Abstract
The measurement of multidimensional poverty has been advocated by most welfare scholars and is experiencing a growth in interest partly explained by controversial debates emerged across academics and practitioners. This chapter follows one of the least explored approaches—multiple correspondence analysis (MCA)—to assess multidimensional poverty in Morocco between 2001 and 2007. MCA provides two major advantages for the measurement of multidimensional poverty: it generates a matrix of “weights” based on the variance-covariance matrix of all welfare dimensions selected and provides a natural approach for constructing a composite welfare indicator that satisfies essential poverty orderings axioms. The application shows that poverty in Morocco has declined according to both monetary and multidimensional indicators and that these findings are robust to stochastic dominance tests. This chapter concludes that the sustained positive growth that Morocco experienced during the last decade has translated in improvements in living conditions well beyond monetary returns.
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Notes
- 1.
Unlike previous studies, we refer to the composite indicator as ‘welfare’ rather than ‘poverty’ indicator. That is because the composite indicator applies to poor and non-poor and is therefore a ‘welfare’ indicator.
- 2.
See http://www.omdh.hcp.ma/ for a number of poverty studies on Morocco conducted by the High Commission for the Plan.
- 3.
Note that other criteria also used to select relevant variables such as the spread on the first axis, the high frequency of non-responses or low frequencies of responses on certain modalities.
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Acknowledgments
The authors are grateful to Florent Bresson and Valérie Bérenger for very useful comments.
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Ezzrari, A., Verme, P. (2013). A Multiple Correspondence Analysis Approach to the Measurement of Multidimensional Poverty in Morocco 2001–2007. 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_7
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