Inequality and Welfare Evaluation of Heterogeneous Income Distributions

This paper establishes the principles which should govern the welfare and inequality analysis of heterogeneous income distributions. Two basic criteria?the ?equity preference? condition and the ?compensation principle??are shown to be fundamentally incompatible. The paper favours the latter, thereby vindicating the traditional method of dealing with heterogeneous samples. However, inequality and welfare comparisons will usually be well defined only if equivalent incomes are obtained using constant scale factors; and researchers will need to distinguish clearly between inequality of nominal incomes and inequality of living standards. Furthermore, household observations must always be weighted according to family size.income distribution, inequality, living standards, needs

Spatial Decomposition of Inequality

inequality, index, decomposition

Ungrouping Income Distributions: Synthesising Samples for Inequality and Poverty Analysis

We describe a new method of facilitating inequality and poverty analysis of grouped distributional data by allowing individual income observations to be reconstructed from any feasible grouping pattern. In contrast to earlier methods, our procedure ensures that the characteristics of the synthetic sample exactly match the reported values. The performance of the algorithm is evaluated first by using household survey records to compare true income observations with their synthetic counterparts, then by comparing the true and generated values of the Gini coefficient and other inequality indices. The results indicate that the new technique is capable of reproducing individual data from grouped statistics with a high degree of accuracy.grouped data, income distribution, inequality, poverty

A Decomposition Analysis of Regional Poverty in Russia

poverty, Russia, regions, decomposition

Ungrouping income distributions: Synthesising samples for inequality and poverty analysis

We describe a new method of facilitating inequality and poverty analysis of grouped distributional data by allowing individual income observations to be reconstructed from any feasible grouping pattern. In contrast to earlier methods, our procedure ensures that the characteristics of the synthetic sample exactly match the reported values. The performance of the algorithm is evaluated first by using household survey records to compare true income observations with their synthetic counterparts, then by comparing the true and generated values of the Gini coefficient and other inequality indices. The results indicate that the new technique is capable of reproducing individual data from grouped statistics with a high degree of accuracy

A decomposition analysis of regional poverty in Russia

This paper applies a new decomposition technique to the study of variations in poverty across the regions of Russia. The procedure, which is based on the Shapley value in cooperative game theory, allows the deviation in regional poverty levels from the all- Russia average to be attributed to three proximate sources; mean income per capita, inequality, and local prices. Contrary to expectation, regional poverty variations turn out to be due more to differences in inequality across regions than to differences in real income per capita. However, when real income per capita is split into nominal income and price components, differences in nominal incomes emerge as more important than either inequality or price effects for the majority of regions

Spatial decomposition of inequality

This paper reviews the theory and application of decomposition techniques in the context of spatial inequality. It establishes some new theoretical results with potentially wide applicability, and examines empirical evidence drawn from a large number of countries

The World Distribution of Household Wealth

There has been much recent research on the world distribution of income, but also growing recognition of the importance of other contributions to well-being, including those of household wealth. Wealth is important in providing security and opportunity, particularly in poorer countries that lack full social safety nets and adequate facilities for borrowing and lending. We find, however, that it is precisely in the latter countries where household wealth is the lowest, both in absolute and relative terms. Globally, wealth is more concentrated than income both on an individual and national basis. Roughly 30 per cent of world wealth is found in each of North America, Europe, and the rich Asian-Pacific countries. These areas account for virtually all of the world?s top 1 per cent of wealth holders. On an official exchange rate basis India accounts for about a quarter of the adults in the bottom three global wealth deciles while China provides about a third of those in the fourth to eighth deciles. If current growth trends continue, India, China and the transition countries will move up in the global distribution, and the lower deciles will be increasingly dominated by countries in Africa, Latin American and poor parts of the Asian-Pacific region. Thus wealth may continue to be lowest in areas where it is needed the most.wealth, net worth, personal assets, wealth inequality, households, balance sheets, portfolios

Estimating the level and distribution of global wealth, 2000-14

Davies et al. (2008, 2011) provided the first estimates of the global distribution of wealth, using 2000 as the benchmark year. These estimates have been revised and updated since 2010, and the purpose of this paper is to explain the ways in which the estimation methodology has evolved and improved in recent years. Further, the paper summarizes lessons learned about trends in the level and distribution of global wealth for the period 2000-14. Finally, the paper discusses the results in the context of the discourse provoked by Piketty (2014)