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Editorial | Dimensiones 3

11 May, 2017
Foto: Amit Gupta - Flickr - Creative Commons

In this edition, we are pleased to present a variety of articles from different regions of the world – Latin America, Africa and India – that illustrate the richness offered by multidimensional poverty indices (MPIs) for analysing poverty, either alone or as a complement to income measurement.

We begin with Colombia in our series of interviews with key players. In this issue, ex-director of the Colombian Department for Social Prosperity, Tatyana Orozco, discusses the use of the C-MPI by the Colombian government.

We continue with an analysis of sub-Saharan African countries that illustrates the MPI’s powerful disaggregation feature by presenting results for subnational regions. It also shows that pockets of acute poverty are not exclusive to countries with higher national levels of poverty.

The MPI can be easily adapted to analyse subgroups of the population living in poverty – in this case, by identifying the poorest among the poor using different criteria in order to undertake a thorough analysis of this segment of the population.

We showcase India next, where Sabina Alkire and Suman Seth ask if a reduction in poverty was the result of helping those people with a larger number of deprivations or only those just below the poverty line. They also explore which dimensions exhibit the greatest changes over time in the period analysed. Furthermore, they show that the MPI can be easily adapted to analyse subgroups of the population living in poverty – in this case, by identifying the poorest among the poor using different criteria in order to undertake a thorough analysis of this segment of the population.

Both analyses as well as our ‘Data of the Month’ section show the possibilities for analysing changes over time with these indices.

We also offer our readers a description of the creation process for the Chilean MPI. This article illustrates the institutional consultation process and the efforts made to implement, with transparency, a brand-new way of measuring poverty.

We invite you to read Dimensions.

 

 

Photo: Amit Gupta

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