Multidimensional Targeting: Identifying Beneficiaries of Conditional Cash Transfer Programs

Azevedo, Viviane; Robles, Marcos

doi:10.1007/s11205-013-0255-5

Cited by 53 publications

(31 citation statements)

References 24 publications

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“…A very significant methodology of this type is the official national poverty measure for Mexico (CONEVAL, 2010). There have also been applications to other multidimensional measurement problems such as targeting of conditional cash transfers (Azevedo and Robles, 2010) and measuring energy provision (Nussbaumer et al, 2011).…”

Section: An Illustrative Application: Indicators Of Child Poverty In mentioning

confidence: 99%

Beyond headcount: measures that reflect the breadth and components of child poverty

Alkire¹,

Roche²

2012

Global Child Poverty and Well-Being

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This paper presents a new approach to child poverty measurement that reflects the breadth and components of child poverty. The Alkire and Foster method presented in this paper seeks to answer the question 'who is poor' by considering the intensity of each child's poverty. Once children are identified as poor, the measures aggregate information on poor children's deprivations in a way that can be broken down to see where and how children are poor. The resulting measures go beyond the headcount by taking into account the breadth, depth or severity of dimensions of child poverty. The paper illustrates one way to apply this method to child poverty measurement, using Bangladeshi data from four rounds of the Demographic Health Survey covering the period 1997-2007. Results for Bangladesh show that the AF adjusted headcount ratio adds value because it produces a different ranking than the simple headcount, because it also reflects the simultaneous deprivations children experience (intensity). Given this, we argue that child poverty should not be assessed only according to the incidence of poverty but also by the intensity of deprivations that batter poor children's lives at the same time. The Bangladesh example is used to illustrate how to compute and interpret the child poverty figures, how the final measure can be broken down by groups and by dimensions in order to analyse child poverty, how to interpret changes over time, and how to undertake robustness checks concerning the poverty cut-off.

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Section: An Illustrative Application: Indicators Of Child Poverty In mentioning

confidence: 99%

Beyond headcount: measures that reflect the breadth and components of child poverty

Alkire¹,

Roche²

2012

Global Child Poverty and Well-Being

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“…1 More broadly, to assert clearly whether policy is deemed to reduce multidimensional or unidimensional poverty would seem particularly important. 2 As pointed out by Azevedo and Robles (2010), erroneously focussing policy on unidimensional poverty measurement may lead to a sub-efficient fall in multidimensional poverty. (This is in fact the core motivation of this paper.)…”

Section: Introductionmentioning

confidence: 99%

Multidimensional Poverty Targeting

Duclos

Tiberti

Araar

2018

Economic Development and Cultural Change

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Abstract:The importance of taking into account multiple dimensions of wellbeing in the measurement of poverty has been emphasized in the recent literature. The poverty alleviation literature has not, however, yet addressed the important issue of policy design for efficient multidimensional poverty reduction. From a normative perspective, it can be argued that, in addition to being concerned with impacts on multiple dimensions of poverty, policy should also consider impacts on their joint distribution. From a positive perspective, it is regularly observed that different poverty dimensions are often correlated and mutually reinforced, especially over time. The paper integrates these two perspectives into a consistent policy evaluation framework. Targeting dominance techniques are also proposed to assess the normative robustness of targeting strategies. The analytical results are applied to data from Vietnam and South Africa and illustrate the role of both normative and positive perspectives in designing efficient multidimensional poverty targeting policies.

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“…On the other extreme, the intersection approach demands considering as multidimensionally poor only people who are deprived in every dimension. 6 For instance, Batana (2008), Santos and Ura (2008), Alkire and Seth (2008), Battiston et al (2009), Foster et al (2009, Azevedo and Robles (2009), Singh (2009), Trafton (2009 and Roche (2009). 7 For a recent articulation of this concern see, for instance, Ravallion (2010).…”

Section: Introductionmentioning

confidence: 99%

Conditions for the most robust multidimensional poverty comparisons using counting measures and ordinal variables

Yalonetzky

2014

Soc Choice Welf

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A natural concern with multivariate poverty measures, as well as with other composite indices, is the robustness of their ordinal comparisons to changes in the indices' parameter values. Applying multivariate stochastic dominance techniques, this paper derives the distributional conditions under which a multidimensional poverty comparison based on the popular counting measures, and ordinal variables, is fully robust to any values of the indices.parameters. As the paper shows, the conditions are relevant to most of the multidimensional poverty indices in the literature, including the Alkire-Foster family, upon which the UNDP.s "Multidimensional Poverty Index" (MPI) is based. The conditions are illustrated with an example from the EU-SILC dataset. Conditions for the Most Robust Multidimensional Poverty Comparisons Using Counting Measures and ordinal variablesGaston Yalonetzky University of Leeds, OPHI July 3, 2012Abstract A natural concern with multivariate poverty measures, as well as with other composite indices, is the robustness of their ordinal comparisons to changes in the indices' parameter values. Applying multivariate stochastic dominance techniques, this paper derives the distributional conditions under which a multidimensional poverty comparison based on the popular counting measures, and ordinal variables, is fully robust to any values of the indices'parameters. As the paper shows, the conditions are relevant to most of the multidimensional poverty indices in the literature, including the AlkireFoster family, upon which the UNDP's "Multidimensional Poverty Index" (MPI) is based. The conditions are illustrated with an example from the EU-SILC dataset.JEL Classi…cation: I32.

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Multidimensional Targeting: Identifying Beneficiaries of Conditional Cash Transfer Programs

Cited by 53 publications

References 24 publications

Beyond headcount: measures that reflect the breadth and components of child poverty

Beyond headcount: measures that reflect the breadth and components of child poverty

Multidimensional Poverty Targeting

Conditions for the most robust multidimensional poverty comparisons using counting measures and ordinal variables

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