Discussion Paper
No. 2013-6 | January 15, 2013 | http://www.economics-ejournal.org/economics/discussionpapers/2013-6

Child Disability and Maternal Work Participation:
New Evidence from India
Prachi Gupta, Upasak Das, and Ashish Singh
Abstract
Using data from the India Human Development Survey, this paper analyses the relationshipbetween child disability and maternal work participation for India. The authors’ findings suggest
a significant positive relationship between child disability and the work participation of the urban
mothers who are wives of household heads. These mothers are 1.27 times as likely to participate inlabour market as mothers (wives in urban areas) without a disabled child. However, for the same
mothers, child disability significantly affects the weekly work hours of those participating in thelabour market in a negative manner with presence of a disabled child reducing the weekly work
hours by 3.6 hours. For the rural mothers and the mothers in urban areas who are household heads,
our findings do not suggest any significant association between child disabilities and their work
participation (or weekly work hours).
JEL J10 J22
Keywords Child disability; maternal work participation; India
Authors
Prachi Gupta, Indira Gandhi Institute of Development Research, Mumbai
Upasak Das, Indira Gandhi Institute of Development Research, Gen. A.K. Vaidya Marg,
Goregaon (East), Mumbai 400065, India, upasak.das@gmail.com
Ashish Singh, Azim Premji University, Bangalore
This paper was written when Ashish Singh was a PhD candidate at the Indira Gandhi Institute of Development Research,
India.
Citation Prachi Gupta, Upasak Das, and Ashish Singh (2013). Child Disability and Maternal Work Participation:
New Evidence from India. Economics Discussion Papers, No 2013-6, Kiel Institute for the World Economy. http://
www.economics-ejournal.org/economics/discussionpapers/2013-6© Author(s) 2013. Licensed under the Creative Commons License - Attribution 3.0

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1. Introduction
There is an increasing evidence in the literature on parental work participation which shows thatchildren and their upbringing has a significant impact on the labour supply of parents, especiallymothers. As noted by Breslau et al. (1982), women’s activities in the labour market are dominated by
the events in their motherhood. Factors like fertility, child age, and child health are some of the key
child related factors which determine a mother’s labour participation. Since, a disabled child often
requires additional support for self care and mobility, presence of a disabled child in a household
generally increases the child care demands on the household members. In such situations, theresponsibility of the female members of the household, especially mothers is observed to rise due topowerful cultural norms that assign women the principal responsibility of taking care of sick membersof the household (Lewis & Lewis, 1977; Carpenter, 1980). This may lead to reduced participation of
women especially mother’s in the labour force. However, as noted by Breslau et al. (1982) and Gould(2004), presence of a disabled child in a household could also lead to an opposite effect on mother’s
work activity wherein faced with the additional financial burden due to health care requirements ofthe disabled child, the mother may chose to enter the work force or increase her hours of participation.
Most of the existing studies on the subject find a negative correlation between child disability andmother’s labour participation (Breslau et al., 1982; Salkever, 1982a; Kimmel, 1998, Porterfield, 2002;
Dunkelberg & Spiess, 2007). But in the case of single mothers, the evidence is mostly mixed. Lu andZuo (2010) find that child disability has different impacts on the labour market activities of marriedand non-married women in Australia, with child disability imposing a greater hardship on the nonmarried women. This is so because they may have to stay on to work as usual even if they have adisabled child in order to meet the financial requirements of the medical care of the disabled child.
Another study by Wolfe and Hill (1995) based on US, analyses data on female household heads(single mothers) and documents that child disability reduces their labour force participation. Similar
evidence for single mothers is also presented by Gould (2004) (based on US), where there is anegative correlation between mother’s work participation and the child disability in cases of timeintensive illness. Apart from labour force participation, existing studies have also analysed the impact
of child disability on the work hours of mothers. As usual, the evidence is mixed. While studies byPorterfield (2002) and Gould (2004), find disability to have a negative impact on the work hours ofmarried mothers, Salkever (1990) finds no significant impact of child disability on the work hours of
single mothers.
An important reason behind such varied evidence may lie in the fact that various studies use
different datasets, methods, and disability definitions. Powers (2003) provides an excellent survey ofthe studies on the subject along with their main findings. Addressing the mixed evidence, Powers(2003) applies multiple definitions of disability in both static and dynamic frameworks to analyse the3impact of child disability on maternal work activity and finds negative effect of child disability on
women who are either female heads or the wives of household heads in a static framework. However,in the dynamic framework, the negative effect is only evident in the case of female heads but not for
the wives. With respect to the working hours, Powers (2003) finds increase in the work hours overtime for the female heads.
It is important to note that all the reviewed studies are based on developed countries. Surprisingly,
studies assessing the impact of child disability on mother’s work activity for developing countries,
especially India, are absolutely rare.1 This study, where we investigate the association between childdisability and mother’s labour participation (and mother’s weekly hours of work) in India is importantfor several reasons. First, India is home to the largest number of children in the world, significantly
greater than China (UNICEF, 2011). However the health condition of Indian children remains
deplorable. Various studies have identified the poor state of average child health in India (see forexample, Singh et al., 2011; UNICEF, 2011). India contributes to more than 20 per cent of the total
child deaths in the world. Poverty, malnutrition, early motherhood, inadequate sanitation, andinsufficient health care services have extreme implications on child health leading to long term
chronic illness and disability (Singh et al., 2011, UNICEF, 2011).
According to Census 2001, India had 3.2 million children in the age group of 0-9 years and 4.4
million children in the age group of 10-19 years who were suffering from some form of disability.
This approximately constitutes to 1.6 per cent of the population of the children in the age group of 019 years. According to another estimate by NSSO (2002), in rural areas there were 0.5 per cent, 1.1
per cent, 1.5 per cent, and 1.7 per cent children in the age groups of 0-4 years, 5-9 years, 9-14 years,
and 15-19 years, respectively, who were suffering from at least one kind of disability. For urban areas
these figures stood a slightly less at 0.5 per cent, 1 per cent, 1.3 per cent, and 1.3 per cent,respectively.
As discussed earlier, presence of a disabled child in a household could either restrict or increase
the labour participation of the household members, especially mothers. One cannot be sure about thekind of relationship between child disability and maternal work participation in the Indian context,
precisely because there is no study till date which has investigated this relationship.
Given this gap in the existing literature, we in this paper, examine the impact of the presence of adisabled child on the maternal labour force participation for India. We provide separate analysis formothers residing in rural and urban areas as well as mothers who are household heads and mothers
who are wives of household heads. We also conduct the analyses for two indicators, namely, work
participation and weekly work hours. Our results show that there exists a significant positive
relationship between child disability and work participation of the mothers who are wives ofhousehold heads and reside in urban areas. However, for these mothers, the relationship between

4child disability and weekly hours of work is found to be negative (and significant). For the mothers inrural areas and mothers in urban areas who are household heads, our findings do not suggest any
significant relationship between child disabilities and maternal work participation (or weekly work
hours).
The remaining of the paper is organised as follows. The next section briefly presents the data,
variables, and some sample statistics. It is followed by a section on the multivariate analyses used in
the paper along with the main findings of the study. Finally, the study concludes with some discussion
on the main findings and a few concluding remarks.
2. Data, Variables and Sample Statistics
2.1 Data
We use the publicly available data from the Indian Human Development Survey (IHDS), conductedby the National Council of Applied Economic Research, New Delhi, India in collaboration with the
University of Maryland, in 2004-2005. The IHDS is a micro unit recorded and nationally
representative survey with an average response rate of 92 per cent. It is spread over 33 states andunion territories of India and covers 26,734 and 14,820 households in rural and urban areas,
respectively. It is unique in the sense that it was designed to measure different dimensions of humandevelopment with modules on education, health, employment, economic status, marriage, fertility,
gender relations, and social capital.
Since the main objective of our study is to examine the association between child disability andwork participation of the mothers, we primarily use the information on women and their children
collected through the education and employment modules of the household level questionnaire as wellas the health module of the individual level questionnaire (women’s questionnaire). In addition wealso use some household level information (for example, socioeconomic characteristics and family
structure) obtained through the household level questionnaire.
2.2 Outcomes of Interest - Maternal Work Participation and Weekly Hours of Work
The primary outcome of interest of the multivariate analyses of the present study is the work status of
the mothers, which we measure using two variables, namely labour force participation (workparticipation) and weekly hours of work. These two variables form the outcome variables for ourstudy. The IHDS survey directly provides information on the work status of individuals andcategorises it as ‘1’ (individual is working) if the individual is involved in 240 or more hours of workin a year, otherwise ‘0’ (not working). Similarly, weekly hours of work for women are also obtained
from the ‘Household Farm: Household Labour’, ‘Household Nonfarm Business’, and ‘Wage andSalary Work’ modules of the IHDS.

5

Our analysis is based on a sample of 27,857 women (aged 15-60 years at the time of survey) who
are either household heads or wives of household heads and who have at least one child aged 21 years
or less. The lower limit for women’s age is taken as 15 years because in India women get married at a
young age and therefore different demographic (or other) surveys (for example, IHDS, NFHS) set thelower limit of 15 years as the age of women for interviews related to fertility, health, gender relations,and birth history modules (IIPS & ORC Macro, 2007; Desai et al., 2010). The upper age limit is taken
as 60 years because in India it is the upper age limit for active employment.
The analysis is performed separately for the mothers who are married to household heads and themothers who are household head themselves. This is done because child disability can have a very
different kind of impact on these two types of mothers. Since, the majority of the mothers who arehousehold heads are either widows or divorcees; their work participation can be significantly different
from the mothers who are married to household heads. This is also in line with the published literatureon the subject (for example, see Kimmel, 1988; Powers, 2003). The analysis is performed separately
for urban and rural areas, because the nature of labour market is very different in these two areas.
Moreover, the family structure in India also differs by urban and rural areas. It is worthwhile to notethat the multivariate analyses (models, specifications, and the variables) presented in this paper are
well acceptable in the literature on the subject (for example, see Powers, 2003).
2.3 Child Disability
For identifying child disability, we follow the broader International Classification of Functioning,
Disability and Health (ICF) framework developed by The World Health Organization (WHO). The
WHO developed the International Classification of Impairments, Disabilities, and Handicaps in theearly 1980s, which was later revised and renamed as the International Classification of Functioning,
Disability, and Health (WHO, 2001; Mitra & Sambamoorthi, 2006). Typically, ICF is presented as anintegration of the medical and the social models of disability (WHO, 2001, p. 20): ‘ICF attempts toachieve a synthesis, in order to provide a coherent view of different perspectives of health from abiological, individual and social perspective’.
Defining disability as per the ICF model includes the three disability measures which arecommonly used in the applied disability research: measures based on impairments, functional
limitations and activity limitations. Impairment measures of disability focus on the presence ofimpairment intrinsic to an individual, for example, impairments that might include blindness,deafness, mental retardation, stammering and stuttering, and complete or partial paralysis. Functional
limitations refer to difficulties experienced with particular bodily functions such as seeing, walking,hearing, speaking, climbing stairs, lifting, and carrying, irrespective of whether the individual has an
impairment or not. Activity limitations are limitations in activities of daily living (ADL) such as
bathing or dressing. Activity limitations may also include participation limitation in major life

6

activities such as going outside the home, work or housework for working age persons, and school orplay for children (Mitra & Sambamoorthi, 2006, p. 4022-23).
To be precise, we have defined child disability as follows: First, for children aged 7 years andabove – a child is considered disabled if s/he is ‘unable’ or ‘finds it difficult’ to perform the following
activities of daily living; walking, going to toilet, dressing, hearing normal conversation, speaking
normally, seeing distant things (with glasses if any), and seeing near objects such as reading (withglasses if any). This information is directly obtained from the ‘Activity of Daily Living’ module of the
IHDS individual questionnaire. A child is also considered disabled if s/he is not able to perform
normal activities of daily living due to major illnesses, for example, High BP, Heart disease, Diabetes,
Leprosy, Cancer, Polio, Paralysis, Epilepsy, Mental illness, AIDS or other long term illnesses. 2
Second, for the children aged below 7 years – in the absence of direct module on the activities of dailyliving for this age group of children, we use the ‘Major Morbidity’ module of the IHDS individualquestionnaire and categorise a child as disabled if s/he is not able to perform normal activities of dailyliving due to major illnesses, for example, High BP, Heart disease, Diabetes, Leprosy, Cancer, Polio,
Paralysis, Epilepsy, Mental illness, AIDS or other long term illnesses. 3
The child disability variable hence constructed forms the first explanatory variable of primaryinterest in our study. Though, it is interesting to analyse how maternal work participation and weekly
hours of work are related to child disability, it is also interesting to investigate how the maternal work
participation as well as weekly work hours vary with the degree of disability of children. To
investigate the nature of relationship between maternal work participation (and weekly work hours)
and degree of disability of children, we construct another variable which captures the degree of
disability of children. For this purpose we divide the disabled children into two groups, children who
are disabled but not severely disabled and children who are severely disabled. Therefore, the degree ofchild disability variable is categorised into three levels, not disabled (if child does not have adisability), disabled but not severely disabled, and severely disabled (if child is severely disabled).
From the sphere of all disabled children, children who are ‘unable’ to perform the following activities
of daily living; walking, going to toilet, dressing, hearing normal conversation, speaking normally,
seeing distant things (with glasses if any), and seeing near objects such as reading (with glasses ifany); or children who are not able to perform normal activities of daily living due to Leprosy, Cancer,
Polio, Paralysis, Epilepsy, Mental illness, and AIDS are categorised as severely disabled.
Identification of severe disability as above is in line with the US Census Bureau’s guidelines (McNeil,
1997, p.7, 2001). Our identification of disability and severe disability is also similar to Powers’ (2003)
definition 1 of disability and the definition of severe disability, respectively. Hence defined, thedegree of child disability forms another explanatory variable of primary interest. It may be noted that,
we conduct the analyses based on the variables child disability (dichotomous) and degree of childdisability (three categories) separately.4

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2.4 Control Variables
Drawing from the published literature on the determinants of mother’s work participation (Powers,
2003; Lu and Zuo, 2010) and taking into account the Indian context, we include a number of controls.
These can be broadly classified into four groups; first group relates to child specific characteristics,
second is related to the maternal characteristics, third pertains to father’s characteristics, and fourth isrelated to the household characteristics. Child specific characteristics include the age, the square ofage, and the gender of the youngest child. Including gender of the youngest child is a departure fromthe existing literature (mostly based on developed countries) but we include it given the compelling
evidence of discrimination against female children in providence for basic necessities in India (seePande & Astone, 2007 for an exhaustive review).
The variables related to maternal characteristics include age, the square of the age, years ofcompleted schooling (categorised into four levels - no formal schooling, schooling up to primary (5years), more than primary but up to secondary (10 years), and more than secondary), and health status
which is taken as dichotomous and is captured by the variable whether the mother received treatment(or advice) for a major illness in the last year.
We also include father’s characteristics by using data on his age, square of his age, and his levelof schooling. As in the case of mothers, the schooling of fathers is also divided into the four
categories of no formal schooling, schooling up to primary (5 years), schooling more than primary but
up to secondary (10 years), and schooling more than secondary. In the multivariate analyses, no
education (both in case of mothers and fathers) is taken as the reference category. It may be noted thatin the analyses based on the sample of mothers who are household heads, fathers’ characteristics are
not included in the models. It is in line with the existing literature (Powers, 2003).
To characterise the households we use dummies for caste and religion, number of children (age less than or up to 21 years), number of other adult (age - greater than 21 years) females, and thenumber of adult males in the household.

The categorical variable for caste is coded into thecategories of ‘Scheduled’ groups (‘Scheduled Caste’ (SC) and ‘Scheduled Tribes’ (ST)), ‘Other
Backward Classes’ (OBC), and ‘Other Castes’ (OC; taken as reference) which are meaningful
representations of the Indian social fabric along caste lines.5 Religion is also divided into three
categories, namely, ‘Hindu’ (the majority religious group in the Indian population; taken as thereference category), ‘Muslim’ (largest group among religious minorities), and ‘Others’. ‘Muslims’ lag
behind their ‘Hindu’ and ‘Others’ counterparts in education, employment and income (Government ofIndia, 2007). Of note is the fact that the different geographical regions of India are at different levelsof economic and demographic development, with the regions of south and west generally better thantheir other counterparts (Bose, 1991; Bhat & Zavier, 1999; Singh, 2011). To control for the regional
effects, following Singh (2011), we divide India into the regions of North, Central, East, North East,8

West, and South and include the regional dummies in all the models. The list of variables and thesample statistics are presented in Table 1.
2.5 Sample Statistics
Some stylised observations can be noted from Table 1 which in addition to elucidating the variables
used in our models, also presents the sample statistics for the rural as well as the urban samples for thetwo groups - mothers who are wives of household heads (henceforth referred as wives) as well as
mothers who are the household heads themselves (henceforth referred as household heads). It can beobserved that the work participation of mothers in rural areas is substantially higher than that of urban
areas. It can also be observed that among the two types of mothers, the work participation of thehousehold heads is higher than that of the wives. As far as instances of child disability is concerned,
the figures are quite similar for the wives in rural (4.58%) and urban areas (4.33%) as well as for thehousehold heads in the two areas (5.25% and 5.24%). Further, it may be observed that the rural andurban samples are comparable within the respective groups (wives and household heads) in terms of
demographic factors like age of the youngest child, age of the mothers, age of the fathers, number ofadult males, number of other adult females, and the number of children in the household. Moreover,the educational attainment (in terms of more than 5 years of schooling) of the mothers in urban areas
is substantially higher than that of the mothers in rural areas.
Table 1. Sample Statistics
Rural--------------------------------------Wives
Female Household
Heads

Urban
-------------------------------------Wives
Female Household
Heads

Dependent Variable
Work participation (%)

72.1

80.08

23.10

56.63

Usual weekly hours (mean)

10.8

15.89

5.58

20.68

Has a disabled (including severely
disabled) child (%)
Has a disabled but not a severely
disabled child (%)
Has a severely disabled child (%)

4.58

5.25

4.33

5.24

2.18

2.54

2.07

3.27

2.40

2.70

2.26

1.96

Age of the youngest child (yrs; mean)

8.94

11.90

9.32

13.49

Youngest child is female (%)

40.62

41.56

43.42

44.19

Independent variables
Child related variables

Maternal Characteristics

9

Age in yrs (mean)

36.54

41.72

36.01

42.09

No formal schooling (%)

62.50

68.93

31.52

40.75

≤ 5yrs of formal schooling (%)

16.03

14.59

14.88

14.73

5 yrs < formal schooling ≤ 10 yrs (%)

18.49

14.10

36.13

31.26

Formal schooling > 10 yrs (%)

2.98

2.38

17.47

13.26

Received medical treatment (advice)for major illness in last year (%)
Father’s characteristics

7.89

10.98

9.15

15.55

Age in yrs (mean)

41.99

41.70

No formal schooling (%)

70.13

45.33

≤ 5yrs of formal schooling (%)

20.50

24.32

5 yrs < formal schooling ≤ 10 yrs (%)

8.18

22.92

Formal schooling > 10 yrs (%)

1.19

7.43

Household Characteristics
Composition
Number of adult males (mean)

1.30

0.33

1.28

0.45

Number of other adult females(mean)
Number of children (age ≤ 21 yrs;
mean)
Caste

0.30

0.29

0.26

0.31

3.00

2.72

2.57

2.37

OBC (%)

39.93

41.07

38.42

37.97

SC/ST (%)

34.98

36.23

20.53

21.11

OC (%)

25.09

22.70

41.04

40.92

Hindu (%)

81.47

78.11

77.37

70.70

Muslim (%)

10.64

11.80

16.26

20.29

Other religion (%)

7.89

10.08

6.37

9.00

N

16363

1220

9663

611

Religion

Source: Authors’ computations based upon IHDS (2004-05).

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3. Multivariate Analyses and Results
3.1 Maternal Work Participation
We use binary logistic models for mother work participation (since it is dichotomous in nature). We
conduct the analyses at two levels for both, the rural wives and rural household heads as well as theurban wives and urban household heads.
At the first level we conduct the regression analysis taking child disability as a binary variable,that is, ‘1’ if the mother has a disabled child and ‘0’ otherwise. At the second level we take the degreeof disability into account which is categorised into ‘no disabled child = 0’, ‘has a disabled but not aseverely disabled child = 1’, and ‘has a severely disabled child = 2’. The control variables include thechild level, maternal level, father’s level (only in case of wives), and household level characteristics
as discussed in the ‘control variables’ subsection of the previous section.
The odds ratios from the logistic models for the rural areas are presented in Table 2. In the rural
sample, for both the wives (model 1) as well as mothers who are household heads (model 3) the
maternal work participation shows an insignificant (positive in nature) relationship with childdisability. The relationship remains insignificant even when degree of disability is taken into account(models 2 and 4).

Table 2. Odds Ratio estimates of Logistic Regression Models for the Dependent Variable – MaternalWork Participation (Yes = 1, No = 0): Rural India

Has a disabled child (Ref: no disabled child)

Wives----------------------------(1)(2)
1.03(0.09)

Female Household Heads-------------------------------(3)
(4)
1.548
(0.557)1.086***(0.014)
0.997***(0.001)
0.994(0.037)1.230(0.164)0.884(0.105)1.086***(0.014)
0.997***(0.001)
0.994(0.037)

1.180***(0.064)
0.993***(0.002)0.895(0.140)1.478(0.662)1.629(0.928)1.180***(0.064)
0.993***(0.002)0.896(0.140)1.105***(0.026)0.999***(0.000)1.105***(0.026)0.999***(0.000)1.052(0.078)0.999(0.001)

1.052(0.078)0.999(0.001)0.679***

0.679***

0.509***

0.508***

Severity of child disability (Ref: no disabledchild)
Has a disabled but not severely disabled childHas a severely disabled childAge (youngest child)
Square of age (youngest child)
Youngest child female (Ref: male)
Maternal Characteristics
Age
Square of Age
Education (Ref: no formal schooling)≤ 5yrs of formal schooling11

5 yrs < formal schooling ≤ 10 yrs
Formal schooling > 10 yrs
Received medical treatment (advice) for a major
illness in last year
Father’s Characteristics
Age
Square of Age
Education (Ref: no formal schooling)≤ 5yrs of formal schooling
5 yrs < formal schooling ≤ 10 yrs
Formal schooling > 10 yrs
Household Characteristics
Composition
Number of other adult females
Number of adult males
Number of children (age ≤ 21 yrs)
Caste (Ref: OC)
OBC
SC/ST

(0.035)0.499***(0.026)
0.371***(0.040)0.776***(0.035)0.499***(0.026)
0.371***(0.040)0.773***(0.108)0.288***(0.060)0.251***(0.107)0.776(0.108)0.289***(0.060)0.251***(0.107)0.777(0.051)(0.051)(0.178)(0.178)1.062***(0.022)0.999***(0.000)1.062***(0.022)0.999***(0.000)0.794***(0.038)0.725***(0.048)0.563***(0.090)0.793***(0.038)0.725***(0.048)0.564***(0.090)1.051(0.036)0.860***(0.029)1.048***(0.016)1.052(0.036)0.860***(0.029)1.048***(0.016)1.242(0.170)0.686***(0.092)0.964(0.059)1.241(0.170)0.686***(0.092)0.964(0.059)1.003(0.049)1.043(0.056)1.004(0.049)1.043(0.056)1.057(0.219)1.337(0.313)1.058(0.219)1.337(0.313)

Religion (Ref: Hindu)
Muslim0.557***
0.557***
0.549***
0.550***(0.035)(0.035)(0.124)(0.124)
Other religion
0.859**
0.858**
0.567**
0.567**(0.059)(0.059)(0.144)(0.144)
Regional Dummies
Yes
Yes
Yes
Yes
N
16363
16363
1220
1220
Notes: Figures in parenthesis are robust standard errors. ***Significant at the 1% level; ** significant at the 1%
level; * Significant at the 10% level.
Source: Authors’ computations based upon IHDS (2004-05).

Among the control variables of interest, it can be seen that the maternal work participation (forboth, the wives as well as household heads) shows a significant but nonlinear (‘inverted U’) kind of
relationship with the age of the youngest child. A similar kind of relationship also exists between thematernal work participation and mother’s age. However, the relationship is significant only in the caseof wives. It makes sense because most of the women who are working in rural areas are either self
employed in agriculture or are agricultural labourers. Given, the physical nature of this work and the12age (15 - 60 yrs.) of the women in our sample, it is possible that the participation will increase withthe age initially (in the earlier ages) but will decrease as the women move from being young to older
ages. But in the case of women who are household heads, the relationship is insignificant because
irrespective of their age they have to work in order to take care of the financial needs of their families.
It is surprising to observe that the maternal work participation is decreasing in the education of
mothers (models 1, 2, 3, and 4). It will not seem surprising if seen in the light of the Indian social
fabric, the correlation between education of wives and husbands, and the correlation between
education and income in India. In India, education of wives and husbands is highly correlated andeducation itself is strongly correlated with the occupation and therefore income. The increasing
completed years of schooling of mothers is nothing but an indicator of the increasing economic statusof the households to which they belong. Combine this with the social norms in rural India, where
women step out of the house to work in the fields only when the economic status of the household issuch that there is no other option but for the women to come out and work.6 Further, mothers who
received medical treatment (or advice) for a major illness in the last year are less likely to work
(significant only in the case of wives) than women who didn’t receive any treatment (or advice) for
the same. The relationship is not significant for mothers who are household heads probably due to thefact that they have to work despite their poor health status because in the absence of other earning
members (mostly husbands) they are bounded by the financial needs of their households. Moreover,the maternal work participation (for both, wives as well as household heads) shows a negative andsignificant relationship with the number of adult males in the household. It is not unnatural because
more number of adult males means more number of earning hands and therefore less chances for the
women to come out of house and work.
Table 3 reports the odds ratios from the logistic models for the maternal work participation for
urban areas. It is interesting to note that, unlike rural areas, for the women who are wives ofhousehold heads, the maternal work participation is positively (significant at the 5% level) related tothe presence of child disability (model 1). The wives who have a disabled child are 1.27 times as
likely to work as the wives who do not have a disabled child. When severity of disability is taken into
account (model 2), then wives who have a disable child (but not a severely disabled one) are 1.41
times as likely to work as the wives who do not have a disabled child. However, the positive nature of
relationship between child disability and maternal work participation is not significant in the case of aseverely disabled child. Of note is the finding that the relationship (though positive in nature) between
child disability and maternal work participation is not significant in the case of mothers who arehousehold heads (models 3 and 4).

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Table 3. Odds Ratio estimates of Logistic Regression Models for the Dependent Variable – MaternalWork Participation (Yes = 1, No = 0): Urban India

Has a Disabled child (Ref: no disabled child)

Wives------------------------------(1)(2)
1.267**(0.147)

Severity of child disability (Ref: no disabled child)Has a disabled but not severely disabled child1.088***(0.021)
0.996***(0.001)
1.015(0.051)1.408**(0.226)
1.149(0.188)1.088***(0.021)
0.996***(0.001)1.014(0.051)

1.153*(0.098)0.994*(0.003)1.323(0.241)1.059(0.511)1.491(0.915)
1.152*(0.098)0.994*(0.003)1.323(0.241)1.130***(0.046)0.999**(0.001)1.130***(0.046)0.999**(0.001)1.073(0.125)0.999(0.001)1.073(0.125)0.999(0.001)0.670***(0.052)0.457***(0.032)0.802**(0.070)0.956

0.670***(0.052)0.457***(0.032)0.803**(0.070)
0.954

0.843
(0.233)0.387***(0.092)1.350(0.436)
0.895

0.843
(0.233)0.385***(0.091)1.342(0.433)0.897(0.085)(0.085)(0.229)(0.230)0.951(0.033)1.000(0.000)0.951(0.033)1.000(0.000)0.667***(0.044)0.615***(0.045)0.795**(0.087)

0.666***(0.044)0.614***(0.045)0.793**(0.087)1.116**(0.053)0.887**(0.043)

1.115**(0.053)0.888**(0.043)1.111(0.187)0.533***(0.084)1.104(0.187)0.533***(0.084)

Has a severely disabled childAge (youngest child)
Square of Age (youngest child)
Youngest child Female (Ref: male)
Maternal Characteristics
Age
Square of age
Education (Ref: no formal schooling)≤ 5yrs of formal schooling
5 yrs < formal schooling ≤ 10 yrs
Formal schooling > 10 yrs
Received medical treatment (advice) for a major
illness in last year
Father’s Characteristics
Age
Square of Age
Education (Ref: no formal schooling)≤ 5yrs of formal schooling
5 yrs < formal schooling ≤ 10 yrs
Formal schooling > 10 yrs
Household Characteristics
Composition
Number of other adult females
Number of adult males

Female Household Heads-------------------------------(3)
(4)
1.208
(0.467)

14

Number of children (age ≤ 21 yrs)
Caste (Ref: OC)
OBC
SC/ST

1.101***(0.024)

1.102***(0.024)0.991(0.076)0.989(0.075)1.245***(0.077)1.418***(0.102)

1.245***(0.077)1.419***(0.102)1.042(0.227)2.367***(0.685)1.041(0.227)2.371***(0.687)

Religion (Ref: Hindu)
Muslim0.776***
0.775***
0.709
0.710
(0.060)(0.060)(0.179)(0.179)Other religion
1.093
1.095
1.793
1.808
(0.115)(0.115)(0.702)(0.711)
Regional Dummies
Yes
Yes
Yes
Yes
N
9663
9663
611
611
Notes: Figures in parenthesis are robust standard errors. ***Significant at the 1% level; ** significant at the 1%
level; * Significant at the 10% level.
Source: Authors’ computations based upon IHDS (2004-05).

The nature of relationship in the urban areas between maternal work participation and the control
variables of interest (for example, age of the youngest child, age of the mothers, education of themothers, and number of adult males) is similar to that of rural areas. The notable exception is theresult that the negative nature of relationship between maternal work participation and the poor healthstatus of wives is not insignificant.

3.2 Maternal Weekly Work Hours
Before estimating the effect of child disability on weekly hours of work, we tested for the existence ofself selection bias on account of the fact that the weekly work hours are non-observable for themothers who did not participate in the labour market. We tested for the self selection bias using
Heckman’s two step sample selection model (Heckman, 1979). However, the inverse mills ratio cameout to be insignificant; suggesting the absence of any significant self selection bias.7 We therefore
present the estimates of the determinants of weekly work hours obtained using OLS method for only
those mothers, who participated in the labour market.
The estimation is once again carried out separately for wives and household heads and also forrural and urban areas. It is also carried out at two levels; the first level includes child disability as adichotomous variable whereas, the second level takes into account the degree of disability of thechildren. The control variables included in the model are same as those included in the maternal work
participation models presented earlier.

15

Table 4. Coefficient estimates of OLS Regression Models for the Dependent Variable – Maternal
Weekly Work Hours: Rural India

Has a Disabled child (Ref: no disabled child)

Wives------------------------------(1)
(2)
0.053
(0.569)Severity of child disability (Ref: no disabledchild)
Has a disabled but not severely disabled child

0.319***(0.085)-0.016***(0.004)0.297(0.248)-0.687(0.798)0.773(0.788)0.318***(0.085)-0.016***(0.004)0.298(0.248)0.364(0.405)-0.020(0.017)0.736(1.012)-1.349(3.074)0.738(2.903)0.357(0.406)-0.020(0.017)0.744(1.012)0.081(0.172)-0.002(0.002)0.080(0.172)-0.002(0.002)0.350(0.554)-0.006(0.006)0.334(0.555)-0.006(0.006)-0.281(0.356)-1.148***(0.376)5.022***(0.891)-0.427-0.281(0.356)-1.148***(0.376)5.025***(0.891)-0.4070.935(1.498)1.333(1.656)-3.220(3.714)-3.697**0.902(1.500)1.324(1.657)-3.268(3.717)-3.700**(0.460)(0.460)(1.630)(1.630)0.115(0.154)-0.001(0.002)-0.504(0.240)-0.225(0.093)-1.781***(0.329)-0.783(0.499)2.505*(1.315)-1.777***(0.329)-0.777(0.499)2.492*(1.315)-0.234(0.227)-0.505**-0.232(0.227)-0.504**-0.545(0.945)-0.743-0.576(0.948)-0.742

Has a severely disabled childAge (youngest child)
Square of Age (youngest child)
Youngest child Female (Ref: male)
Maternal Characteristics
Age
Square of age
Education (Ref: no formal schooling)≤ 5yrs of formal schooling
5 yrs < formal schooling ≤ 10 yrs
Formal schooling > 10 yrs
Received medical treatment (advice) for amajor illness in last year
Father’s Characteristics
Age
Square of Age
Education (Ref: no formal schooling)≤ 5yrs of formal schooling
5 yrs < formal schooling ≤ 10 yrs
Formal schooling > 10 yrs
Household Characteristics
Composition
Number of other adult females
Number of adult males

Female Household Heads-------------------------------(3)(4)-0.244(2.141)

16

Number of children (age ≤ 21 yrs)
Caste (Ref: OC)
OBC
SC/ST

(0.240)-0.223**(0.093)(0.240)-0.225**(0.093)(1.011)-0.962**(0.407)(1.011)-0.963**(0.407)0.559*(0.337)1.752***(0.359)0.559*(0.337)1.756***(0.359)-1.680(1.426)1.611(1.497)-1.664(1.427)1.614(1.497)

Religion (Ref: Hindu)
Muslim-2.627***-2.626***-0.981-0.977(0.465)(0.465)(1.792)(1.793)
Other religion-2.211***-2.204***-3.421*-3.411*(0.501)(0.501)(1.930)(1.930)Constant
8.587***
8.565***
14.36914.757(2.297)(2.297)(10.960)(10.992)
Regional Dummies
Yes
Yes
Yes
Yes
N
11797
11797
977
977
Notes: Figures in parenthesis are robust standard errors. ***Significant at the 1% level; ** significant at the 1%
level; * Significant at the 10% level.
Source: Authors’ computations based upon IHDS (2004-05).

Table 4 presents the estimates for rural areas. For both, wives as well as household heads, thematernal weekly work hours is not significantly related to the presence of a disabled child (models 1
and 3). The coefficient is positive for wives, whereas for household heads, it is negative. Whendegree of disability is taken into account, then also the relationship remains insignificant (models 2
and 4). For wives (models 1 and 2), weekly work hours - is positively (significant) related to their (aswell as their husbands’) formal schooling if more than 10 years; seem to follow an ‘inverted- U’ kindof relationship with the age of youngest child; and is negatively affected by increase in number ofadult males and number of children. Caste and religious affiliation also affects the weekly work hoursof these mothers. When we consider the mothers who are household heads, only three variables affecttheir weekly work hours significantly. To be precise, their poor health status, (increase in) total
number of children in the household and belonging to non-Hindu and non-Muslim religions (reference– Hindu) affects their weekly work hours negatively. The insignificant effect of most of the importantvariables on the weekly work hours of mothers who are household heads and are participating in thelabour market points to one thing, that is, these women do not have much choice when it comes to the
supply of weekly work hours as their households depend on them for earnings.

17

Table 5. Coefficient estimates of OLS Regression Models for the Dependent Variable – Maternal
Weekly Work Hours for those who participated in labour market: Urban India

Has a Disabled child (Ref: no disabled child)

Wives---------------------------------(1)(2)-3.558**(1.657)

Female Household Heads-------------------------------(3)
(4)
5.467
(4.004)0.338(0.285)-0.017(0.013)0.291(0.760)-5.241**(2.340)-1.970(2.276)0.354(0.286)-0.018(0.013)0.286(0.760)2.234***(0.809)-0.096***(0.033)-2.691(1.849)5.524(5.002)
5.370(6.414)2.235***(0.811)-0.096***(0.033)-2.691(1.852)

1.866***(0.606)-0.022***(0.007)1.873***(0.606)-0.023***(0.007)-0.428(1.235)0.005(0.014)-0.429(1.239)0.005(0.014)0.522(1.157)0.250(1.034)11.484***(1.361)
0.755

0.532
(1.157)0.231(1.034)
11.465***(1.361)0.793-2.314(2.772)0.466(2.450)1.561(2.852)1.024-2.315(2.776)0.466(2.454)1.563(2.858)1.022(1.316)(1.316)(2.734)(2.740)-1.259**(0.521)0.013**(0.005)-1.265**(0.521)0.013**(0.005)-0.808(1.022)-0.061(1.163)1.314(1.777)-0.744(1.024)-0.048(1.163)1.344(1.777)0.174(0.698)-1.499**0.198(0.698)-1.506**-0.718(1.882)-2.649-0.716(1.889)-2.650

Severity of child disability (Ref: no disabledchild)
Has a disabled but not severely disabled childHas a severely disabled childAge (youngest child)
Square of Age (youngest child)
Youngest child Female (Ref: male)
Maternal Characteristics
Age
Square of age
Education (Ref: no formal schooling)≤ 5yrs of formal schooling
5 yrs < formal schooling ≤ 10 yrs
Formal schooling > 10 yrs
Received medical treatment (advice) for amajor illness in last year
Father’s Characteristics
Age
Square of Age
Education (Ref: no formal schooling)≤ 5yrs of formal schooling
5 yrs < formal schooling ≤ 10 yrs
Formal schooling > 10 yrs
Household Characteristics
Composition
Number of other adult females
Number of adult males

18

Number of children (age ≤ 21 yrs)
Caste (Ref: OC)
OBC
SC/ST

(0.730)-0.839***(0.314)(0.730)-0.843***(0.314)(1.699)-2.223***(0.823)(1.702)-2.222***(0.826)-1.119(0.960)1.652(1.129)-1.168(0.961)1.623(1.129)-2.501(2.340)-2.876(2.625)-2.501(2.343)-2.879(2.634)

Religion (Ref: Hindu)
Muslim-2.088*-2.121*1.063
1.064(1.151)(1.151)(2.751)(2.756)
Other religion
1.090
1.035
-1.798-1.800(1.646)(1.647)(3.180)(3.187)
Constant
15.891**15.89347.86147.881(7.953)(7.953)(25.083)(25.143)
Regional Dummies
Yes
Yes
Yes
Yes
N
2232
2232
346
346
Notes: Figures in parenthesis are robust standard errors. ***Significant at the 1% level; ** significant at the 1%
level; * Significant at the 10% level.
Source: Authors’ computations based upon IHDS (2004-05).

The respective estimates for the urban areas are reported in Table 5. Unlike rural areas, we findsignificant (significant at the 5% level) negative relationship between child disability and maternal
weekly work hours of mothers who are wives of household heads. Presence of a disabled childdecreases the weekly work hours of these mothers by about 3.6 hours. This implies that for wives who
participate in labour market despite of having disabled children, seem to compensate the increased
participation by supplying less labour through decreased weekly hours of work. Of note is the fact that
we found positive (and significant) relationship between maternal work participation and childdisability for wives (Table 3, model 1 and 2). When severity of disability is taken into account (model2), then wives who have a disable child (but not a severely disabled one) are likely to supply 5.2 lessweekly hours of work (significant at the 5% level) as the wives who do not have a disabled child. We
also find wives weekly hours of labour supply follow an ‘inverted U’ shape curve with their as well as
their husbands’ age. It is negatively affected by number of adult males and children in the household
but is positively affected by their formal education if it is more than 10 years. However, in the case ofhousehold heads, we find no significant relationship between child disability and the maternal weekly
work hours. The nature of relationship between the maternal weekly work hours and the control
variables of interest comes out to be more or less insignificant for mothers, who are household heads.
However for the household heads, their weekly hours of work seem to increase with age of youngest
children but decrease for higher levels of their age (inverted-U).
4. Conclusions
In this paper, we provide the first estimates of the association between child disability and maternal
work participation as well as maternal weekly work hours for India. While doing so, we provide the19estimates separately for the mothers who are wives of household heads and those who are household
heads themselves. We also provide separate analyses for the rural and the urban areas of India. In
addition, we also conduct the analyses at two levels; first by taking child disability as a binary
outcome and second by taking severity of child disability into account.
In rural areas, we find that the presence of a disabled child does not have any significant
association with the work participation and the weekly work hours of the wives as well as thehousehold heads. Severity of disability is also found to have an insignificant relationship with thework choice of both the wives and the household heads. This insignificant relationship between childdisability and maternal work participation (and weekly work hours) can be due to the fact that thefemales in rural households engage themselves in traditional (agriculture related) occupations (Desai& Jain, 2004). Since these activities can be taken up while keeping the child nearby, maternal work
participation may not be affected by child disability. Also the structure of the rural society in India is
integrated with the community and the networks. Hence, it is also seen that the child is taken care by
the neighbouring households and community as a group, which acts like a social insurance for thehouseholds (Munshi & Rosenzweig, 2006, 2009). Another point to ponder upon is the health careinfrastructure and the cost of health care in rural areas. Only about 25 per cent of the health careinfrastructure, medical man power and other health resources are concentrated in the rural areas (Patilet al., 2002). Due to the traditional beliefs and the absence of proper health care infrastructure, a large
proportion of rural population still uses the traditional medication system as well as the services ofquacks which are relatively cheaper (Kumar et al., 2007). Since, in these cases the cost of medicalcare is not very high, it may not impose significant financial burden on the households with a disabledchild and which in turn may not compel the women of the households to work. The above discussion
may plausibly explain why child disability may not significantly affect maternal work decisions inrural areas of India.
However, in the case of urban households, we find that the presence of a disabled child has asignificant positive association with the work participation of those mothers who are wives ofhousehold heads. This difference between the nature of association of child disability with maternal
work participation in rural and urban areas may be explained by the high cost of living (including
health care) in the urban areas. Of note is the finding that even in urban areas the maternal work
participation of mothers who are household heads and have at least a disabled child is not
significantly different from the mothers who are also household heads but do not have a disabledchild. The reason may lie in the fact that in the case of mothers who are household heads, theresponsibility of the financial needs of the households lie with the mothers and they have to work inorder to fulfil the daily needs of the household members irrespective of whether they have a disabledchild or not. Another point of interest is that the relationship between maternal weekly hours of work(for non- household head mothers who participated in labour market) and disability of children isfound to be negative and significant. This signifies that the mothers who participate in labour market

20

due to disability of children in the households seem to compensate the increased participation byworking less during the week.
It is surprising to note that in a country like India which has achieved unprecedented economic
growth during the past two decades and which has social schemes like pension for widows andfreedom fighters, a social scheme in terms of financial aid to households (especially households
headed by widows and divorced mothers) with disabled children, like the SSI (supplementary security
income) disability benefits in the US is missing. The demand for such a scheme is not unjustified if
we consider the following. We found that in the case of female household heads, the maternal work
participation (both rural and urban areas) of mothers who have received treatment (or advice) in thelast year for a major illness is not significantly different from the mothers (again household heads)
who did not receive any. Also, in the urban areas, even the weekly work hours of the mothers who arehousehold heads and received treatment (or advice) for a major illness in the last year is not
significantly different from those mothers who are also household heads but did not receive anytreatment or advice for a major illness. This shows the compulsion of the mothers who are household
heads to work irrespective of their poor health status. On top of this if these mothers have a disabledchild then their plight can be very worrisome.
Though the Government of India provides some tax benefits to the individuals with a dependent
disabled individual, it is fundamentally different from providing financial assistance to the mothers of
disabled children, if seen in the context of maternal work participation. First, to get a tax exemption
benefit the mother has to participate in work activity and earn, which may not be desirable in manycases, especially in the cases where the disabled child needs substantial attention and care. Second,
the income of females up to a certain upper limit is already completely exempted from income tax, so
any mother who has a disabled child and is earning less than this limit will not get any advantage outof the tax benefits based on the disability criteria.8 Further, in most of the cases of mothers who are
wives of household heads and have a disabled child, it is the household head (or the husband) who isthe earning member, so the tax benefits on account of the disability criteria will go to the household
head (husband). Whereas, there is substantial evidence in literature which says that the welfare (interms of, say, education and health) of children increases with the increase of direct control ofmothers over the household income (Thomas, 1990; Hoddinott & Haddad, 1995; Phillips & Burton,
1998; Duflo, 2003; Seebens, 2009). So, based on our findings and the above discussion we advocate
the policy of providing financial assistance directly to the mothers (especially the mothers who arehousehold heads) of disabled children.

Notes
1. To the best of our search, we could not find even a single study which has assessed the aforesaid
relationship for India.

21

2. This information is obtained from the ‘Major Morbidity’ module of the individual questionnaire of
IHDS.
3. This information is also obtained from the ‘Major Morbidity’ module of the individualquestionnaire of IHDS.
4. These two variables are never used simultaneously in any model.
5. It may be noted that the SCs and STs have suffered from severe social exclusion and discriminationfrom historical times and lag behind the OCs as well as OBCs in the different indicators of welfare.
OBCs have also suffered from discrimination but to a lesser extent than SCs and STs. They also lag
behind OCs in the indicators of welfare (Deshpande, 2011).
6. The average monthly per capita consumption expenditure (MPCE) for women who have no formal
schooling is 657.38 Indian Rupees compared to the average MPCE of 1834.85 Indian Rupees for the
women who have more than 10 years of completed schooling. We could not include MPCE or wealthin the regression analyses because it will lead to multicollinearity problems.
7. The results can be provided upon request.
8. Presently (year, 2011) this limit for females is 0.19 million Indian Rupees annually (The Economic
Times, 2011). Also, agriculture income in India is exempted from income tax as per the Income Tax
Act of India. So, the women involved in agricultural activities in rural areas cannot benefit from tax
exemptions based on the disability criteria.
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