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RESEARCH ARTICLE
Migration and empowerment: the experience of women in households
in India where migration of a husband has occurred
Babita Sinha*, Smita Jha and Nalin Singh Negi
Department of Humanities & Social Sciences, IIT Roorkee, Roorkee-247667, India
(Received 19 March 2010; final version received 21 June 2011)
Women’s empowerment is a major concern in the developing world and is emerging as
an important indicator of the development of a society as well as the status of women.
In this paper, we study empowerment of women in families which have experienced the
migration of their male members. A direct relationship between migration of a husband
and a woman’s empowerment is difficult to establish. Nevertheless, it is worthwhile
examining whether women have experienced any change in their freedoms in terms of
decision making, mobility and restrictions. Our measure of women’s empowerment is
based mainly on three indicators, viz. their decision-making powers, restrictions placed
on them and their mobility. Analysis of these three indices of women’s empowerment
has been achieved through multinomial logistic regression models on data from India’s
2005–2006 National Family Health Survey-3 (NFHS-3). The findings of this study
show that out-migration of men has not had a significant impact on the emancipation of
women. The common factors which increase the decision-making power and mobility
of women and lessen the social restrictions placed on them are age, their educational
attainment, marital duration, occupation and residence in urban areas.
Keywords: women’s empowerment; migration; decision making; feminist approach to
economics
Introduction
Women’s empowerment is a major concern in the developing world and is emerging as an
important indicator of the development of a society as well as the status of women in that
society which affects their access to social and economic opportunities. Lack, or low
levels, of empowerment is not solely a detriment to the woman in question since it is also
felt by the family and extends to the community. As Sen (2001) states
The expansion of women’s capabilities not only enhances women’s own freedom and
well-being, but also has many other effects on the lives of all. An enhancement of women’s
active agency can, in many circumstances, contribute substantially to the lives of all people –
men as well as women, children as well as adults.
John Snow Inc. (1990) defines empowerment as the ability to take effective action.
In particular, it is the ability to make and carry out significant decisions affecting one’s
own life and the lives of others. The Beijing Declaration (1995) states that
ISSN 0958-9236 print/ISSN 1465-3869 online
q2012 Taylor & Francis
http://dx.doi.org/10.1080/09589236.2012.639551
http://www.tandfonline.com
*Corresponding author. Email: bsinha08@gmail.com
Journal of Gender Studies
Vol. 21, No. 1, March 2012, 61–76
Women’s empowerment and their full participation on the basis of equality in all spheres of
society, including participation in the decision-making process and access to power, are
fundamental for the achievement of equality and development. (Cited in DAC 1998)
According to Schuler and Hashemi (1993), the process of empowerment begins at the
level of a woman’s individual consciousness and becomes externalized through greater
physical mobility, remunerated labour, a strong role in the household and, eventually,
meaningful participation in the wider community.
The genesis of the idea of women’s empowerment
The concept of woman’s empowerment is not recent – during the nineteenth and twentieth
centuries women launched movements for liberation, suffrage and equality. Mary
Wollstonecraft, for example, remarked that women could not be measured by men’s
standards (Lewis 2009). J.S. Mill stressed the importance of women’s education and
freedom in his books Subjection of women (1869) and On liberty (1859).
Feminism is a broad social enterprise striving for equality for all as well as emphasizing
the importance of values such as co-operation, tolerance, nurturance and the freedom for
each person to achieve her or his potential. Despite the advances made, women are still
systematically excluded from positions of power and influence. On average in North
America, women who work full time still only earn 59 cents for every dollar a man makes
and female college graduates statistically earn less than males with only an eighth-grade
education (Drinkwater 2005).
Hochschild (1983) observed that while a remarkable change was underway in the
increased likelihood that women, including the mothers of young children, would work in
formal employment, a much less dramatic change would occur on the home front. Women
are more likely to do paid work but men are not more likely to share domestic work and
child care. According to Hochschild this results in an ‘extra-burden’ or ‘second-shift’ in
which women perform the equivalent of an ‘extra month of twenty-four-hour days a year
of labour’ (1983, p. 56). Rajan and Mathur (1995) state that medical and health services
are not equally accessible to men and women. Globally, for every three men who use a
medical facility, only one woman does so. This is not because women enjoy better health
but because of the low importance accorded to women by themselves and others (Ramji
2005).
As with other branches of economics and the social sciences, feminist economics is
evolving in response to new research as well as new economic developments. During the
1980s and 1990s, the social sciences experienced major transformations – among the most
notable were two separate developments: the growth in feminist-oriented scholarship and
immigration research. Gender is one of the fundamental social relations anchoring and
shaping immigration patterns (Drinkwater 2005) and immigration is one of the most
powerful forces disrupting and realigning everyday life. However, in the majority of
studies on international migration, basic concepts such as sex, gender, power, privilege
and sexual discrimination rarely enter the vocabulary or research design. Feminist
research called attention to the unequal power relations between women and men (Figart
2005) in society and analyzed the ways in which women’s and men’s actions, positions
and relative privileges are socially constructed in ways which tend to favour men. We have
witnessed a shift away from the premise of a unitary notion of ‘women’ or ‘men’ to a
position which acknowledges how the multiplicities of masculinities and feminities are
interconnected, relational and enmeshed with class, race and nation (Hondagneu-Sotelo
2005). The first stage of the relevant feminist scholarship on migration emerged in the
62 B. Sinha et al.
1970s and early 1980s, and might be labelled ‘women and migration’ (Morokvasic 1984,
Momsen 1999). This early phase of research sought to remedy the exclusion of women
subjects from immigration research, and to counter sexist as well as andocentric bias.
A feminist approach to the principles of economics explicitly recognizes the ideological
character of economic analysis (Bergmann 1986). The male-dominated field of economics
has tended to overlook issues of importance to women, children and families – other than as
variables in studies. Mankiw’s (1998) study focuses on the individual and individual
decisions, and ‘the household has traditionally been out of the purview of economics’
(Schor 1992, p. 45). Yet no economic actor makes decisions in a vacuum, as is often implied
in neoclassical principles. There is, therefore, a need to make the household, rather than the
individual, the locus of economic study and activity.
The neglect of the household in economic analysis is a shortcoming addressed through
feminist economics, where the household is treated as an important economic unit.
As Schor (1992, p. 85) observes:
Food preparation, child rearing, laundry services, house cleaning, the transportation of people,
care of the sick and elderly, the acquisition of goods and services (shopping), gardening and
lawn care, home and car maintenance and repair, and financial accounting are all services
typically produced in American homes.
Once it is acknowledged that the household is a locus of economic activity, it also becomes
apparent that unpaid work, such as the raising of children and other household tasks, is an
essential aspect of any economy. This has become a particularly important issue as more
and more women have entered the workforce while still bearing primary responsibility for
household duties.
If the field of economics hopes to contribute to solving real problems in our global
economy, it must look beyond the narrow definition of economics as we find in the case
of neoclassical economists such as Jevons (1871), Menger (1871) and Walras (1874). The
narrowness of the questions asked by neoclassical economists, and the data gathered to
answer these questions, fails to take into account the complexity of how society manages
its resources. Feminists such as Waring (1988) have criticized the focus on GDP growth in
neoclassical economics, and the corresponding lack of consideration given to women’s
issues and environmental concerns. Even today, studies tend to focus on development and
advancements limited to men, ignoring their benefit (or lack thereof) for women.
Women’s empowerment: an Indian perspective
Women, whether young or adult, occupy a secondary status compared to their male
counterparts in Indian society. Existing patriarchal structures assure the subjugation of
women (through their status as home-makers, child-bearers and unpaid family labourers).
Many studies (Browning and Chiappori 1998, Duflo 2003, Blumberg 2005) have
demonstrated that economic factors are important in the empowerment of women.
However, given the cultural and social constraints imposed on women in India, economic
factors alone will not result in this. Though economic interventions are important, other
development initiatives such as education, political quotas, awareness generation and
property rights etc. are as essential for empowering women (Malhotra and Mather 1997,
Deshmukh-Ranadive 2003).
The World Bank has suggested that empowerment of women should be a key feature
of all social development programmes (World Bank 2002). The Millennium Development
Goals (2000) emphasized the essential role of gender equity and women’s empowerment,
as a tool for achieving acceptable demographic changes in developing countries.
Journal of Gender Studies 63
Empowerment of women can be expressed in terms of decision-making power from the
perspectives of health, mobility and household purchases as well as access to work and
education. A number of studies have shown that women may be empowered in one area of
life while not in others (Hashemi et al. 1996, Malhotra and Mather 1997, Kishor 2000).
The effect of migration of the husband on a woman is examined here. The significance
of migration is largely based on the type of community under investigation, its family
system, and to what extent other factors such as culture, kinship, religion and traditions
affect a community. Kinship associations and family residence patterns influence the
household’s adaptation to migration (UN 1994). Male migration leads to modification in
the structure of family life and also transforms women’s social and economic position,
often to their detriment. Families have to make adjustments in their lifestyle and shoulder
greater responsibilities as a consequence of the migration of a male member (Gulati 1993).
A significant effect of conjugal separation is that the wife is left with in-laws or with
parents and other relatives. It is rare that the woman and children are left behind alone
(Gulati 1993, citing Parasuraman 1986). The need for help and guidance is greatest in the
period immediately after the migrant’s first departure (Gulati 1993).
Rationale for our study
Empowerment is a latent variable that, along with its components, cannot be directly
observed or measured. In this study we look at women in families which have experienced
the migration of male adults and investigate the factors that determine their empowerment.
Amin et al. (1998) provide the theoretical perspective for the approach to this study.
Amin et al. split the concept of women’s empowerment into three components: the inter-
spouse consultation index, which seeks to represent the extent to which husbands consult
their wives in household affairs; the individual autonomy index, which represents women’s
self-reported autonomy of physical movement outside the house and in matters of spending
money; and the authority index, which reports on actual decision-making power (which is
traditionally in the hands of the patriarch of the family). Comparable components of
empowerment are included in the eight indicators used by Hashemi et al. (1996): mobility,
economic security, ability to make a small purchase, ability to make larger purchases,
involvement in major decisions, relative freedom from domination by the family, political
and legal awareness, and involvement in political campaigning and protests.
The incidence of migration of one or more family members will influence the way
the family functions. The absence of particular family members, either on a permanent
or temporary basis, will influence family structure, both in destination and origin areas
(Hugo 1987). During the husband’s absence, the wife may take over several of his roles in
order to maintain the family, such as handling more agricultural tasks (Colfer 1985,
Rodenburg 1993) or acting as a de facto household head (Hetler 1986).
The absence of the migrant from the household, especially if he is ‘the head of the
family’, can have serious implications for the women left behind, both socially and
economically (Sekher 1997). There are, however, diverse views regarding the change of
women’s status in the family due to male out-migration. On the one hand, it is believed
that women should attain more authority and power in decision making (Findley and
Williams 1991) whereas, on the other, it is remarked that male out-migration does not
substantially change women’s decision-making powers (Shaheed 1981). Women may gain
autonomy through the absence of men; however, they are left with greater stress and
vulnerability, an increased workload and a high chance of extended family intervention.
64 B. Sinha et al.
So, the migration of men potentially affects cultural norms in the household, to women’s
benefit or detriment (Jolly et al. 2003).
Data source and methodology
Empowerment of women, expressed in terms of decision-making powers in health,
mobility, household purchases etc., portrays one phase of women’s developing autonomy.
For this analysis we have taken data from India’s 2005 –2006 National Family Health
Survey-3 (NFHS-3). The NFHS-3 gathered data on certain features such as making
household purchases, having access to money and having freedom to visit the market,
a relative’s house or healthcare facility. Taking the NFHS-3 as the main source of
information, the objective of the present study is to determine the factors affecting
women’s empowerment in terms of their decision-making powers, mobility and economic
control. The present study sets out to understand the following before moving on to the
specific analysis of migration:
(1) factors affecting the empowerment of women;
(2) levels of women’s autonomy in decision making in multidimensional aspects of
life such as household purchases, access to money and mobility; and
(3) socio-economic variations in the level of empowerment.
NFHS-3 collected information from a nationally representative sample of 109,041
households and 124,385 women in the age group 15 –49. The NFHS-3 sample covers 99%
of India’s population living in the 29 states (IIPS and MI 2007a). This survey included
questions on several emerging issues such as peri-natal mortality, male involvement in
maternal healthcare, adolescent reproductive health, higher risk sexual behaviour, family
education, safe injections and knowledge about tuberculosis. In addition, NFHS-3 carried
out blood testing for HIV to provide, for the first time in India, population-based data on
the prevalence of HIV.
In this study women belonging to families experiencing male out-migration were the
unit of analysis. Thedata did not give details about those women left behind due to male out-
migration directly. In order to identify these women certain control variables were used
namely, ‘currently married women’ and ‘husbands having no other wives’. Further,
questions were asked such as: ‘Are you living with your husband now or is he staying
elsewhere?’ (IIPS and MI 2007b). Here there were two categories of women, one living with
her husband and the other not living with her husband. The latter category has been termed
as ‘left-behind women’ (due to male out-migration). Women were also asked about the
duration of the husband’s absence. To measure the effects, if any, of migration on the
empowerment of ‘left-behind women’, all those women whose husbands had migrated for
less than one year were excluded here. The women were divided into two categories, i.e.
wives of migrants and non-migrants. Therefore the total sample size is 82,676 (being made
up of 79,554 who were the wives of non-migrants and 3122 who were the wives of migrants).
Table 1 presents general information about the wives of migrants and non-migrants in
India according to different background characteristics. The variable ‘age of women’
indicates that the larger proportion of women affected by out-migration fall in the younger
age group of 15–34. Age of the husband also shows similar distribution across the two
categories. This suggests that there is a greater probability
1
of males migrating at a
younger age (leaving their wives behind) as compared to those migrating later in life.
Marital duration shows a negative association with migration, i.e. as marital duration
increases, the percentage of women left behind due to male out-migration decreases.
Journal of Gender Studies 65
Fifty-seven percent of left-behind wives have no education whereas this figure is 46% for
the wives of non-migrants. The husband’s education shows a similar pattern across the two
categories indicating that migration occurs more among people with lower levels of
educational achievement and therefore is likely to be a subsistence decision.
Another interesting feature is that there is a greater chance of women in the non-migrant
category being employed so out-migration of the husband may not lead to economic
freedom for women left behind. The difference in standard of living also augments this fact
Table 1. Distribution of women in migrant and non-migrant categories by women’s background
characteristics (percentage).
Women’s background characteristics Non-migrant Migrant
Age of women
15–19 6.7 10.1
20–34 55.1 62.0
35–49 38.2 27.9
Education
No education 46.3 56.8
Primary 15.5 13.7
Secondary 32.0 25.3
Higher 6.1 4.2
Husband’s education
No education 26.6 26.1
Primary 16.5 14.3
Secondary 45.1 48.7
Higher 11.9 10.9
Women currently working 36.4 29.5
Standard of living
Low 24.6 32.9
Medium 33.3 34.9
High 42.0 32.1
Household structure
Non-nuclear 47.2 60.3
Nuclear 52.8 39.7
Place of residence
Urban 32.5 11.5
Rural 67.5 88.5
Marital duration
0–9 years 36.9 44.9
10–19 years 33.8 33.1
More than 20 years 29.3 22.0
Age of husband
10–19 0.6 0.5
20–34 38.5 49.1
above 35 60.9 50.4
Religion
Hindu 82.1 76.8
Muslim 12.4 21.3
Others 5.5 1.8
Caste
General 31.4 28.8
Schedule Caste 19.5 16.2
Schedule Tribes 8.8 3.0
Other Backward Castes 40.2 52.0
N79,554 3122
66 B. Sinha et al.
as a relatively large proportion of wives of non-migrants belong to the high SLI category
(Standard of Living Index). This may be due to the fact that a majority of the left-behind
wives (60%) belong to a non-nuclear household which conforms to kinship patterns where
there is a preference among husbands to leave their wives with their parents rather than on
their own. Also, migration appears to be higher among Hindus and other ‘backward castes’.
2
Some 89% of left-behind wives are from rural areas which indicates the general trend
of rural to urban migration, one of the reasons for which may be the growing shortage of
fertile land due to the complex interplay of high population growth, landholding inequality,
environmental degradation, rural poverty, and the lack of infrastructure and social services
in rural areas. The result of rural out-migration aggravates the deterioration of the rural
economy leading to chronic poverty and food insecurity. There are government policies,
like the National Agriculture Policy (2000), which discourage migration from rural areas
but these measures have not proven to be effective in reversing or stalling the trend.
So it can be concluded that younger women, with shorter marital duration, belonging
to Hindu and other ‘backward castes’ are those whose husbands out-migrate leaving them
in a non-nuclear household.
Our measure of women’s empowerment is based mainly on three indicators, viz. their
decision-making powers, restrictions placed on them by their husband and their mobility.
Each of these indices provides a different dimension of empowerment. The decision-
making index is a sum of the scores assigned to women’s responses to questions regarding
their voice in certain spheres such as her own health, household purchases (both large and
those for daily needs), and decisions over her husband’s earnings. On the basis of such
scores, women are divided into three categories of low, medium and high level decision-
making powers. Similarly, indices for restrictions and mobility have been constructed.
Statistical information for other researchers in the field
Our analysis of the three indices of women’s empowerment is multivariate and employs
multinomial logistic regression models. The response (or dependent) variable in each
model is a dummy variable that indicates whether a woman has a low, medium or high
level of empowerment. The following multinomial logistic regression model has been
used in this study:
Z1¼log P1=P3
¼a1þSb1j*Xj
Z2¼log P2=P3
¼a2þSb2j*Xj
and
P1þP2þP3¼1
where,
a
i
,i¼1,2: constants
b
ij
,i¼1,2; j¼1,2, ...,n: multinomial regression coefficient
P
1
: estimated probability of medium decision-making powerby a currently married woman
P
2
: estimated probability of high decision-making power by a currently married woman
P
3
: estimated probability of low decision-making power by a currently married woman
Here, P
3
is the reference category. The same model is used for studying the other two
aspects of women empowerment, viz. freedom of mobility and restrictions by husband.
Journal of Gender Studies 67
Construction of the dependent variables
Decision-making power of women
This variable is computed on the basis of certain questions asked during the survey to the
respondent.
(1) Final say on her own healthcare.
(2) Final say on making large household purchases.
(3) Final say on making household purchases for daily needs.
(4) Final say on visits to her family or relatives.
(5) Final say on deciding what to do with the money husband earns.
The responses to the above questions are in three categories, i.e. ‘husband or any other
person’, ‘respondent and husband together’ and ‘respondent alone’. Those women who
responded that they take decisions ‘alone’ are given a value of 2 and if they answered
‘jointly’ take the decision then a value of 1 is given. If the decision is taken by ‘husband or
someone else’ then a value of 0 is given. After giving the values of 0, 1 and 2, scores for every
woman are calculated. Women getting a score of 0 are categorized as ‘no decision power’,
1–5 as ‘medium decision-making power’ and 6–10 as ‘high decision-making power’.
Freedom of mobility
NFHS-3 asked three questions on the basis of which this variable is computed.
Are you usually allowed to go to the following places alone, only with someone else or
not at all?
(a) Market
(b) Health facility
(c) Places outside village or community.
The responses to the above questions are put into three categories (i.e. ‘respondent
alone’, ‘with someone else’ and ‘not at all’). Those women who responded that they are
allowed ‘alone’ are given a value of 2 and if they are allowed ‘with someone else’ then a
value of 1 is given. If they are ‘not at all allowed’ then a value of 0 is given. After giving
the values of 0, 1 and 2, scores for every woman are calculated. Women getting a score of
0 are categorized as ‘low’, 1 – 3 as ‘medium’ and 4 – 6 as ‘high’ mobility.
Restrictions by husband
NFHS-3 asked three questions on the basis of which this variable is computed. These three
questions are as follows.
(1) Does not permit her to meet her female friends.
(2) Husband tries to limit her contact with family.
(3) Husband insists on knowing where she is.
Those who responded ‘No’ are given a value of 1 whereas if respondents reported ‘Yes’
they are given a value of 0. After giving the values of 0 and 1, scores for every woman are
calculated. Women getting a score of 0 are categorized as having ‘high restrictions’, 1– 2
‘medium restrictions’ and 3 as ‘no restrictions by husband’.
Ten predictor variables are used in the analysis. All predictor variables are categorical.
The predictor variables are: age of the woman in years (15 – 19, 20 – 34, 35– 49); women’s
education (primary, secondary or higher); husband’s education (primary, secondary or
68 B. Sinha et al.
higher); marital duration (0 – 9 years, 10 – 19 years and .20 years); residence (urban,
rural); household structure (nuclear and non-nuclear/extended); standard of living index
(low, medium and high, based on ownership of assets and other amenities); religion
(Hindu, Muslim, other); caste/tribe (SC/ST, General and OBC). These variables have been
selected as they have an association with the level of empowerment in women in migrant
households and because the data are readily available from the NFHS.
We estimate the adjusted effects of each of the 10 predictor variables on decision-
making powers, restrictions by the husband and mobility, where ‘adjusted’ means that
other selected demographic and socio-economic variables are statistically controlled by
holding them constant at their mean values. We present effects in the form of adjusted
percentages for categories of each predictor variable of interest. The adjusted percentages
(for a particular response variable) are based on a single logistic regression that includes
all 10 predictor variables. In calculating adjusted percentages for categories of any given
predictor variable, the set of control variables consists of all the other 10 predictor
variables, which are controlled by setting them at their mean values. This method of
presenting results when controlling for potentially confounding variables is called
Multiple Classification Analysis, or MCA. In the tables, we do not show the logistic
regression coefficients but rather present our results in the simple cross-tabulation format
of MCA tables [refer to Retherford and Choe (1993) for further details]. The regressions
were estimated using the STATA statistical software package. Constant terms in the
regressions are reset so that predicted percentages agree with observed percentages when
all predictor variables in the regressions are set to their mean values.
Results and discussion
Based on NFHS-3 data, from which information was collected on the magnitude of a
wife’s participation in household decision making, women’s control over resources,
restrictions by the husband and freedom of movement, the following tables show the
results of the multivariate analysis on each of these indicators of women’s empowerment.
Table 2 presents the percentage of women (those living with their husband and those
not living with their husband) with three levels of decision-making power, according to
selected background characteristics. Taking the category of women who are living with
their husbands, there is an increase in decision-making powers with increases in age,
educational attainment and marital duration of the women. With increased levels of
educational attainment in the husband and the standard of living of the family, decision-
making powers in women appear to decline, corroborating the patriarchal kinship
structure. Where a woman has economic freedom (i.e. when she is working), she has more
decision-making powers as compared to those women who are not working. Urban
residence exposes women to liberal ideologies enabling higher levels of decision-making
powers as compared to their rural counterparts. Similarly, a woman living in a nuclear
household may enjoy greater freedom and hence decision-making powers than those
women who are living in an extended family. This may be as a result of the necessity of
running the family or of a more genuinely, progressive outlook.
Migration of male members of the family does not appear to significantly change the
decision-making powers of the women left behind. Analysis of such women against
background characteristics shows similar patterns to those of non-migrant families, i.e.
age and marital duration has a positive impact on the decision-making powers of women
whereas a husband’s education and standard of living has a negative impact on the
decision-making powers of women. However, there is a significant departure from this
Journal of Gender Studies 69
trend for women living in urban areas, belonging to nuclear families, who are working.
The percentages of women enjoying higher levels of decision-making powers are much
higher for these categories as compared to those women who live in rural areas who do not
work outside the home and live in a non-nuclear/extended family. The study also found
that women belonging to other religions and the general category have higher decision-
making power when compared to Hindu or Muslim women or women of SC, ST and other
categories.
Table 2. Percentage of women with different levels of decision-making power by migrant status
and background characteristics, 2005 – 2006.
Living with husband
(non-migrant HH)
Not living with husband
(migrant HH)
Background characteristics Low Medium High Low Medium High
Age of women (in years)
15–19 18.8 68.9 12.3 10.0 51.5 38.5
20–34 10.6 66.4 23.0 5.9 45.5 48.6
35–44 8.5 63.8 27.6 3.9 42.4 53.7
Marital duration
0–9 years 13.5 67.1 19.4 11.8 52.6 35.5
10–19 years 8.8 64.9 26.3 4.8 39.1 56.0
More than 20 years 7.9 63.9 28.2 1.1 34.1 64.8
Place of residence
Urban 8.3 61.5 30.2 2.2 36.1 61.8
Rural 11.7 68.7 19.7 7.0 47.5 45.5
Household structure
Non-nuclear 14.1 65.5 20.4 16.1 47.5 36.4
Nuclear 7.5 65.2 27.3 0.8 34.3 64.9
Education of women
No education 13.9 65.9 20.2 8.4 41.0 50.6
Primary 11.1 64.7 24.2 4.3 48.4 47.3
Secondary 8.4 65.3 26.3 4.4 47.5 48.2
Higher 4.1 64.0 32.0 1.3 48.5 50.3
Education of husband
No education 10.0 64.5 25.5 4.3 40.5 55.1
Primary 9.6 64.9 25.5 3.4 42.1 54.5
Secondary 10.1 66.2 23.6 5.9 47.0 47.1
Higher 10.5 67.4 22.1 7.0 45.9 47.1
Wife currently working
No 10.6 66.8 22.6 5.7 47.3 47.0
Yes 9.1 64.0 27.0 4.5 39.8 55.6
Standard of living
Low 9.1 65.0 25.9 4.0 45.9 50.2
Medium 10.4 65.0 24.7 5.5 43.6 50.9
High 10.2 66.7 23.1 6.1 45.5 48.4
Religion
Hindu 10.7 66.1 23.2 6.5 45.1 48.4
Muslim 11.7 65.3 23.0 5.3 47.9 46.8
Others 5.8 63.4 30.8 0.8 32.4 66.8
Caste
General 10.1 65.4 24.5 4.7 42.8 52.5
SC 9.2 65.6 25.2 3.8 47.0 49.3
ST 8.6 67.8 23.5 2.6 52.7 44.7
OBC 11.2 65.6 23.2 7.3 44.9 47.8
70 B. Sinha et al.
Table 3 presents the percentage of women (those living with their husband and those
not living with their husband) with three levels of freedom of mobility, according to
selected background characteristics. With an increase in age, educational attainment and
marital duration of the women, the percentage with high levels of freedom of mobility is
increased in both migrant and non-migrant households. As expected, women who are
working, and who live in urban areas and in nuclear families, experience higher levels of
freedom of mobility than their counterparts in the respective categories. However, higher
levels of educational attainment in the husband does not translate into greater freedom of
Table 3. Percentage of women with different levels of freedom of mobility by migrant status and
background characteristics.
Living with husband
(non-migrant HH)
Not living with husband
(migrant HH)
Background characteristics Low Medium High Low Medium High
Age of women (in years)
15–19 6.7 57.3 36.0 3.7 52.0 44.3
20–34 2.9 37.0 60.1 3.0 34.2 62.8
35–44 2.7 29.2 68.1 1.7 24.8 73.5
Marital duration (in years)
0–9 3.7 41.8 54.6 3.9 41.0 55.2
10–19 2.6 31.7 65.6 2.7 27.1 70.1
.20 2.4 29.8 67.8 0.9 23.9 75.2
Place of residence
Urban 2.2 26.3 71.5 1.5 16.0 82.6
Rural 3.6 42.5 53.9 2.9 38.5 58.6
Household structure
Non-nuclear 3.1 39.7 57.2 4.2 40.5 55.2
Nuclear 2.8 30.9 66.3 1.1 21.0 77.9
Education of women
No education 3.0 42.6 54.5 2.9 33.4 63.7
Primary 3.3 38.1 58.6 1.6 37.4 61.1
Secondary 3.0 30.9 66.1 2.9 31.7 65.4
Higher 1.9 17.6 80.5 1.2 18.8 80.0
Education of husband
No education 3.1 33.3 63.6 3.2 28.0 68.8
Primary 3.2 32.6 64.2 1.7 30.7 67.6
Secondary 2.9 35.7 61.4 2.5 33.5 64.0
Higher 2.6 36.7 60.7 2.7 34.0 63.3
Wife currently working
No 3.3 38.7 58.0 2.4 36.6 60.9
Yes 2.3 27.9 69.8 2.7 22.8 74.5
Standard of living
Low 2.8 36.2 61.0 2.2 35.4 62.4
Medium 3.1 36.1 60.8 2.6 31.9 65.5
High 2.9 33.6 63.5 2.7 30.7 66.6
Religion
Hindu 2.8 35.3 61.9 2.1 32.5 65.4
Muslim 4.2 41.2 54.6 4.2 39.1 56.7
Others 2.7 26.2 71.2 2.9 13.0 84.2
Caste
General 3.2 34.8 62.1 2.5 32.1 65.4
SC 2.8 32.1 65.1 2.5 21.2 76.2
ST 2.5 35.1 62.4 1.2 28.1 70.7
OBC 2.9 36.3 60.8 2.8 36.8 60.4
Journal of Gender Studies 71
mobility for women, indicating that there might be stronger intervening factors exerting a
negative influence on the expected outcome of more liberal attitudes with increasing levels
of education. Women belonging to other religions have more freedom of mobility than
Hindu and Muslim women. Again the differentials among the migrant and non-migrant
households are more of degrees than pattern.
Table 4 shows that with an increase in age, educational attainment of the woman and
standards of living, restrictions placed on the woman by her husband decrease. Women
living in a non-nuclear household have a higher level of restrictions than is experienced by
Table 4. Women experiencing different levels of restrictions by husband by migrant status and
background characteristics (percentage).
Living with husband
(non-migrant HH)
Not living with husband
(migrant HH)
Background characteristics Low Medium High Low Medium High
Age of women (in years)
15–19 2.3 26.5 71.2 1.4 24.6 74.0
20–34 1.8 22.4 75.7 1.6 19.1 79.4
35–44 1.8 20.7 77.5 1.1 16.4 82.6
Marital duration (in years)
0–9 1.9 21.2 76.9 2.0 16.9 81.1
10–19 2.0 22.6 75.4 1.0 17.7 81.3
.20 1.7 22.1 76.2 1.0 23.2 75.8
Place of residence
Urban 2.0 19.5 78.6 1.7 22.9 75.4
Rural 1.8 24.1 74.1 1.3 17.3 81.5
Household structure
Non-nuclear 2.0 22.5 75.5 1.2 18.8 80.0
Nuclear 1.8 21.4 76.9 1.7 18.0 80.3
Education of women
No education 2.3 22.6 75.1 2.3 23.2 74.5
Primary 2.1 23.8 74.1 1.5 16.3 82.2
Secondary 1.7 21.0 77.2 1.3 15.3 83.4
Higher 0.8 19.3 79.9 0.1 13.6 86.3
Education of husband
No education 2.0 21.8 76.2 1.3 17.5 81.2
Primary 2.2 22.4 75.4 1.4 20.4 78.2
Secondary 1.9 22.2 75.9 1.2 18.2 80.7
Higher 1.3 20.6 78.1 2.4 19.6 78.0
Wife currently working
No 1.8 22.4 75.8 1.3 20.9 77.8
Yes 2.0 21.0 77.0 1.6 13.7 84.7
Standard of living
Low 2.4 23.8 73.9 2.4 28.8 68.9
Medium 2.0 22.6 75.4 1.0 18.2 80.8
High 1.6 20.9 77.5 1.2 14.7 84.1
Religion
Hindu 1.8 21.8 76.4 1.0 19.1 79.9
Muslim 1.8 24.3 73.9 2.6 18.1 79.4
Others 2.4 20.3 77.3 3.6 14.4 82.0
Caste
General 1.9 24.3 73.8 1.1 19.9 79.0
SC 2.2 22.2 75.5 1.8 21.3 76.9
ST 1.7 23.2 75.1 0.9 17.9 81.2
OBC 1.7 18.9 79.4 1.6 16.7 81.7
72 B. Sinha et al.
women who live in nuclear families. Women belonging to other religions have less
restrictions than Hindu and Muslim women. Working women also face less restrictions
than non-working women. A similar pattern was found among the group of women not
living with their husbands. Among left-behind wives, rural women have high restrictions
compared to their urban counterparts.
Conclusion
Migration is radically changing the socio-economic, demographic and development
profile of India. This study suggests an effect on the women who are left behind. Older
women are more likely to live with their husband or family as compared to younger
women. This may be because the husbands of older women are settled and can afford to
keep their family with them when they migrate, while the husbands of younger women are
still not settled enough to keep their family with them. People who belong to the high SLI
category mostly live with their wives, whereas more women belonging to the low SLI are
left behind due to male migration. Wives of non-migrants are more educated than their
migrant counterparts. This needs to be explored more as quantitative data limit the scope
for assessing the reasons behind a particular phenomenon. Women whose husbands have
migrated tend not to work and this may be because in the absence of the husband since
women’s responsibilities regarding their children’s health and education, social
expectation and dependency on others, increases.
Women’s greater involvement in agricultural production and increased responsibility
in managing households may or may not modify their socio-economic status. Previous
research has suggested that most migration takes place from the rural areas of India. Rural
unemployment resulting from rapid population growth and the mechanization of
agricultural processes has been identified as the leading cause of migration from rural
areas (UN POPIN 1995).
Another reason that the wives of migrant men may not work outside of the home might
be that, in the absence of the husband, the wife is left in the care of other members of the
extended household. Indian society does not readily allow married women to live alone.
While this extended household structure gives social protection to the wife, it may impede
their empowerment if decision-making powers are transferred to other males. Male
migration tends to conserve the traditional kinship relationships and patriarchal/seniority
values, thus reinforcing gender asymmetries in the intra-household distribution and
management of productive resources. However, another picture is also emerging – that
empowerment among certain categories of women is increasing. Women in the
community from where men migrate will assert more authority within the household,
including having more decision-making authority regarding child-rearing, household
expenditure and healthcare. It has also been found that women are now managing bank
accounts, which is a positive sign of economic emancipation (NFHS-3).
The findings of this study do not show any major breaks from the traditional restrictive
patriarchal kinship system existent in the typical Indian family. The out-migration of
males has not had a significant impact on the emancipation of women. The common
factors which increase the decision-making powers and mobility of women and that
decrease the restrictions placed on them are the age, educational attainment, marital
duration, occupation and urban residence of the women in question. The common factor
which has a negative impact on the decision-making powers, mobility of women and the
restrictions placed on them is the husband’s educational attainment (the higher the
attainment the less autonomy the woman enjoys). However, the findings do not show how
Journal of Gender Studies 73
factors interact to influence the empowerment of women. Despite this caveat, the results
will be useful in identifying those categories of women where civil society, policy makers
and institutions can direct their endeavours and interventions to ensure a tangible
enhancement in women’s empowerment.
Notes
1. Probability value is the p-value or the lowest significance level at which a null hypothesis can be
rejected (see Wright 2003, Gujarati 2007).
2. The Central Government of India classifies some of its citizens, based on their social and
economic condition, as Scheduled Caste, Scheduled Tribe and Other Backward Class (OBC) and
General. Scheduled Castes and Scheduled Tribes are Indian population groupings that are
explicitly recognized by the Constitution of India, previously called the ‘depressed classes’ by the
British (see http://en.wikipedia.org/wiki/Scheduled_castes_and_scheduled_tribes). In the Con-
stitution, OBCs are described as ‘socially and educationally backward classes’, and the
government is committed to ensuring their social and educational development (see http://en.wiki
pedia.org/wiki/Other_Backward_Class). In India, General caste or forward caste, denotes
peoples, communities and castes from any religion who do not currently qualify for Government
of India Reservation benefits (that is, set quotas for education benefits, government jobs and
political representation) (see http://en.wikipedia.org/wiki/Forward_caste).
Notes on contributors
Babita Sinha is Assistant Professor at the Indian Institute of Technology, Rooorkee, India. Her areas
of interest and research include economics, gender studies and intellectual property rights. She has
20 publications in national and international journals and conferences, and has co-edited a book on
knowledge sharing and intellectual property management. She has under her guidance several
research scholars in economics and demography.
Smita Jha, who graduated from the Central Institute of English & Foreign Languages in Hyderbad, is
Assistant Professor in the Indian Institute of Technology, Rookee, India.
Nalin Singh Negi is a Research Scholar at the Indian Institute of Technology, Roorkee, India and is
working towards his PhD in the field of demography.
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