First Order Dominance Techniques and Multidimensional Poverty Indices: An Empirical Comparison of Different Approaches

First Order Dominance Techniques and Multidimensional Poverty Indices: An Empirical Comparison of... 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Social Indicators Research Springer Journals

First Order Dominance Techniques and Multidimensional Poverty Indices: An Empirical Comparison of Different Approaches

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Publisher
Springer Netherlands
Copyright
Copyright © 2017 by Springer Science+Business Media Dordrecht
Subject
Social Sciences; Sociology, general; Quality of Life Research; Microeconomics; Public Health; Human Geography; Quality of Life Research
ISSN
0303-8300
eISSN
1573-0921
D.O.I.
10.1007/s11205-017-1637-x
Publisher site
See Article on Publisher Site

Abstract

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.

Journal

Social Indicators ResearchSpringer Journals

Published: Apr 26, 2017

References

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