Multidimensional Poverty in India: District Level Estimates

Abstract

Spatial inequalities exist at all levels of disaggregation. However, the nature and extent of these inequalities vary 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 lead to very different results. In addition there is the issue of choice of method to be used in estimating the index. The paper tries to identify chronic poverty at the district level by using multidimensional indicators that reflect persistent deprivation, such as illiteracy, infant mortality, low levels of agricultural productivity and poor infrastructure.

Keywords: India, Data, Multidimensional Poverty, Spatial Analysis, Multidimensional Poverty Measurement