Abstract
The main goal of this chapter is to undertake a multidimensional poverty analysis in relation to five southern Mediterranean countries, namely Egypt, Lebanon, Morocco, Tunisia, and Turkey. We rely on a broader concept of poverty by considering the deprivations in women’s educational attainments, the possession of durable goods and the consequences of housing conditions, each of which we operationalize by making use of recent developments in multidimensional poverty measurement. This analysis is based on an axiomatic approach to poverty and on the use of stochastic dominance tools to achieve robust results that do not hinge on the choice of poverty line and weighting scheme. Our findings provide comparisons over time for each country and between countries that cannot be obtained when each dimension of poverty is analysed separately, as the approaches take into account the correlations which may exist between different kinds of poverty. Furthermore, in contrast to rankings drawn from cardinal poverty measures (for example, from the Multidimensional Poverty Index), multidimensional tests make it possible to nuance the performance levels reached by certain countries.
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Notes
- 1.
- 2.
Note that there are two types of poverty line definitions which reflect different views of poverty: relative and absolute. These concepts have been widely debated in the literature as illustrated by the controversy between Sen (1981, 1983) and Townsend (1979, 1993). Indeed, Sen (1983) attempted to hierarchize these two concepts and argued that “poverty is an absolute concept in the space of capabilities but very often it will take a relative form in the space of commodities or characteristics” (p. 159, 1983) required to realize those capabilities. Despite the fact that multidimensional poverty analyses have mainly used absolute poverty lines, it would seem reasonable to include both views, depending on the nature of the attributes under consideration. Some attributes, such as income, which can be used to express the deprivation felt by an individual in relation to the living standards of a particular society can be viewed as relative while other attributes, such as health, education, and access to social services, which reflect capabilities in reference to supposedly universal human needs, are better expressed in absolute terms.
- 3.
The approach can be further generalized if different weights are given to each deprivation for the identification of the poverty domain (see Alkire and Foster 2011, for more details). This additional complexity of the approach is not presented here as equal weights are given to each dimension in our empirical analysis.
- 4.
These authors first define some real-valued and differentiable well-being function \( \lambda :\Re^{m} \to \Re \) i.e. non-decreasing with the level of each attribute\( \left( {\frac{{\partial \lambda \left( {x_{i} } \right)}}{{\partial x_{ij} }} \ge 0\,\forall j \in \left\{ {1, \ldots ,m} \right\}} \right) \). Using this function, an individual is deemed poor if and only if his or her level of well-being is below the one corresponding to the set of poverty lines z. The approach can be summed up using the following identification function: \( \psi^{\text{DSY}} \left( {x_{i}} , z \right) = \left\{ {\begin{array}{*{20}c} { 1 {\text{ if }}\lambda \left( {x_{i}} \right) \le \lambda \left( z \right)} \\ { 0 {\text{ if }}\lambda \left( {x_{i}} \right) > \lambda \left( z \right)} \\ \end{array} }\right. \)
- 5.
Symmetry states that the only relevant information for assessing poverty at the individual level is that contained in the vector x i . Symmetry thus implies equal treatment of the equals. With the (weak) focus axiom, it is assumed that an increment in the value of a particular attribute does not change the level of poverty if the corresponding individual does not belong to the set of poor individuals. On the contrary, (weak) monotonicity means that raising the level of some attribute for a poor individual does not increase the poverty level. A poverty index is said to be continuous if marginal variations of the value of some attribute do not yield large variations in the poverty index. Finally, the principle of population states that for a given matrix X, the poverty level should be the same when replicating each element in the matrix many times. This axiom is necessary for the comparison of populations of different sizes. For more details on the axiomatic of poverty measurement, see Zheng (1997).
- 6.
A bistochastic matrix is a square matrix with the sum of each column and row equal to one.
- 7.
PDP and MTP both require the individual poverty function to be convex.
- 8.
In order for this axiom to hold, the poverty index has to be continuous, twice differentiable, and convex. Then the marginal utility of one attribute decreases when the quantity of the other increases. This corresponds to the Auspitz-Lieben-Edgeworth Pareto definition of substitutability and differs from Hicks definition.
- 9.
Thus, the additivity implied by factor decomposability requires that the poverty measure is insensitive to the correlation increasing switch. Conversely, poverty measures that satisfy NDCIS are sensitive to the joint relation between attributes. In this case, poverty measures are then defined by taking a nondecreasing concave function of poverty gaps for each individual in different dimensions.
- 10.
This expression can be generalized by considering different weighting schemes. Let a j be the weight attached to the jth dimension such that \( \sum\limits_{i = 1}^{m} {a_{j} } = m \). In this case, the cut-off “c” can be a real number instead of being a positive integer. See Alkire and Seth (2008).
- 11.
With the class \( \gamma_{1,2} \), sensitivity to progressive transfers would be observed with respect to the second dimension.
- 12.
Children under 5 years are supposed to be less demanding with respect to housing surface and so to weight twice less than more than 5-year-old individuals.
- 13.
In addition, changes in rent control may affect the residential mobility of households. In particular, shifts from the older versions of rent control which maintained rents at fixed nominal levels to other kinds of rent control where rents are freely set but cannot go higher than a maximum rental index might be responsible for adverse effects: smaller housing area per capita and a deterioration in housing conditions.
- 14.
The weights are 0.13 for a television, 0.67 for a car, and 0.19 for a refrigerator.
- 15.
Moreover, the analysis of the urban bias for each dimension shows that deprivation is mainly a rural phenomenon. The results of the tests are available upon request.
- 16.
For further details see online data: http://hdr.undp.org.
- 17.
The rankings of countries for which data are available using the MPI is the following: Tunisia, Egypt, Turkey, Morocco (HRD 2010).
- 18.
The Economic and Social Plan of 1996–2000 was the first document to declare the fight against poverty as a national priority.
- 19.
Among them, BAJ1, launched in 1996, focuses on basic health, basic education, and infrastructure investment in the 14 poorest provinces.
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Acknowledgments
This paper has been prepared within the framework of the “PROPOORSUDS” project funded by the ANR “French National Agency of Scientific Research”. The authors would like to thank the Ministry of Social Affairs of Lebanon for providing the access to the dataset from Lebanon Consumption Household Budget Survey: 2004–2005.
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Bérenger, V., Bresson, F. (2013). Axiomatic and Robust Multidimensional Poverty Measurements in Five Southern Mediterranean Countries. In: Berenger, V., Bresson, F. (eds) Poverty and Social Exclusion around the Mediterranean Sea. Economic Studies in Inequality, Social Exclusion and Well-Being, vol 9. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-5263-8_1
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