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This article builds on an extensive literature overview of plausible dimensions and indicators that are desirable from a theoretical perspective to measure multidimensional poverty. Methodologically, it draws upon the dual cut-off counting approach for poverty measurement developed by Alkire & Foster (2011), which is also the methodological underpinning of the global and national MPIs. Conceiving the MPI-MIC is not an easy task. One fundamental issue is the existence of strictly comparable micro data sources. The proposed measure aims to be an internationally comparable measure, so ideally, it needs to build solely on a set of harmonized indicators available for all the countries that will be studied. Thus, available data satisfying this criterion is a crucial determining factor. In the spirit of the SDGs and the acceptance of the multidimensional nature of poverty, we do not wish to select countries based solely on aggregate income. We supplement the traditional monetary classification of countries with other non-monetary aspects of development. We used data from Brazil, Ecuador, Costa Rica, Mexico and Colombia to estimate the MPI-MIC and compare the results across countries.
This article builds on an extensive literature overview of plausible dimensions and indicators that are desirable from a theoretical perspective to measure multidimensional poverty. Methodologically, it draws upon the dual cut-off counting approach for poverty measurement developed by Alkire & Foster (2011), which is also the methodological underpinning of the global and national MPIs. Conceiving the MPI-MIC is not an easy task. One fundamental issue is the existence of strictly comparable micro data sources. The proposed measure aims to be an internationally comparable measure, so ideally, it needs to build solely on a set of harmonized indicators available for all the countries that will be studied. Thus, available data satisfying this criterion is a crucial determining factor. In the spirit of the SDGs and the acceptance of the multidimensional nature of poverty, we do not wish to select countries based solely on aggregate income. We supplement the traditional monetary classification of countries with other non-monetary aspects of development. We used data from Brazil, Ecuador, Costa Rica, Mexico and Colombia to estimate the MPI-MIC and compare the results across countries.