A Comparative Study of Living Conditions in Slums of Three Metro Cities in India

Abstract

Urban population in India has been rising rapidly as millions of migrants are moving to urban areas aspiring for higher earning and better living. The number of urban poor is also growing and a significant number of these poor find spaces in slums and continue to struggle for better living standards. Improving their conditions call for significant efforts from the governments for better policy designs. However, better policy design requires understanding the commonalities and differences across slums within and between cities. In this paper, we conduct a comparative study of representative slums across three largest metro cities in India through primary surveys. We find certain characteristics, such as large average household size, poor housing quality, low female labour market participation and high school enrolment rates among children, to be common across and within three cities. Our study however reveals crucial differences between the cities in the demographic pattern of migration and its temporal element. And that in turn brings out considerable heterogeneity among different groups within slums of each cities with respect to living standards, access to civic amenities like sanitation facilities and drinking water. Moreover, there exists major cross-city differences in adult literacy rates across gender, consumption pattern, and subjective wellbeing. Overall, we find that slums in Mumbai on average perform much better in various living condition and social indicators than slums in Delhi and Kolkata.

Heterogeneous contact networks in COVID-19 spreading: the role of social deprivation

“…We demonstrate this here in the context of the city of Kolkata, which captures two aspects critical to our thesis -strong heterogeneity in terms of personal contact networks, as well as areas of great social deprivation, both of which, as will be seen, can lead to the rapid spread of epidemics. While this is a specific choice made by our access to publicly available data [9,11], its relevance FIG. 1.…”

“…In Fig. 14A, we take into account the effect of the slum population obtained from the data of [11] to compute the number of people infected ward by ward (orange curve), to be compared with the city-wide computation (blue curve). We notice a much sharper increase in the number of people infected, relative even to the ward-by-ward graph of Fig.…”

“…Another limitation arises from the availability of data on slums. In [11], 800 slums in Kolkata were studied via sampling methods, without any information on their exact location. We have therefore had to study the slums collectively, without any information on where exactly, and how extensive, they are in any particular area.…”

“…Another point in this context concerns what we mean by the "general" population. The census data [9] that we have based this on includes people of all classes, including slum dwellers, in the city of Kolkata; the specific data on slums [11] is both more recent and focuses only on the 800 slums considered in Kolkata. We reiterate therefore that, as mentioned above, our estimates should be taken as a conservative qualitative indicator of the effects of social deprivation, rather than an accurate quantitative estimate.…”

Does It Matter How We Assess Standard of Living? Evidence from Indian Slums Comparing Monetary and Multidimensional Approaches

“…Slums within urban areas are considered either as "blight" of erstwhile prosperous area or as "staging areas" for immigrant poor (Frankenhoff, 1967) having distinct and derogatory characteristics, such as worse levels of education, health and other socio-economic indicators, compared to the rest of the urban areas (Martinez et al, 2008;Banerjee et al, 2012;Fink et al, 2014). It is to be noted that although slums are differentiated from non-slum areas by certain common characteristics, yet there exist large inter-city and intra-city differences (Bag et al, 2016;O'Hare et al, 1998).…”