In this empirically driven paper we compare the performance of two techniques in the literature of poverty measurement with ordinal data: multidimensional poverty indices and first order dominance techniques (FOD). Combining multiple scenario simulated data with observed data from 48 Demographic and Health Surveys around the developing world, our empirical findings suggest that the FOD approach can be implemented as a useful robustness check for ordinal poverty indices like the multidimensional poverty index (MPI; the United Nations Development Program’s flagship poverty indicator) to distinguish between those country comparisons that are sensitive to alternative specifications of basic measurement assumptions and those which are not. To the extent that the FOD approach is able to uncover the socio-economic gradient that exists between countries, it can be proposed as a viable complement to the MPI with the advantage of not having to rely on many of the normatively binding assumptions that underpin the construction of the index
Bibliographical noteImportant note from the Publisher regarding the attached version of the article: “This is a post-peer-review, pre-copyedit version of an article published in Social Indicators Research. The final authenticated version is available online at: http://dx.doi.org/10.1007/s11205-017-1637-x”.
- Multidimensional poverty measurement
- Poverty index
- First order dominance