A Rethink on Measuring Health Inequalities Using the Gini Coefficient

Objective- We show that a standardized Gini coefficient that takes into account the feasible range of health inequality for a given health attribute is a better instrument than the normal Gini coefficient for quantifying inter-individual health inequality. Methods- The standardized Gini coefficient is equal to the normal Gini coefficient divided by the maximal attainable Gini coefficient, which is computed based on the maximal level of a health attribute an individual could achieve. Both the old and new coefficients are used to estimate the lifespan inequality of 185 countries for year 1990, 2000 and 2006, respectively. The results are then compared both across countries and over time. Findings- Firstly, the standardized Gini coefficient can still be related to the Lorenz curve. Secondly, changes in standardized Gini coefficients can be decomposed into respectively the change in the distribution of health outcomes and the change in the average health outcomes. Thirdly, the standardized Gini coefficient provides richer information and often gives different conclusions regarding health inequality in individual countries as well as country ranking, as compared to the normal Gini coefficient. Conclusion- Accounting for the maximal level of health attribute an individual could achieve is important when measuring health inequality. The proposed standardized Gini coefficient can provide more accurate information regarding the actual level of health inequality in a society than the normal Gini coefficient

Gini coefficient as a life table function

This paper presents a toolkit for measuring and analyzing inter-individual inequality in length of life by Gini coefficient. Gini coefficient and four other inequality measures are defined on the length-of-life distribution. Properties of these measures and their empirical testing on mortality data suggest a possibility for different judgements about the direction of changes in the degree of inequality by using different measures. A new computational procedure for the estimation of Gini coefficient from life tables is developed and tested on about four hundred real life tables. The estimates of Gini coefficient are precise enough even for abridged life tables with the final age group of 85+. New formulae have been developed for the decomposition of differences between Gini coefficients by age and cause of death. A new method for decomposition of age-components into effects of mortality and composition of population by group is developed. Temporal changes in the effects of elimination of causes of death on Gini coefficient are analyzed. Numerous empirical examples show: Lorenz curves for Sweden, Russia and Bangladesh in 1995, proportional changes in Gini coefficient and four other measures of inequality for the USA in 1950-1995 and for Russia in 1959-2000. Further shown are errors of estimates of Gini coefficient when computed from various types of mortality data of France, Japan, Sweden and the USA in 1900-95, decompositions of the USA-UK difference in life expectancies and Gini coefficients by age and cause of death in 1997. As well, effects of elimination of major causes of death in the UK in 1951-96 on Gini coefficient, age-specific effects of mortality and educational composition of the Russian population on changes in life expectancy and Gini coefficient between 1979 and 1989. Illustrated as well are variations in life expectancy and Gini coefficient across 32 countries in 1996-1999 and associated changes in life expectancy and Gini coefficient in Japan, Russia, Spain, the USA, and the UK in 1950-1999. Variations in Gini coefficient, with time and across countries, are driven by historical compression of mortality, but also by varying health and social patterns.inequality, life expectancy, mortality, variability

Inequality and Migration: A Behavioral Link

We provide an analytical-behavioral explanation for the observed positive relationship between income inequality, as measured by the Gini coefficient, and the incentive to migrate. We show that a higher total relative deprivation of a population leads to a stronger incentive to engage in migration for a given level of a population’s income; that total relative deprivation is positively related to the Gini coefficient; and that, consequently, the Gini coefficient and migration are positively correlated, holding the population’s income constant.Income inequality, Relative deprivation, The Gini coefficient, The incentive to migrate

The Gini Coefficient Reveals More

We revisit the well-known decomposition of the Gini coefficient into betweengroups, within-groups and overlap terms in the context of two groups in which the incomes in one group may be scaled and that group’s population weight modified. In this more general setting than usual, we focus on the properties of the overlap term, proving inter alia that overlap unambiguously reduces as a result of a within-group progressive transfer, and is increased by scaling up the incomes in the group with the lower mean, reaching a maximum when the two means become the same. In the case of a socially heterogeneous population and equivalized incomes, the effect on the Gini overlap of changing the income unit is determined, along with that of adjusting the equivalence scale deflator in case the income unit is the equivalent adult (such adjustment simultaneously changing the weighting of income units).

Globalization and Economic Inequality in the Short and Long Run: The Case of South Korea 1975-1995

We have analyzed the determinants of the Gini coefficient for income and expenditure. In both cases, we do not find support for the Kuznets inverted-U hypothesis. From economic globalization viewpoint, the opening of goods markets reduces income inequality both in the short run (the Gini coefficient for income) and in the long run (the Gini coefficient for expenditure). On the other hand, the opening of capital markets increases income inequality both in the short and long run, but the latter is not statistically significant. These results suggest that the effect of economic globalization has two routes and two different speeds to affect income inequality.Globalization, Economic inequality, Gini coefficient, South Korea

DEFINING POVERTY LINES AS A FRACTION OF CENTRAL TENDENCY

We show under lognormality that, when the Gini coefficient is stable over time, defining the poverty line as a fraction of a central tendency of the living standard distribution restricts the evolution of the poverty measures to be stable. That is, poverty does not change if the Gini coefficient does not change. Moreover, when the Gini coefficient slightly changes, most of the poverty change can be considered a change in inequality. Then, the consequences of using different poverty lines are analysed. Thus, important features in studies of poverty change based on these lines may result from methodological choices rather than from economic mechanisms.Measurement and Analysis of Poverty, Income Distribution, Personal Income Distribution