In this paper we briefly revisit some of the prior research by the
authors with regard to the identification of states and regions that
suffer high income poverty and multidimensional deprivation and methods
of computing indices 1. We then extend the analysis by using
multidimensional indicators to analyse spatial variations in development
outcomes for 379 districts in 15 states of India and then to 175 talukas
(subdistricts) in the state of Karnataka. The paper tries to:
identify areas in chronic poverty at the district level by using
multidimensional indicators that could reflect persistent
deprivation, such as illiteracy, infant mortality, low levels of
agricultural productivity and poor infrastructure.
operationalise multidimensional concepts and methods at the district
and below level
identify patterns of development that can input into policy.
Section 2 identifies the states and regions of India that have
experienced greater incidence of long duration or persistent poverty,
severe poverty and multidimensional deprivation. Section 3 tries to
identify the most deprived districts based on indices of
multidimensional poverty using traditionally applied methods and
compares the results with alternate more robust methods. Section 4
extends the analysis to the sub district level or Taluka level for the
state of Karnataka. Section 5 stresses the importance for planners to
decipher \"patterns\" of development and uses the Kohonen
Self-Organizing Map, an artificial intelligence algorithm to do this. We
then identify priority areas for state and civil society action and
conclude the paper.
Operationalising multidimensional concepts of chronic poverty: an exploratory spatial analysis, presented at Staying Poor: Chronic Poverty and Development Policy, Institute for Development Policy and Management, University of Manchester, 7-9 April 2003. Chronic Poverty Research Centre (CPRC), Manchester, UK, 30 pp.