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WPS5580 Policy Research Working Paper 5580 Public Disclosure Authorized On Multidimensional Indices of Poverty Martin Ravallion Public Disclosure Authorized Public Disclosure Authorized The World Bank Public Disclosure Authorized Development Research Group Director’s office February 2011 Policy Research Working Paper 5580 Abstract There has been a growing interest in what have come for, should it be done in the space of “attainments,” to be termed “multidimensional indices of poverty.” using prices when appropriate, or that of “deprivations,” Advocates for these new indices correctly point out that using weights set by the analyst? The paper argues that command over market goods is not all that matters to the goal for future poverty monitoring efforts should be peoples’ well-being, and that other factors need to be to develop a credible set of multiple indices, spanning considered when quantifying the extent of poverty and the dimensions of poverty most relevant to a specific informing policy making for fighting poverty. However, setting, rather than a single multidimensional index. the author argues that there are two poorly understood When weights are needed, they shouldn’t be set solely by issues in assessing these indices. First, does one believe an analyst measuring poverty. Rather, they should be, as that any single index can ever be a sufficient statistic for much as possible, consistent with well-informed choices poverty assessments? Second, when aggregation is called made by poor people. This paper is a product of the Director’s office, Development Research Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at [email protected]. The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. Produced by the Research Support Team On Multidimensional Indices of Poverty Martin Ravallion1 1 The author is Director of the Development Research Group, World Bank, 1818 H Street NW, Washington DC, 20433, USA. For helpful discussions on this topic and comments on this paper the author is grateful to Sabina Alkire, Kathleen Beegle, Gabriel Demombynes, Quy-Toan Do, Jean-Yves Duclos, Francisco Ferreira, James Foster, Garance Genicot, Stephan Klasen, Peter Lanjouw, Michael Lokshin, Nora Lustig, Branko Milanovic, Mead Over, Dominique van de Walle, Roy Van der Weide and Hassan Zaman. These are the views of the author, and need not reflect those of the World Bank or any affiliated organization. 1. Introduction There has been a growing interest in what have come to be termed “multidimensional indices of poverty.” There are many issues one might discuss related to these indices, including the choice of the functional form, the choice of poverty lines, and the robustness of the implied rankings to those choices.2 However, these issues are essentially generic to all poverty measures (though with some more technical differences). The present discussion will focus instead on how multidimensional indices differ from more familiar approaches. This is a logical starting point for potential users trying to understand and apply these new measures; to assess their contribution we must first understand how they differ from standard measures. Multidimensionality per se cannot be what distinguishes a multidimensional index of poverty (MIP). There is an obvious sense in which almost every poverty measure found in practice is “multidimensional.” Indeed, to my knowledge, the only truly one-dimensional indices are the rice-based measures once found in some countries in Asia, but no longer used.3 The main measures now found in practice use a composite measure of consumption or income with many components, relying heavily on market prices in aggregation. Nor does the difference lie in the recognition of the fact that poverty is not just about low consumption of market commodities. It is widely agreed that there are also important non-market goods relevant to welfare, such as access to public services. Poverty is multidimensional. However, that does not imply that one needs a MIP. It is one thing to recognize that something is missing from a given measure, and needs to be considered, and quite another to create a single composite index. The more common approach is to collect multiple indicators of the various dimensions of poverty, invariably including an index of command over market goods, but also including indicators for health and education attainments and access to services. A well-known example is the United Nations’ Millennium Development Goals, which span multiple 2 For example, in the case of poverty measurement, where there is almost always a degree of arbitrariness about the poverty line, best practice tests the robustness of poverty comparisons to the choices made, invoking the theory of stochastic dominance. For expositions in the standard “unidimensional” case see Atkinson (1987) and Ravallion (1994). Duclos et al. (2006) provide dominance tests for “multidimensional poverty.” 3 For example, the government of Vietnam measured poverty by rice consumption prior to the early 1990s. This was in part at least because of high inflation in the 1980s, and inadequate price indices. More standard multi-commodity poverty measures emerged soon after. 2 dimensions, but without forming a single composite index. At the country level, the World Bank’s Poverty Assessments and the Poverty Reduction Strategy Papers of individual governments have typically drawn on multiple indicators (though naturally with varying emphasis), without forming a single composite index.4 This paper argues that the real differences between the recent measures that are called “multidimensional” and standard approaches lie elsewhere. The first difference is in whether one believes that a single index of poverty could ever be a sufficient statistic, or whether multiple indices are required, each measuring different things using the best data available for that task— presenting us with a “large and eclectic dashboard” (Stiglitz et al., 2009, p.62). A second difference is also evident on closer inspection, namely how the analyst chooses to collapse multiple dimensions into one, recognizing that some degree of aggregation will probably be called for even in the “dashboard” approach. In elaborating these two differences I will illustrate the arguments using the most well- developed and broadly applied MIP to date, namely that developed by Alkire and Santos (2010a), which is a special case of the class of measures proposed by Alkire and Foster (2007). The following section discusses the Alkire-Santos index, and whether it can be considered sufficient for measuring poverty and informing policy making. Section 3 turns to the issue of how one can go about aggregating across multiple dimensions when a degree of aggregation is called for to reduce the dimensionality. Section 4 concludes. 2. Can we measure poverty adequately with any single index? There are countless possibilities for forming composite indices by some form of essentially ad hoc aggregation—giving what I term elsewhere “mashup indices” (Ravallion, 2010a). The issue in this section is not how this can be done but whether it is useful to do so. One can easily imagine situations in which one would not want a mashup index. Imagine you go for your annual medical checkup. Your doctor does all the usual tests, but tells you that she will base her assessment solely on a single composite index—rescaling and averaging all the test 4 The Bank’s Poverty Assessments (significant analytic reports covering virtually all developing countries) typically cover education, health and nutrition and access to infrastructure, in addition to income poverty. 3 results. You would be well advised to get a new doctor!5 Or imagine that a new car comes on the market that collapses all those dials on the dashboard into just one composite index, on which you are supposed to decide what to do (slow down or get fuel). You would surely not buy this car! Essentially the same point applies to the task of prioritizing policies for fighting poverty in a given country (or other geographic area). We will naturally want to look at the country’s attainments in various dimensions, rather than focusing on its performance with respect to a single composite index. Should we be focus on promoting job creation (say) or better health and education services? Such an approach does not deny that poverty is “multidimensional.” Rather it says that forming a single (uni-dimensional) index may not be particularly useful for sound development policy making. Consider now the MIP developed by Alkire and Santos (2010a) for the 2010 Human Development Report (UNDP, 2010). They choose 10 variables for their MIP under the same three headings—health, education and living standards—as the UNDP’s Human Development Index (HDI). There are two variables for health (malnutrition, and child mortality), two for education (years of schooling and school enrolment), and six for deprivation in “living standards” (namely cooking with wood, charcoal or dung; not having a conventional toilet; lack of easy access to safe drinking water; no electricity; dirt, sand or dung flooring and not owning at least one of a radio, TV, telephone, bike or car).

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