Speaker: Dr. Sugata Bag, Associate Professor, Delhi School of Economics

From a social planning perspective, the slums are significant because the bulk of the city's vulnerable population resides here. Though the slum dwellers are not necessarily the poorest of the poor, they are subject to marginalization by various socio-economic factors. Their vulnerable situation poses a severe threat to their livelihood and hence also to the city's social stability. In this paper, we use a primary household survey data from the slums of three metro cities in India to study the slum deprivations as well as the associated household level characteristics.

An important question we encounter in our endeavour is: How should we assess the household level well-being and deprivation (especially in slums)? The most frequently used indicators are monetary indicators (such per capita income or consumption expenditure) which are indeed crucial in capturing household well-being, but their efficacies may be questionable especially within slums where non-monetary indicators may be argued to be of equal or greater importance. Thereby we adopt a two-pronged approach: (a) to assess household's monetary well-being, we use both per-capita income and per capita consumption expenditure; (b) to gauge non-monetary well-being, we resort to the counting approach framework capturing multiplicity of direct deprivations. The other crucial question that we encompass in this paper is: Which factors or household characteristics are associated with various types of well-being assessment? In order to explore this question, we resort to multivariate regression analyses. We aim to understand how various observable characteristics of the slums and the dwelling households are similarly or differently associated with monetary vis-a-vis non-monetary indicators of households? standard of living - first, 'within each city'; and secondly, 'across different cities'.We find not only that certain characteristics are differently associated with welfare aggregates across cities, but also they are quite differently associated with different welfare aggregates within cities. Policy choices are accordingly tempered.