Compare methods

	Health Inequality Gini Decomposition	Oaxaca-Blinder Health Decomposition
Field	Social Epidemiology	Social Epidemiology
Family	Process / pipeline	Regression model
Year of origin	1985	1973
Originator	Robert Lerman & Shlomo Yitzhaki; Adam Wagstaff & Eddy van Doorslaer	Ronald Oaxaca; Alan Blinder (health extension popularized by Fairlie and others)
Type	Inequality-measurement and decomposition pipeline	Regression-based decomposition of a between-group mean gap in a health outcome
Seminal source	Lerman, R. I., & Yitzhaki, S. (1985). Income inequality effects by income source: A new approach and applications to the United States. The Review of Economics and Statistics, 67(1), 151-156.	Oaxaca, R. (1973). Male-Female Wage Differentials in Urban Labor Markets. International Economic Review, 14(3), 693-709.
Aliases	Health Gini Decomposition, Gini Decomposition by Source, Inter-Individual Health Inequality, Total Health Inequality Gini	Blinder-Oaxaca Decomposition for Health Inequalities, Threefold Decomposition of Health Disparities, Detailed Decomposition of Health Gaps, Nonlinear Oaxaca-Blinder for Binary Health Outcomes
Related	4	4
Summary	The Gini coefficient is the most familiar single-number summary of inequality, and applied to a health variable it captures total, inter-individual health inequality — how unequally health is distributed across all people, regardless of their socioeconomic position. Its real analytic power comes from decomposition. Robert Lerman and Shlomo Yitzhaki's 1985 covariance formulation rewrites the Gini as twice the covariance between health and its rank divided by the mean, which makes it decomposable into the contributions of separate sources or components, each weighted by its share, its own Gini, and its Gini correlation with the overall distribution. The same machinery supports a between-versus-within-group split. As Wagstaff and van Doorslaer's review of health-inequality measurement explains, this 'pure' inequality view complements socioeconomic measures like the concentration index: the Gini asks how unequal health is, while the concentration index asks how that inequality is patterned by income or rank.	The Oaxaca-Blinder decomposition partitions the mean difference in a health outcome between two groups into a portion explained by differences in their measured characteristics and a residual, unexplained portion attributed to differences in how those characteristics translate into health. Developed independently by Ronald Oaxaca (1973) and Alan Blinder (1973) to study labor-market wage gaps, the method was imported into social epidemiology to quantify, for example, how much of a Black-White, urban-rural, or rich-poor gap in self-rated health, BMI, hypertension, or mortality is accounted for by differences in socioeconomic exposures versus differences in returns to those exposures. Group-specific regressions are estimated, the gap in fitted means is written as a function of mean covariates and coefficients, and that gap is algebraically split into an explained (composition) component and an unexplained (coefficient) component, each of which can be further decomposed variable by variable.