Inequality Decomposition Analysis and the Gini Coefficient Revisited

Lambert, Peter J.; Aronson, J. Richard

doi:10.2307/2234247

Cited by 363 publications

(181 citation statements)

References 14 publications

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“…This decomposition can be used to study the contribution of between-group differences to the total level of lifespan variation. The Gini coefficient G can also be decomposed in this way, but contains an overlap term (Lambert and Aronson 1993). The M LD index can additionally be additively decomposed over time, to account for compositional change to the between-and within-group variation components (Mookherjee and Shorrocks 1982).…”

Section: Indices Of Lifespan Variationmentioning

confidence: 99%

Perturbation Analysis of Indices of Lifespan Variability

2013

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A number of indices exist to calculate lifespan variation, each with different underlying properties. Here we present new formulae for the response of seven of these indices to changes in the underlying mortality schedule (life disparity, the Gini coefficient, the standard deviation, the variance, Theil's index, the mean logarithmic deviation, and the inter-quartile range). We derive each of these indices from an absorbing Markov chain formulation of the life table, and use matrix calculus to obtain the sensitivity and the elasticity (i.e., the proportional sensitivity) to changes in age-specific mortality. Using empirical French and Russian male data we compare the underlying sensitivities to mortality change under different mortality regimes in order to test under which conditions the indices might differ in their conclusions about the magnitude of lifespan variation. Finally, we demonstrate how the sensitivities can be used to decompose temporal changes in the indices into contributions of age-specific mortality changes. The result is an easily computable method for calculating the properties of this important class of longevity indices.

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Section: Indices Of Lifespan Variationmentioning

confidence: 99%

Perturbation Analysis of Indices of Lifespan Variability

2013

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“…While one method cannot be claimed to be superior to others (Shorrocks 1982), the covariance methods developed later require, implicitly or explicitly, special assumptions on population grouping. See Fei et al (1978), Pyatt et al (1980), Lerman and Yitzaki (1985) and Lambert and Aronson (1993). Such assumptions, however, are not needed for deriving Kakwani's results;see equation (4).…”

Section: Decomposing the Gini Coefficient And Its Changementioning

confidence: 99%

Changes in regional inequality in rural China: decomposing the Gini index by income sources

Wan

2001

Aus J Agri & Res Econ

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A new method is proposed to decompose inequality changes as measured by the Gini index 1 into structural e¡ects, real inequality e¡ects and interactive e¡ects. Application of the method to updated Chinese data reveals that structural e¡ects represent the driving force underlying the increasing trend in regional income inequality in rural China. Policy implications are explored. In addition to these contributions, considerable e¡orts are made to construct the income data used in the article. Pitfalls in measuring income inequality in rural China are discussed.

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“…Similar methods applied to other indices require the introduction of a vaguely defined residual or "interaction" term in order to maintain the decomposition identity. The best known example is the subgroup decomposition of the Gini coefficient, which has exercised the minds of many authors including Pyatt (1976) and Lambert and Aronson (1993).…”

Section: Introductionmentioning

confidence: 99%