmers and processors’ profit at 1 and 10%, respectively.

The study recommends that agricultural policies that promote agrifood value chains should aim at minimizing income inequality by targeting vulnerable groups, particularly female farmers to achieve sustainable development in rural communities.

Existing studies recognise income inequality in agricultural value chains in sub-Saharan Africa. However, there are few rigorous quantitative studies that address this pressing issue. Our paper fills this knowledge gap and suggests ways to minimise income inequality in the agri-food value chain, using the example of the cassava value chain in Nigeria.