Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

The challenges faced in calibrating poverty and welfare measures to objective data have long been recognized. Until recently, most economists have resisted a seemingly obvious solution, namely to ask people themselves: "Do you feel poor?" The paper studies the case for and against this approach. It is argued that, while one would not want to use self-assessments as welfare metrics in their own right, there is scope for using such data to help calibrate multidimensional measures. Indeed, the idea of a "social subjective poverty line" (below which people tend to think they are poor, but above which they do not) is arguably the most conceptually appealing way of defining poverty. However, the paper points to a number of concerns that have received insufficient attention, including the choice of covariates, survey design issues, measurement errors, frame-of-reference effects, and latent heterogeneity in personality traits and personal tradeoffs. Directions for future research are identified.

Crime and Society --- Economic Theory & Research --- Latent heterogeneity --- Multidimensional poverty --- Poverty Reduction --- Rural Poverty Reduction --- Scales --- Services & Transfers to Poor --- Social Development --- Subjective welfare --- Vignettes --- Well-being

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Widespread agreement that poverty is a multifaceted phenomenon, encompassing deprivations along multiple dimensions, clashes with often vociferous disagreement about how best to measure these deprivations. Drawing on the recent literature, this short note proposes three methodological alternatives to the false dichotomy between scalar indices of multidimensional poverty, on the one hand, and a "dashboard" approach that looks only at marginal distributions, on the other. These alternatives include simple Venn diagrams of the overlap of deprivations across dimensions, multivariate stochastic dominance analysis, and the analysis of copula functions, which capture the extent of interdependency across dimensions. Examples from the literature on both developing and developed countries are provided.

Achieving Shared Growth --- Copulas --- Dependency structure --- Economic Theory & Research --- Macroeconomics and Economic Growth --- Multidimensional poverty --- Poverty Reduction --- Regional Economic Development --- Rural Poverty Reduction