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In measuring human development, one of the main concerns relates to the inclusion of a measure that penalizes inequalities in the distribution of achievements across the population. Using indicators from nationally representative household surveys and census data, this paper proposes a straightforward methodology to estimate a household-based distribution-sensitive human development index aggregated through generalized means. The evidence shows that the losses in human development due to inequality reach up 22, 29 and 57% in Mexico, Peru and Nicaragua, respectively. Among dimensions, the loss in the income index reaches up 61% in Nicaragua, while the education index appears as the most sensitive in the case of Mexico and Peru, with a percentage of loss between 38 and 48%. The importance of household-level calculations is highlighted when we compare the indices computed from the entire distribution with those existing indices computed for quintiles of the distribution, which minimizes the losses due to inequality. Overall, the estimations evidence a higher sensitivity of the index to inequality, and therefore an important space for public action to reduce inequality that could involve positive development returns. (Contains 5 figures, 5 tables and 15 footnotes.)

At the core of poverty eradication is the need to eliminate that poverty that is persistent over time (chronic poverty). Unfortunately, traditional approaches to identifying chronic poverty require longitudinal data that is rarely available. In its absence, this paper proposes an alternative approach that only requires 1 year of cross‐sectional data on monetary and non‐monetary poverty. It puts forth two conjectures and contends that the combined profile of a household as both income poor and multidimensionally poor can be used as a proxy of that household being chronically income poor. To explore the viability of this approach, we use a probit model and longitudinal data for three Latin American countries to estimate households' probabilities of remaining in income poverty based on their past income and multidimensional poverty statuses. We find empirical support for the approach that is significant, consistent across countries, and robust to various controls and periods of analysis. [ABSTRACT FROM AUTHOR]