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Understanding Deprivation and Well-being of Households with Children

Sunil Kumar Mishra (sunil.mishra@ihdindia.org) is a fellow at the Institute for Human Development, Delhi. Ashima Gupta (ashima29@hotmail.com) is a freelance researcher based in New Delhi.

The composite multiple deprivation index of households with and without children is estimated based on the India Human Development Survey data for 2011–12. The study uses both household- and individual-level dimensions such as shelter, sanitation, water, education, food, health and information. The bivariate logit model is used to find out the factors responsible for the deprivation of the households with children. 

(Appendix Table 1 accompanying this article is available on the EPW website).
The authors thank Ashok Pankaj for his valuable comments and thoughtful suggestions. The authors also thank the anonymous referee for their valuable feedback, which helped in improving the article.

 

A World Bank report on the “State of the Poor” estimated that the regional share of the poor in India to the world poor increased from 22% in 1981 to 33% in 2010 (Olinto et al 2013). As per the National Sample Survey (NSS) 2011–12, more than 269.3 million Indians or 22% of the country’s population are living below the poverty line (BPL). According to the Organisation for Economic Co-operation and Development (OECD 2011) report on inequality in emerging economies, income inequality has doubled in India since the early 1990s. The Gini coefficient of consumption expenditure in rural areas rose from 0.26 in 2004–05 to 0.28 in 2011–12 and in urban areas it was at an all-time high of 0.37, rising from 0.35 for the same period (Jha 2013). Inequality measures look distressing; with the disparity between rural and urban income widening as per the World Bank (2012) data. As per the NSS, 2011–12, more than a quarter of the total Indian rural households are poor and about 83% are in the poorest quintile, which is twice as many as in the highest one. Moreover, large disparities remain among different social categories, thus pointing to challenges in access to opportunities, inclusive service delivery, etc. About 70% of all households in India raise children. With such a large share of households with children, add­r­essing poverty and its disparities in comparison to households without children remains critical.

The remainder of this article explains the status and reasons for multiple deprivations of households with and without children. The status of households’ deprivation in six dimensions is explained, and the multiple deprivations of households in terms of composite deprivation are listed. The gap in poverty, disparity among the two sets of households, and also the different policies that are responsible for deprivation are explained. In this section, we have analys­ed different pillars of well-being in the context of individual deprivation (nutrition, health, education) and house­hold deprivation (shelter, information, water and sanitation) as well as overall deprivation, using the India Human Development Survey (ihds), 2011–12.1 A total of 42,556 households were covered in the survey.

According to the IHDS, 17% of the households are BPL.2 However, the poverty rate among households with and without children is 22% and 8% respectively (Figure 1, p 63). In rural areas, the poverty rate of households with children is 25% and those without children is 10%, while in urban areas, the difference is comparatively low, with 13% of BPL households having children and 4% without children. Among the major states, Bihar shows a highest percentage point difference (26 percentage points) in the poverty rate between households with and without children. Nevertheless, it is important to understand that the number of children in the household and the level of poverty have a direct relationship.

The incidence of poverty has a positive association with the proportion of households belonging to disadvantaged communities (Adivasi/Dalit/Muslim), and with households where the main occupation is “wage labour.” Poverty is also negatively associated with female education.

Poverty can mean poor health, inadequate education, low income, precarious housing, difficult or insecure work, political disempowerment, food insecurity, and the scorn of the better off. The components of poverty change across people, time, and context, but multiple domains are involved. (Alkire 2011)

Income and non-income poverty indicators are equally important for ass­essing deprivation of a particular household. Also, the opportunities in adult life to earn a sufficient income depend on access to educational opportunities in childhood, available health facilities, access to nutritious food, etc. The article follows the household-level dimensions of deprivation from Gordon et al (2003) (Table 1, p 63).

Manifestation of Deprivation

Both the household-level as well as the individual-level indicators play an important role in assessing the deprivation level. This is because a household is influenced not only by the surroundings but also by the facilities provided by the family. On the other hand, individual factors like health, education, etc, are important in determining the deprivation level. Figure 2 explains the status of deprivation for the households with special reference to households with and without children.

For analysing shelter deprivation, we have used two indicators, overcrowding and quality of floor material. Nearly 39% of the total households live in dwellings which have mud floors. Of these, 42.4% households have children and 32.6% do not. The living arrangement of about 10% of households is five or more persons per room. From among them, households with children is 13.4% whereas households with­out is only 1.3%. Half of the total households are found to be shelter-deprived, out of which 54% are with children and 38% are without. The most disadvantaged am­ong the shelter-de­pri­ved households are the ones where female education is low (Figure 3), which is reflective of the lower income and fewer opp­ortunities for investing in improving the family’s living conditions.

Households facing wa­ter deprivation are defined as those which generally take more than 30 minutes to collect water from the source and/or those households which have the access to unsafe water sources. Half of all the households have access to drinking water within their premises. Another 37% manage to collect their drinking water from a distance that takes half an hour, while 10% of the households take between 30 minutes to 1 hour to collect water. The incidence of water deprivation is similar, at 13%, across households with and without children.

A household suffering from sanitation deprivation is defined as a household with no access to a toilet facility. About 63% of total households are found to be sanitation-deprived. Among households with children, it is 65% as compared to 58% of households without children. A negative relationship between sanitation deprivation and the highest education among women is found in households.

Information is one of the important indicators that connects people with the outer world and helps them to know about various developments in society and various plans and programmes. Information deprivation leads to other kinds of deprivation. Figure 4 clearly indicates that households’ access to four sources of information is low except for television. Also, among the households having these resources, a large difference is noticed.

In terms of information deprivation, 19% of total households are deprived wherein a 4 percentage point gap is found in terms of information deprivation bet­ween households with and without children (20% with; 16% without) (Figure 5, p 65). It is notable that as the education level of women increases, the percentage of households accessing the various forms of information sources also increases, irrespective of their economic status.

As we move from primary education category to above the graduation category, a careful observation will lead us to notice that the total level of deprivation has decreased with increase in level of education of women. The overall deprivation drastically falls down as we move up the higher education ladder.

Education deprivation is defined by children in the age group 7–17 years having either dropped out of school, or never gone to school; children in the age group of 7–17 years presently attending school but who have not completed primary education; and if the highest year of education within the household is five or below. Of the total households, 28% are found to be education deprived. Educational deprivation for households with children is 3 percentage points less compared to household without children (27% and 30% respectively).

A household is said to be health deprived if the households having children are not fully immunised or if the women of the household perceive their health status as poor/very poor. About 11% of the total households are found to be health deprived and of these, health deprivation of households with children is 14% while that of households without children is 6%.

Multiple Deprivations

This section analyses the multiple deprivation of households. About 80% of households suffer from one or more deprivation, with about 82.4% households with children and 75% households without children. About 18% of households with children are found to be not deprived in any of the dimensions considered, whereas for households without children, this figure is about 25% (Table 2).

A household is said to be suffering from multiple deprivations if they are deprived in three or more dimensions. A substantial difference can be seen in the multiple deprivations in rural (42%) and urban areas (9.5%). Again the percentage of households with and without children in rural areas is 45% and 37% respectively, whereas for urban areas the figure is 11% and 4% respectively. Likewise, in terms of highest education level for women a substantial difference in deprivation level is found between households with and without children. In terms of the social category of households, the deprivation level is highest among Scheduled Castes (SCs) households (with children, 43.5%, and without children, 34.7%). The deprivation level of Scheduled Tribes (Sts) households is high for both, households with and without children. Among households with non-agriculture wage labour as the main income source, 49.3% of households with children are water-deprived compared to 36.4% of those without children, a difference of 13 percentage points. The deprivation level by income status shows that the difference in deprivation level between households with and without children is 10 percentage points (54.7% and 44.8% respectively) (Table 3).

It is interesting that even among the households identified as income non-poor (using the Tendulkar methodology), 26% were found to have multiple deprivations. To assess the relative importance, logistic regression has been carried out among households with children (Appendix Table 1). In this exercise, households with children who are deprived are denoted as y = 1 and otherwise = 0. It is hypothesised that a set of households having specific demographic, economic, information, health and education-related characteri­stics are gathered in a vector x, which explains the household deprivation status as Prob (y=1) = f (x). The logit backward stepwise regression has been used to get the final results. Households in rural areas face nearly 2.1 times the risk of deprivation as compared to their urban counterparts. The chance of deprivation of households in poorer states such as Madhya Pradesh, Odisha, Bihar, Jharkhand, Rajasthan and Chhattisgarh is 1.23 times higher as compared to rest of the states. Household deprivation is also linked to the caste and religion of the household. Among Muslim households the chances of deprivation are about two times higher as compared to households belonging to the “other than Hindu and Muslim” category. Likewise, the chances of deprivation for SC and ST households with children are 1.5 times higher than Other Backward Class (OBC) and general caste households. The results suggest that the type of occupation of the parent is important in protecting children from deprivation. The chances of deprivation of wage labour households are 1.2 times higher than cultivator and business households.

We find no major difference between the different groups of income and the level of deprivation of households. Perhaps, the distribution of resources within the household has a bearing on deprivation. The risk of household deprivation is found to be significantly associated with parents’ education level and more specifically with the education level of women. It is found that the chance of deprivation is 1.6 times higher in households with illiterate women, as compared to those where education of women is below the primary level, and deprivation is 1.4 and 1.3 times higher compared to households where women have middle and secondary education respectively. The probability of deprivation in households where children have never attended or been enrolled in schools is 1.3 times higher than those with children enrolled in schools.

Deprivation is also higher in households with a higher number of children. House­holds with seven or more children are 1.12 times more deprived as compared to households with two or less children. The sex of the head of households is also an important determining factor in expla­ining the household-level deprivation. The chances of household deprivation are 1.11 times higher for households headed by women as compared to male-headed households. It is interesting to find that the deprivation level is highly associated with the shelter quality as well as the accessibility to different sources of information. The risk of multiple deprivations for children of households suffering from information deprivation is 15 times higher as compared to children of households which are accessing information. On the other hand, the probability of deprivation of households is 15 times higher if it faces high congestion, and if the house suffers from poor structural quality.

Conclusions

Multiple deprivations among households with children in India are strikingly high. A vast difference is visible between areas (rural/urban), socio-religious groups, income/occupation categories and the mother’s education. The study shows an inverse relationship between the mother’s education and multiple deprivations. Likewise, the income/asset quintile has a high negative correlation with the multiple deprivations. It is also interesting to note that about 80% of total households suffer from one or more deprivations. It is interesting to find the major reasons of deprivation in households with children. The analysis clearly shows that among wage labour households, the level of deprivation is higher as compared to those with other occupations. Also, the deprivation level is high for female-headed households. Asset holdings also have a bearing on explaining the households’ deprivation level. Studies show that some proactive measures help a lot in lifting households with children out of deprivation. For example, Bihar’s cycle programme increased the probability of girls in the age group 14–15 years being enrolled in or having completed Class 9 by 30%. Further study shows that the scheme has bridged the gender gap in age-appropriate secondary school enrolment by 40% (Muralidharan and Prakash 2013). Likewise, the mid-day meal scheme has had an impact on enrolment of children in schools, as well as a significant increase in daily calorie intake and the level of protein and iron among children (Afridi 2007). Studies show that teacher absenteeism is one of the hindrances for educational development of children. A study by the Institute for Human Development–Centre for Advocacy and Research (IHD-CFAR)3 in Delhi revealed that the group approach is one of the powerful tools to spread awareness about water and sanitation issues.

A dramatic change is found in terms of use of sanitary napkins by women, drinking of safe water, and realising the importance of accessing toilets. If any member of the household is a part of credit or saving group, the deprivation rate is low as compared to a non-member. The proportion of households who are shelter-deprived is 41% if that household is a member of credit society as compared to 62% of the households which are not members of credit societies. Likewise, we have found a 16 percentage point gap in sanitation deprivation (57% and 41%), 10 percentage point gap in information deprivation (21% and 11%) and 4 percentage point gap in food deprivation (14% and 10%) between the two groups. The inclusion and exclusion error as well as low value of benefit of different programmes has a negative impact on child development (Barrientos and De Jong 2006).

Household deprivation is less if the household is a public distribution system (PDS) beneficiary as compared to a non-beneficiary. Likewise studies show that the likelihood of a child getting involved in child labour is low if a poor household participated in the Mahatma Gandhi National Rural Employment Guarantee Scheme (MGNREGS). Uppal (2009) found that the likelihood of children involved in child labour increased for boys by 13.4% and girls by 8.2% if the household is not registered in MGNREGS.

Notes

1      The India Human Development Survey (IHDS) is undertaken jointly by National Council for Applied Economic Research (NCAER) and the University of Maryland. It is a multi-dimensional survey conducted respectively in 2004–05 and 2011–12 and it includes a wide range of human development-related issues.

2      Based on the Tendulkar poverty line.

3      The Institute for Human Development (IHD) along with the Centre for Advocacy and Research (CFAR) conducted an evaluation on the impact of the group approach in change in water, sanitation behaviour and the overall increase in agency among women and its impact in the household as well as society. The study was done in 27 identified clusters/slums identified by the CFAR.

References

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Alkire, Sabina (2011): “The Capability Approach and Human Development,” Oxford Poverty and Human Development Initiative, Working Paper No 46.

Barrientos, A and J DeJong (2006): “Child Poverty and Cash Transfers,” Report No 4, Childhood Poverty Research and Policy Centre, London.

Gordon, David and Shailen Nandy (2003): “Measuring Child Poverty and Deprivation,” University of Bristol, British Medical Association, Housing and Health: Building for the Future, British Medical Association.

Gordon, David, Shailen Nandy and Peter Townsend (2003): “Measuring Child Poverty and Deprivation,” Townsend Centre for International Poverty Research University of Bristol, http://www.equityforchildren.org/wpcontent/uploads/2013/07/4.GordonandNandyMeasuringChildPoverty-1.pdf.

Jha, Somesh (2013): “Rich–Poor Gap Widens in India,” Business Standard, 10 August, https://www.business-standard.com/article/economy-policy/rich-poor-gap-w....

Muralidharan Karthik and Nishith Prakash (2013): “Cycling to School: Increasing SecondarySchool Enrollment for Girls in India,” Discussion Paper No 7585, ForschungsinstitutzurZukunft der Arbeit, Institute for the Study of Labor, Bonne.

OECD (2011): “Inequality in Emerging Economies,” Organisation for Economic Co-operation and Development.

Olinto, Pedro, Kathleen Beegle, Carlos Sobrado and Hiroki Uematsu (2013): “The State of the Poor: Where Are the Poor, Where Is Extreme Poverty Harder to End, and What Is the Current Profile of the World’s Poor?” Economic Premise, No 125, World Bank, Washington, DC.

Uppal, Vinayak (2009): “Is the NREGS a Safety Net for Children? Studying the Access to the National Rural Employment Guarantee Scheme for the Young Lives Families and its Impact on Child
Outcomes in Andhra Pradesh,” thesis submitted in partial fulfilment of the requirements for the Degree of Master of Science in Economics for Development, University of Oxford United Kingdom.

World Bank (2012): “World Development Indicators,” World Bank, Washington, DC.

Updated On : 13th May, 2019

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