Analysis of Multidimensional Poverty: Theory and Case by Louis-Marie Asselin

By Louis-Marie Asselin

Poverty is a paradoxical country. Recognizable within the eld for any delicate observer who travels in distant rural components and concrete slums and meets marginalized humans in a given society, poverty nonetheless continues to be a problem to conceptual formalization and to size that's in step with such formalization. The research of poverty is multidisciplinary. It is going from ethics to economics, from political technological know-how to human biology, and any form of size rests on arithmetic. in addition, poverty is multifaceted in response to the categories of deprivation, and it's also gender and age speci c. A vector of variables is needed, which increases a considerable challenge for person and crew comparisons essential to fairness research. Multidimension- ity additionally complicates the aggregation essential to practice the ef ciency research of regulations. when it comes to source of revenue poverty, those difficulties, fairness and ef ciency, have bene ted from very signi cant growth within the eld of economics. related achievements are nonetheless to return within the region of multidimensional poverty. inside this basic history, this publication has a truly modest and narrow-scoped aim. It proposes an operational technique for measuring multidimensional poverty, self sustaining from the conceptual foundation, the scale and the qualitative in addition to the quantitative nature of the first signs used to explain the poverty of a person, a loved ones or a sociodemographic entity.

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Let us denote κ = {1, 2, . . , K } as the set of integers from 1 to K . We will now generalize the previous approach to the composite indicator of poverty. First observe that there is an obvious one–one correspondence between the categorical coefficients appearing in the linear expression of the L possible factorial components and the categorical contributions to the disaggregated total inertia, as shown in matrices A and B. The general term of matrix B is the square of the matrix A general term.

The aggregation technique relies on an axiomatic approach to the desired properties of the composite index, largely based on standard axioms enunciated for a univariate poverty index, and on a composite poverty measure referring to a given poverty threshold for each primary indicator. The implicit context is thus a set of quantitative indicators and the resulting index is usually relevant only for that type of indicators. In fact, the composite poverty measure proposed by Bourguignon and Chakravarty is a CES function of the shortfalls (poverty gaps) in each of the primary poverty indicators.

It must also be observed that by breaking down each indicator Ik in as many variables, Jk , as there are categories, MCA allows for non-linearity in the categorical weights, contrary to a PCA which would be run on a numerical coding 1 to Jk of the indicator Ik , as some researchers could be tempted to do. Having looked at some variants of factorial analysis, FA, PCA, and MCA, our third methodological choice is to go on with MCA, due essentially to its particular convenience for categorical variables, its remarkable duality properties and its operationality.

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