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I appreciate all the thought that is being brought to bear on the methodology that Sabina Alkire and I have proposed, and which has recently been implemented for cross country comparisons in the MPI by Sabina and my student Maria Emma Santos. The new technology builds upon the FGT or P-alpha indices that Erik Thorbecke, Joel Greer and I introduced more than 25 years ago, and that are now quite standard for measuring poverty in a single variable (such as income, consumption, or even calories as applied in our original paper using the 1975 Integrated Survey in Kenya). Moreover, the multidimensional methodology reduces to the traditional FGT measures when zero weight is placed on non-income variables. We think that our more general approach might usefully complement the traditional income or consumption based approach, and there are many who share this view. I thought I would make a few points of clarification. The Alkire-Foster poverty measure is not so closely related to the UNDP’'s Human Development Index (HDI). The HDI aggregates country-wide average achievements into an overall indicator of human development, and is analogous to an aggregate welfare measure for a country. It requires many assumptions on the underlying variables to construct a meaningful measure (in the sense of Roberts, Measurement Theory, 1979). It satisfies a range of axioms appropriate to its aims. The Alkire-Foster methodology yields a poverty measure in the sense of Sen (Econometrica, 1976). It first identifies who is poor and then aggregates to obtain an overall measure of poverty. The measure takes into account several dimensions and their dimensional cutoffs in identifying who is multiply deprived and hence who is poor. It likewise uses information on these deprivations to evaluate the extent of poverty for a person, a group of person, or for a country. It satisfies a different collection of axioms appropriate to its aims. The MPI uses the simplest of our measures, the adjusted headcount ratio, to aggregate across deprivations (and not achievements). It can thus be applied to qualitative or categorical variables so long as one can ascertain what is meant by being deprived. Few assumptions must be made on the underlying variables to ensure that the measure is meaningful. In cases where individual deprivations are not equally important, weights are used to reflect the importance of one deprivation relative to another. Dr. Gonzalo Hernandez has indicated above how his team at CONEVAL in Mexico was able to decide upon weights and cutoffs for the Mexican methodology, which is related in structure to the MPI methodology. I have some responses to the two questions revisited in the above commentary. 1. Why a single measure of poverty? Because that is the goal of Sen'’s (1976) defining contribution, which all of our work in poverty measurement builds upon. If there is a superior conceptual framework for poverty measurement, I would be interested in seeing it. 2. Are weights inherently problematic? Perhaps. But once one adopts the position that poverty is multidimensional, this comes with the territory. The selection of weights may differ depending on the context. For a cross-country exercise, where there are fewer normative guideposts, the selection may naturally tend to the focal point of equal weights for distinct dimensions, with equal weights for variables within dimensions. For within-country comparisons, the decision becomes explicitly normative and can be informed by a range of studies. The underlying choice is not dissimilar to the setting of a poverty line in income poverty. One response to this challenge might be to place full weight on a single dimension and zero weight on all the rest - which as I mention above is the solution implicit in the traditional income or consumption poverty measure. But this choice of weights is increasingly coming under scrutiny and is hard to reconcile with the belief that poverty is fundamentally multidimensional. A point that has been missed in the discussion, but is quite apparent to experts, is that each methodology employed to measure poverty has its own list of arbitrary choices. A discussion of weights in the MPI should be contrasted with, say, the analogous choices involved in cross-country comparisons of consumption poverty. How does economic theory tell us to pick the particular bundle of goods for determining a poverty line or for setting appropriate PPP values? Does it recommend a uniquely best equivalence scale? Isn’t the “market price” of a particular category of goods an aggregate itself, and not the marginal price that a decision maker faces in theory? How exactly should market prices be altered where there are market imperfections or missing markets? And what theorem in economics allows us to use consumption to make interpersonal welfare comparisons? These are familiar challenges. Most of us are willing to suspend disbelief in order to move forward. We think a similar willingness is justified in order to augment the informational basis of poverty measurement. James E. Foster The George Washington University and OPHI