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This chapter studies trends in income distributions and inequality in the European Union using data from the European Union Statistics on Income and Living Conditions. The author models the income distribution for each country under a Dagum distribution assumption and using maximum likelihood techniques. The author uses parameter estimates to form distributions for regions defined as finite mixtures of the country distributions. Specifically, the author studies the groups of ‘new’ and ‘old’ countries depending on the year they joined the European Union. The author provides formulae and estimates for the regional Gini coefficients and Lorenz curves and their decomposition for all the survey years from 2007 through 2011. The estimates of this study show that the ‘new’ European Union countries have become richer and less unequal over the observed years, while the ‘old’ ones have undergone a slight increase in inequality which is however not significant at conventional levels.

“It should also be noted that the objective of convergence and equal distribution, including across under-performing areas, can hinder efforts to generate growth. Contrariwise, the objective of competitiveness can exacerbate regional and social inequalities, by targeting efforts on zones of excellence where projects achieve greater returns (dynamic major cities, higher levels of general education, the most advanced projects, infrastructures with the heaviest traffic, and so on). If cohesion policy and the Lisbon Strategy come into conflict, it must be borne in mind that the former, for the moment, is founded on a rather more solid legal foundation than the latter” European Commission (2005, p. 9)Adaptation of Cohesion Policy to the Enlarged Europe and the Lisbon and Gothenburg Objectives.

This paper aims to estimate the global income distribution during the nineties using limited information. In a first stage, we obtain national income distributions considering a model with two parameters. In particular, we propose to use the so-called Lamé distributions, which are curved versions of the Sigh-Maddala and Dagum distributions. The main feature of this family is that they represent parsimonious models which can fit income data adequately with just two parameters and whose Lorenz curves are characterized by only one parameter. In a second stage, global and regional distributions are derived from a finite mixture of these families using population shares. We test the validity of the model, comparing it with other two-parameter families. Our estimates of different inequality measures suggest that global inequality presents a decreasing pattern mainly driven by the fall of the differences across countries during the course of the study period that offsets the increase in disparities within countries.

Brazil’s regional inequality is an important topic due to the large and persistent differences in development between states and the high levels of inequality in the country. These variations in development can potentially render survey data inaccurate since the significance of capital income varies across the states. Besides, previous studies incorporating tax and national accounts data globally have mainly focused on measuring the income distribution at the country-level. This approach can limit the understanding of inequality, especially when considering large countries such as Brazil.

The methodology used to construct these estimates follows the guidelines of the Distributional National Accounts, whose core goal is to provide income distribution measures consistent with macroeconomic aggregates and harmonized across countries and time. The procedure has three main steps: first, it corrects the survey’s underrepresentation of top incomes using tax data. Then, it accounts for national income items not included in the survey or tax data, such as imputed rents and undistributed profits. Finally, it ensures that all components match the national income.

Compared to survey-based estimations, the results reveal a new angle on the state-level inequality. This study indicates that Amazonas, Rio de Janeiro and São Paulo have a more concentrated income distribution. The top 1\% of earners in these states receives around 28\% of total pre-tax income, while the top 10\% receive nearly 60\%. On the other end, Amapá (AP), Acre (AC), Rondônia (RO) and Santa Catarina (SC) are the states where the income distribution is less concentrated. There were no significant changes in the income distribution across the states during the period analyzed.

This study combines survey, tax and national accounts data to construct new estimates of Brazil’s state-level income distribution from 2006 to 2019. Previous results only considered income captured in surveys, which usually misses a significant part of capital incomes. This limitation may bias comparisons as capital income has different importance across the states. The new estimates represent the income of top groups more accurately, account for the entire national income and enable to compare regional inequality levels consistently with other countries.

EU countries, including those in Central and Eastern Europe, seem to have increasingly similar economies, allowing for the study of real convergence as a process of equalising income levels (measured by GDP per capita). Studies of income convergence in the European Union also have a regional dimension and often focus on convergence at the NUTS2 or NUTS3 regional level. The level of development and income in Polish regions differ significantly. The regional policy implemented at the national and EU level focuses on reducing these differences.

The main aim of the chapter is to analyse the income convergence process among regions in Poland and verify the effectiveness of regional policy implemented at the national and EU level.

The study uses Barro type regression for panel data, log t convergence test, and club clustering algorithm introduced by Phillips and Sul to identify patterns of club convergence in Polish regions. The data used for the study is the Local Data Bank provided by Statistics Poland, which includes gross domestic product per capita at the NUTS-3 level for 73 Polish regions over the period of 2000–2020.

The results of the study indicate a very weak convergence process for all Polish NUTS-3 regions and suggest a club convergence. The club convergence is characterised by regions with similar income levels clustering together. The regional distribution of clubs is similar to the regional distribution of income. The study's findings provide important insights into the effectiveness of regional policy in Poland and suggest that policymakers need to focus on policies that promote catch-up growth in less developed regions. The study also highlights the importance of supporting the most developed regions in the country as they can play a crucial role in driving the country's economic growth and prosperity.

The purpose of this paper is to study the dynamics of the distribution of per capita income of Indian states in the post‐reform period, in order to identify trends towards convergence‐club formation, polarization or stratification during this period.

The authors adopt the “distribution dynamics” framework that involves estimating kernel density functions, stochastic kernels and ergodic distributions in order to identify these trends.

The results show that there is polarization in India in the post‐reform period and this is due to the contrary growth dynamics of the middle‐income states resulting in the “vanishing middle” of the distribution.

This is the first study that highlights the contrary growth dynamics among the middle‐income states as the driving force behind the polarization of Indian states in the post‐reform period.

Does the standard of living vary from region to region in Portugal and are spatial units in Portugal converging in income? We observe spatial error dependence between municipalities and estimate spatial econometric models to test convergence. For conditional convergence we conclude that primary sector employment, activity rate, and percentage of active population with higher education are important to distinguish the “steady state” of the regional economies, reflecting the labor market at regional level.

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.

Dominance techniques are used to analyze and rank inequality, welfare, and poverty across regions in Thailand in the 1990s. Inference-based dominance methods are applied to consumption expenditure microdata from the Household Socio-Economic Surveys (SES) of 1992, 1994, 1996, 1998 and 2000. Attention is focused on the period immediately before and after the economic contraction of 1996–1997. Lorenz dominance is employed to assess inequality, while first-order Engel food share dominance is applied to rank welfare across time and among regions. Poverty is evaluated by comparing truncated food-share quantile functions. The evidence reveals that the economic crisis in 1997 seems to affect inequality in Bangkok (the richest region) more than the Northeast (the poorest region), and most dramatic changes occur in the North and South. Welfare in Bangkok is unambiguously higher than in other regions before and after economic contraction. In fact, the great economic contraction changes the rankings of economic well-being and poverty only in the North, South, and Northeast.

The purpose of this study is to investigate the relationship between government and Balinese society in tax decentralization through budgeting seem to insignificantly improve the welfare of Balinese society.

This research was conducted in Bali Province involving eight regencies and one city. The data used in this study were secondary data, derived from relevant institutions or from websites through internet browsing and other documentations in the form of official reports/publications, such as regional budget, accountability reports, regional regulations and documents on budget and development of the regional economy. The present research used the partial least squares analysis technique.

Fiscal decentralization does not necessarily lead to better budget management. The success of fiscal decentralization can be found in the quality of the regional budget and the quality of budget management. The allocation of the regional budget for public service improvement and the development of infrastructure will increase the economic capacity of the regions. Improvement in regional economic capacity encourages the improvement of community welfare.

This income inequality points to the issue of fiscal capacity. The development of the financial role of district/city regions in the Province of Bali remains at a level gap with the development level of community welfare. During this period, the financial role of the government as estimated from the ratio of the national budget to the regional budget is higher than that of the society development. The acceleration role of the government is not proportional to the development of Human Development Index outcomes.