Compară metode

	Datt-Ravallion Decomposition	Foster-Greer-Thorbecke Index
Domeniu	Economie	Economie
Familie	Process / pipeline	Process / pipeline
Anul apariției	1992	1984
Autorul original	Gaurav Datt & Martin Ravallion	James Foster, Joel Greer & Erik Thorbecke
Tip	Poverty-change decomposition	Parametric class of poverty measures
Sursa seminală	Datt, G., & Ravallion, M. (1992). Growth and redistribution components of changes in poverty measures: a decomposition with applications to Brazil and India in the 1980s. Journal of Development Economics, 38(2), 275–295.	Foster, J., Greer, J., & Thorbecke, E. (1984). A class of decomposable poverty measures. Econometrica, 52(3), 761–766.
Denumiri alternative	Growth-Redistribution Decomposition, Datt-Ravallion Method, Growth and Redistribution Components, Poverty Change Decomposition	FGT Index, FGT Poverty Measures, P-alpha Poverty Index, Foster-Greer-Thorbecke Poverty Measure
Înrudite	3	4
Rezumat	The Datt-Ravallion decomposition, introduced by Gaurav Datt and Martin Ravallion in 1992, separates the observed change in a poverty measure between two dates into a growth component — the change attributable to a shift in mean income holding the relative distribution fixed — and a redistribution component — the change attributable to a shift in the Lorenz curve holding mean income fixed. A residual captures the interaction between the two. It became the standard way to ask whether falling poverty was driven by rising average incomes or by changes in inequality, and underlies the empirical literature on pro-poor growth.	The Foster-Greer-Thorbecke (FGT) index is a parametric class of poverty measures introduced by James Foster, Joel Greer, and Erik Thorbecke in 1984 that became the workhorse of applied poverty analysis. A single parameter alpha tunes how much weight the measure places on the depth and distribution of poverty: alpha = 0 gives the headcount ratio (the share of people below the poverty line), alpha = 1 gives the poverty gap (the average normalized shortfall), and alpha = 2 gives poverty severity (which weights larger shortfalls more heavily). Its defining virtue is additive decomposability — total poverty is the population-weighted sum of subgroup poverty — which makes it ideal for profiling poverty across regions, sectors, and demographic groups.