방법 비교

	Inequality-adjusted HDI	Multidimensional Deprivation Analysis
분야	Development Studies	Development Studies
계열	Process / pipeline	Process / pipeline
기원 연도	2010	2003
창시자	Sabina Alkire & James Foster; UNDP Human Development Report Office	Anthony B. Atkinson; Sabina Alkire & James Foster
유형	Distribution-sensitive composite development index	Family of multidimensional deprivation measurement approaches
원전	Alkire, S., & Foster, J. (2010). Designing the Inequality-Adjusted Human Development Index (IHDI). OPHI Working Paper 37 / Human Development Research Paper 2010/28. UNDP Human Development Report Office, New York.	Atkinson, A. B. (2003). Multidimensional Deprivation: Contrasting Social Welfare and Counting Approaches. Journal of Economic Inequality, 1(1), 51-65.
별칭	IHDI, Inequality-adjusted Human Development Index, Atkinson-adjusted HDI, Distribution-sensitive HDI	Counting Approach to Deprivation, Deprivation Dashboard Analysis, Multidimensional Deprivation Measurement, Overlapping Deprivation Analysis
관련	4	4
요약	The Inequality-adjusted Human Development Index (IHDI) extends the Human Development Index by accounting for how achievements in health, education, and income are distributed across a population, not just their averages. Designed by Sabina Alkire and James Foster for the UNDP and introduced in the 2010 Human Development Report, it discounts each HDI dimension by the inequality observed within it, using an Atkinson-class inequality measure. When there is no inequality the IHDI equals the HDI; as inequality rises the IHDI falls below it, and the percentage gap — the 'loss' — measures how much human development is eroded by being unequally shared.	Multidimensional deprivation analysis is the broad family of methods for measuring and describing disadvantage across several dimensions at once — health, education, living standards, work, and more — rather than through income alone. It spans the counting approach championed by Anthony Atkinson and formalized by Sabina Alkire and James Foster, the dashboard tradition of reporting deprivation indicators side by side, fuzzy-set treatments that soften sharp thresholds, and overlap analysis that asks whether the same people are deprived in many dimensions. The unifying questions are how to decide who is deprived in each dimension, how to identify the multiply deprived, and whether to summarize deprivation in one index or display it as a panel of indicators.