Page 333 - Contributed Paper Session (CPS) - Volume 6

CPS1949 Khalid S.
4. Conclusion
This paper studied the sensitivity of multidimensional indices of poverty to
different weighting schemes. Our approach explained why multidimensional
poverty measure depends not only on the approach but also on the weighting
scheme adopted. Testing of pre-determined normative weighting schemes
showed that the linear weighting overestimates poverty indices. Whatever the
weighting scheme adopted, an important difference is observed in the
estimation of poverty indices depending on whether the items of deprivation
are organized or not by dimension. The most important difference concerns
the AF approach. This tendency concerns all the multidimensional indices of
poverty. The stochastic dominance of the curves of poverty allowed us to
confirm the robustness of these results.
The results of Bourguinon and Chakravarty method show that, regardless
of the weighting scheme, the indices of multidimensional poverty are lower
than those obtained from the AF approach. The differences become more
significant by adopting the weighting scheme proposed by AF. Besides, the
differences noticed become more important if we don’t structure the items of
deprivation by dimension. Also, the multidimensional indices of poverty
obtained according to fuzzy logic method not only shows an important
sensibility for the weighting schemes but remains widely lower than those
obtained using the A.F. approach.
In addition, this work shows that a better targeting of the poverty is not
only conditioned by a determination of the relevant dimensions of the poverty
but also by an adequate choice of the weighting scheme and the
measurement approach.

References (some papers)
1. Alkire S. et J. Foster (2009), « Counting and Multidimensional Poverty
Measurement », OPHI, WP No.32
2. Atkinson A.B. (2003), «Multidimensional Deprivation: Contrasting Social
Welfare and Counting Approaches » Journal of Economic Inequality, 1,
51-65.
3. Betti G. & Verma V. K. (1999), «Measuring the degree of poverty in a
dynamic and comparative context: a multi-dimensional approach using
fuzzy set theory », Working Paper 22, Dipartimento di Metodi Quantitativi,
Università di Siena.
4. Betti G., Cheli B., Lemmi A. & Verma V. K. (2007), «The fuzzy set approach
to the multidi- mensional poverty: The case of Italy in the 1990s', in N.
Kakwani & J. Silber (eds.), Quantitative Approaches to Multidimensional
Poverty Measurement », Palgrave Mac Millan, New York, 30-48. Boniface
E. (2000), « Inégalité, pauvreté et bien-être social: fondements analytiques
et normatifs », Ouvertures Economiques, De Boeck Université.

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