Abstract
The preceding chapter has highlighted a few socio-demographic attributes of the sample households drawn from selected districts or subdistricts (also known as tehsils) in UP, Rajasthan and Delhi. It was noticed from the analysis of these attributes that the capital city of Delhi has certain advantages over the rest, although there appear to be some notable differences between its slum and non-slum households. The two, for example, differed largely in terms of sex distributions. To be more specific, of all the locations and districts covered in the study, a higher fraction of female population may only be noticed in the slum households in Delhi. In addition, the share of their youth population in the 15–24 age groups is also relatively higher, indicating certain differentials in their fertility behaviour with the re
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Notes
- 1.
A further scrutiny of this data reveals that around 80 % of them were in the 0–4 age group. The rest were however between 5 and 14 years of age.
- 2.
All yearly nonfood data have been converted into monthly format before calculating the PCMCE.
- 3.
It ought to be pointed out that this study has nowhere tried to differentiate between emergency and nonemergency health-care items or expenditure.
- 4.
The defined poverty line for the three states were: UP, rural = 365.24 and urban = 483.26; Rajasthan: rural = 374.57 and urban = 559.63; and Delhi, urban = 612.91 (poverty estimates given by the Planning Commission for 2004–2005, released by Press Information Bureau, Government of India).
- 5.
Poverty gaps are generally measured at the household level, but individual income or consumption can also be used as it is drawn as the mean household income or consumption and remains equal for the entire household.
- 6.
In one case, n includes poor and nonpoor both, and in another it simply comprises persons or households with Z > PCMCE.
- 7.
In its simplest way, Gini is mathematically derived as the covariance between the consumption c of an individual (or household) and the F rank that the individual or household occupies in the distribution of consumption (this rank assumes 0 for the poorest to 100 for the richest). Denoting the per capita monthly consumption expenditure by \( \overline{c} \), the standard Gini index is defined as = 2 cov (y, F)/\( \overline{c} \). We have used STATA to obtain these results (Klugman 2002, Technical Note A.7, p. 415). Computationally, it matters whether or not the consumption (or income) is weighted by household size, since households with lower income or consumption may be larger in size. To avoid this problem, we have followed a weighted HHD system in the entire analysis.
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Alam, M. (2013). Socio-economic Variations, Consumption Poverty and Health-Generated Inequalities in Sample Population. In: Paying Out-of-Pocket for Drugs, Diagnostics and Medical Services. India Studies in Business and Economics. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1281-2_3
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