Using Multidimensional Poverty Measures in Impact Evaluation: Emergency Housing and the "Declustering" of Disadvantage.

During the past two decades, impact evaluation and multidimensional poverty measurement have gained increasing relevance in development practice and research. The objective of this paper is to propose empirical strategies for using the multidimensional poverty measures proposed by Alkire and Foster (2011. "Counting and Multidimensional Poverty Measurement." Journal of Public Economics 95 (7–8): 476–487) in impact evaluation. The principal argument for taking this approach is that it provides a means for assessing the effects of social programmes on the simultaneous occurrence or joint frequency of deprivations, what Wolff and de-Shalit (2007. Disadvantage. Oxford: Oxford University Press) call the "clustering" of disadvantage. As the interrelation between functionings tends to bind disadvantages together, social programmes that "decluster" disadvantages could produce benefits that go beyond improvements in multiple wellbeing dimensions individually. These strategies are applied to the evaluation of the NGO TECHO's emergency housing programme in the informal settlements of Buenos Aires, Argentina. The results show that the programme produces a large reduction in the simultaneous occurrence of disadvantages. Privacy, interpersonal relations and psychological health are the dimensions that contribute the most to explaining the decline in multidimensional deprivation. Sensitivity analyses demonstrate the robustness of the results to changes in the criteria used to construct the multidimensional poverty measure. [ABSTRACT FROM AUTHOR]