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Operationalizing Multidimensional Concepts of Chronic Poverty: An Exploratory Spatial Analysis

Aasha Kapur Mehta
Ramakrushna Panigrahi
Sashi Sivramkrishna


Spatial inequalities exist at all levels of disaggregation - between countries, states, regions, districts, blocks and even within cities, towns and villages. However, the nature and extent of these inequalities varies with choice of indicator and geographical space over which comparisons are made. A given state may perform extremely well on all indicators but there may be districts within that state that are among the most deprived in the country. Or a state may have very high levels of attainment on economic development and health and very low levels of attainment on education and gender parameters. No single indicator can capture the complexities of development. Therefore, indices are generally estimated by aggregating performance with regard to several indicators. This requires the identification of variables to be included in the index, the range to be used for scaling and weights to be allocated to the different variables. Decisions in this regard tend to be arbitrary and driven by availability of data. Changes in any of these factors can yield very different results. In addition there is the issue of choice of method to be used in estimating the index. [This paper has been published as a chapter in the book entitled Chronic Poverty in India, edited by Aasha Kapur Mehta and Andrew Shepherd, Sage Publications, India.]

Publication Type(s)

CPRC India Working Paper


India data multidimensional poverty methodology spatial analysis multidimensional poverty measurement


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