Discussion Paper No.

858

WIDOW DISCRIMINATION
AND FAMILY CARE-GIVING IN INDIA

Yoshihiko Kadoya
Ting Yin

November 2012

The Institute of Social and Economic Research
Osaka University
6-1 Mihogaoka, Ibaraki, Osaka 567-0047, Japan

Widow Discrimination and Family Care-Giving in India
Yoshihiko Kadoya
Institute of Social and Economic Research, Osaka University
Email: kadoya@iser.osaka-u.ac.jp

Ting Yin†
Institute of Social and Economic Research, Osaka University
Email: yintingjp2001@yahoo.co.jp

Abstract
The purpose of this research is to address the lack of a region-wide view of widow
discrimination in India, the home of 42 million widows. This study analyzed the household
data collected in face-to-face interviews from January to March of 2011 in six major Indian
cities including Delhi, Mumbai, Bangalore, Chennai, Kolkata, and Hyderabad. It was
revealed that widow discrimination does not prevail across the nation. That is, this research
did not deny the existence of traditional widow discrimination in some areas, butdemonstrated that this phenomenon does not represent the whole nation if we focus on thewidow’s old age and the treatment by their family. Certainly, this research has some
limitations, including the fact that the observations came only from cities. However, this ispioneering research, and more significantly, it addresses the lack of a region-wide view
analysis of widow discrimination in India with an aging population.
Key Words: widowhood, discrimination, family caregiving, India
JEL classification: J16, P48

This research used micro data from the Preference Parameters Study of Osaka University’s 21st Century COE Program‘Behavioral Macrodynamics Based on Surveys and Experiments’ and its Global COE project ‘Human Behavior andSocioeconomic Dynamics.’ We acknowledge the program/project’s contributors: Yoshiro Tsutsui, Fumio Ohtake, andShinsuke Ikeda. We thank Charles Yuji Horioka, Midori Wakabayashi, Shizuka Sekita, and the other seminar participants at
Osaka University, Japan†Institute of Social and Economic Research, Osaka University, Mihogaoka 6-1, Ibaraki, Osaka 567-0047, Japan.

Introduction
Due to longstanding Hindu traditions, many widows have been highly discriminatedagainst in India (Ahmed 2009, Ullrich 1998, Sugirtharajah 2003), which is the home of 42
million widows (Loomba Foundation 2010). However, the argument that widows are
discriminated against has relied heavily on case studies in small areas, there is no empiricalevidence that such discrimination still exists nationally. Analyzing the household datacollected in six major Indian cities, this research addresses the absence of widow
discrimination research, with a focus on how widows are treated by their families.
Widow discrimination in India has a long history. According to Ahmad (2009), in
ancient Hindu law, the concept of stridharma entails a woman’s devotion to her husband.
This signifies women’s duties, roles, and moral responsibilities. According to this ancient law
a husband is a sort of god for women, and in fact Sawaami, the Sanskrit word for husband,means literally “Lord and Master.” Families often believe that any “immoral” act by the wife
damages her husband’s spirit. This was how sati, the Hindu family practice of a widow
immolating herself on her husband’s funeral pyre, became common in India. The ritual of sati
was first reported by Greek travelers to northern India in the 4th century B.C. (Basham, 1954:
187).
Many laws have been passed to prevent people from discriminating against widows.
In 1829, during the British colonial period, the British Government banned the ritual of sati.

More recently, the Indian Government enacted the Commission of Sati (prevention) Act of
1987. After that, the government continued its efforts to toughen the laws against sati until atleast 2008 (Ahmed 2009).
According to Ahmed (2009), there are still instances of sati in India. For example, ayoung widow, aged only 18, was forced to commit suicide after the death of her husband in
Rajasthan in 1987. When the case came to trial later, in 1996, the Indian Court upheld her“suicide” as a social tradition and acquitted all 38 defendants who assisted her act. In 2002 a
65-year-old widow committed sati in Madhya Pradesh. And in Utter Pradesh in 2006, a
35-year-old widow died by jumping into the blazing funeral pyre of her husband. Then, in
Chhattisgarh in 2008, a 71-year-old widow committed sati.
These well-known cases of sati may only be the tip of the iceberg of widow
discrimination in India. Traditionally, those “unfortunate” widows who cannot commit sati
are doomed to lead austere lives. According to tradition, they may shave their heads, wear
only plain clothing, and eat only a single meal each day, and their presence at family public
functions is forbidden (Dandvate, Kumari, & Verghese, 1989). Many of those who live in
joint families die unmourned. For example Vrindavan, a town in northern India, is now hometo thousands of destitute widows (Basu 2010). The widows there are often reduced tobegging, prostitution, and chanting hymns for up to eight hours in order to earn a handful oflentils and rice (Basu 2010, Ahmed 2009). It can be estimated that a significant number ofwidows are still discriminated against by their families and local communities.
Such discrimination against widows has become a serious social issue as the widow
population in India continues to grow at an unprecedented rate. Due to the improvement ofhealthcare, the average life expectancy in India has increased to 66 years for men and 68
years for women (CIA, 2012). Moreover, the old-age dependent ratio, which is the average
ratio of people aged 65 and older to the population aged between 20 and 64 years, is expected
to increase from about 10% in 2000 to about 17% by 2040 (United Nations 2011). With thistrend, the number of widows in India has reached over 40 million, which is about 10% of thefemale population in the country (Basu, 2010). Accordingly, with their steadily increasing
number, discrimination against widows is a growing concern.
Nonetheless, few researchers have attempted to do a region-wide view analysis of
widow discrimination in this era. The research on widow discrimination in India has reliedheavily on case studies that focus on specific areas. For example, Ullrich (1998) gathereddata about widow discrimination over a 23-year period and analyzed the processes andcultural factors of the issues. However, the data came from a specific village in southern
India; therefore the results are not necessarily representative of the entire nation. Likewise,
the above-mentioned small town in northern India, Vrindavan, is a popular target area forwidow discrimination research. However, the situation in such a “widow town” is an extreme
case (Ahmed 2009) and does not represent the entire nation.

Consequently, the following questions remain unanswered. Are widows in modern
India really discriminated against compared to non-widows (i.e., those who are married)?
And if so, are there any regional differences? Analyzing the household data collected in six
major cities, this research addresses the absence of a region-wide view analysis of widow
discrimination in India.

Methods
Since discrimination occurs within the family, this research focuses on how widows
are treated by their families as compared to how non-widows are treated. Specifically, theresearch investigates whether or not the family takes care of an old widow when she requires
long-term care. It is assumed that if widow discrimination exists, a family would only takecare of an old woman if she were married. If there is no difference in treatment on the other
hand, it can be assumed that widow discrimination does not exist.

Data
This research utilizes the data of Osaka University’s Global Center of Excellence(GCOE) Program “Preference Parameter Study of India in 2011.” The study conducted
face-to-face interviews of individuals and households in six major cities including Delhi,
Mumbai, Bangalore, Chennai, Kolkata, and Hyderabad, from January to March in 2011. The

target respondents were adults aged 20 to 71 years old. The sampling applied Multi-Stage
Sampling and the Allocation Method. The study first divided each city into four sections;
north, south, east, and west. Then, each section was further stratified into separate categories
according to gender, age group, and socioeconomic characteristics (SEC). Finally, the study
set the number of responses to be randomly collected within each stratum. From the data set,the current research chose 794 observations from interviewees who were married and had no
missing answers. The distribution of observations by city is 124 (15.62%) from Delhi, 36(4.53%) from Bangalore, 120 (15.11%) from Mumbai, 195 (24.56%) from Chennai, 160(20.15%) from Kolkata, and 159 (20.03%) from Hyderabad.

Results
This research began by investigating family attitudes towards old women in general.
The research first asked whether the mother was a widow. A total of 108 respondents had awidowed mother, whereas 686 respondents had non-widowed mother. The research thenasked who does/would primarily take care of his/her mother when the mother requires
long-term care.
Tables 1 and 2 illustrate who takes care of the mother in cases where she is a
non-widow or a widow, respectively. It can be seen that in both cases the children, includingchildren-in-law, were the primary caregivers for over 80% of the mothers. For non-widowed

mothers, the husbands played a very small role in their care. That is, only 3% of husbands
were primary caregivers. As for the widowed-mother, 4.6% of them had remarried and reliedon the new husband for care. In both cases, nearly 100% of mothers relied on their families
rather than long-term care professionals. Overall, there appeared to be little difference
between the cases of non-widowed mothers and widowed mothers.
The research further investigated whether or not the family treatment of widows andnon-widows varied by city. The model was as follows: Prob (explained_dummy = 1) = a + b(widow) + c (age) + d (h_income) + e (self_edu) + f (spouse_edu) + g (self_sibling) + h(spouse_sibling) + i (hindu*widow) + j (Bangalore*widow) + k (Mumbai*widow) + l(Chennai*widow) + m (Kolkata*widow) + n (Hyderabad*widow). Table 3 shows thedescription of the variables. Numbers 1 through 5 in parentheses are dependent variables. The
others are independent variables. Table 4 presents the descriptive statistics.
Overall, there was no evidence that widow discrimination prevails nationally. As
seen in the variable “widow” in Table 5, families did not appear to treat widows badly
compared with non-widows when it comes to providing long-term care. Indeed, theco-efficient of the variable “widow” was mostly positive. Among widows, financial aid wassignificantly positive. That is, more families send financial aid to widowed mothers.

There were some regional differences, but most of them were not significant.
Compared to the base variable of Delhi, the people in Chennai appeared to be rather harshtowards widows. The people in Bangalore, on the other hand, seemed to be more thoughtful
with respect to widows. Nonetheless, the co-efficient was not significant, except for “aid” in
Chennai and “housework” in Bangalore.
Although the sati ritual and related widow discrimination are rooted in the Hindu
tradition, Hindus did not necessarily treat widows badly compared with non-widows.
Hinduism is still the dominant religion in India, with about 90% of the people (89% in thisresearch sample) affiliated with it. However, attitudes may have changed towards widows
regardless of religion.

Discussions
This research addressed the absence of an overview of the national phenomenon of
widow discrimination in India, but it had several limitations. First, the data used in thisresearch did not include the observations about widows that had already been sent to “widow
town.” The research assumed that the widow (i.e., widowed mother) stayed connected to herfamily after her husband had passed away. As mentioned earlier, in reality some widows aresent by their families to widow town, where thousands of widows are abandoned. Althoughlittle evidence of widow discrimination was found in this research, we must recognize thatsome cases of extreme discrimination still exist.
Second, this research relied heavily on the responses from widows’ children. To
some extent, children may be reluctant to offer negative responses with regard to theirmothers. However, the ritual of sati and related widow discrimination has historically beencommitted by the family, including the children. Thus, the effect may be limited.
Third, this research assumed that the equal treatment of widows and non-widows inlong-term care indicated no discrimination, but that assumption is slightly biased. As widows
principally do not have spouses to take care of them, it is natural that other family members
provide more care to a widow than to a non-widow. Thus, the treatment of widows compared
to non-widows still includes slight discrimination. As seen in Table 1 however, the husband
plays a very small role in providing care to his wife in India; therefore the effect may be very
limited.
Fourth, the data used in this research was collected in major cities only. For better orfor worse, traditional culture tends to remain in rural areas rather than in cities. Although thesample covered many corners of the nation, the sample selection might include city bias.

Conclusions
Analyzing the household data collected in face-to-face interviews in six major cities
in India, this research revealed that widow discrimination does not prevail across the nation.
That is, this research did not deny the existence of traditional widow discrimination in someareas, but instead demonstrated that this phenomenon does not represent the whole nation.
Certainly, this research has some limitations, including such that the observations came only
from cities. However, this is pioneering research, and more significantly it addresses the lackof a region-wide view analysis of widow discrimination in an India with an aging population.
Further research may be needed to understand how widows are treated in families in rural
India.

References
Ahmad, N. (2009). Sati Tradition- Widow Burning in India: A Socio-legal Explanation.
Web

JournalofCurrent

Legal

Issues,2009(2).

Retrievedfrom

http://webjcli.ncl.ac.uk/2009/issue2/ahmad2.html
Basham, A. L. (1954). The Wonder That Was India. London: Sidgwick and Jackson.
Basu,

S.

(2010).

India’sCityof

Widows.

The

Guardian.

Retrievedfrom

http://www.guardian.co/ul/commentisfree/2010/jun/30/india-city-widows-discrimi
nationCentralIntelligence

Agency.

(2012).

The

World

Factbook.

Retrievedfromhttps://www.cia.gov/library/publications/the-world-factbook/fields/2102.html
Dandvate, P., Kumari, R., & Verghese, J. (1989). Widows, abandoned and destitute women in
India. New Delhi: Radiant Publishers.
Ullich, H. E. (1988). Widows in a South India Society: Depression as an Appropriate
Response to Cultural Factors. Sex Roles, 19 (3/4), 169-188.
Sugirtharajah, S. (2003). Imagining Hinduism: A Postcolonial Perspective. London:
Routledge.
Loomba Foundation (2011). Educate a Widows Child Documentary. Retrieved fromhttp://www.theloombafoundation.org/

UnitedNations(2011).

World

Population

http://esa.un.org/wpp/panel_population.htm

Prospects.

RetrievedfromTable 1: Primary caregiver for the non-widowed mother when she needs long-term care.
Freq.

Percent

Cum.

1. You (i.e., child)

74

15.8

15.80

2. Your spouse
3. Your brother/sister or your spouse’s brother/sister
4. The spouse of the parent requiring care
5. Other family member
6. Nursing home or assisted living home
7. Home helper
8. Other
Total

48
251
15
85
2
3
1
481

9.98
52.18
3.12
17.67
0.42
0.62
0.21
100.00

25.78
77.96
81.08
98.75
99.17
99.79
100.00Table 2: Primary caregiver for the widowed mother when she needs long-term care
1. You (child)
2. Your spouse
3. Your brother/sister or your spouse’s brother/sister
4. The spouse of the parent requiring care
5. Other family member
6. Nursing home or assisted living home
7. Home helper
8. Other
Total

Freq.
21
12
57
5
12
1
108

Percent
19.44
11.11
52.78
4.63
11.11
0.93
100.00

Cum.
19.44
30.56
83.33
87.96
99.07
100.00Table 3: Variables and Descriptions
Variable(1) live_together(2) neighbor(3) housework(4) care(5) aidwidow
age
h_ incomeself_edu
spouse_edu
self_sibling
spouse_sibling
hindu
Delhi
Bangalore
MumbaiChennai
KolkataHyderabad

Description
Do/Would you and/or your spouse live with your mother when she needs long-term care? (Yes
= 1, No = 0)
Do/Would you and/or your spouse live close to your mother when she needs long-term care?
(Yes = 1, No = 0)
Do/Would you and/or your spouse help your mother with housework when she needs
long-term care? (Yes = 1, No = 0)
Do/Would you and/or your spouse provide care for your mother when she needs long-term
care? (Yes = 1, No = 0)
Do/Would you and/or your spouse provide financial assistance to your mother when she needs
long-term care? (Yes = 1, No = 0)
Is your mother a widow? (Yes = 1, No = 0)
Your age
Your annual household income (Rs)Your schooling year
Your spouse’s schooling year
# of siblings (you)# of siblings (your spouse’s)
Religious affiliation (Hindu = 1, Others = 0)City dummy
City dummy
City dummy
City dummy
City dummy
City dummyTable 4: Descriptive Statistics(1) live_together(2) neighbor(3) housework(4) care(5) aidwidow
age
h_ incomeself_edu
spouse_edu
self_sibling
spouse_sibling
Hindu*widow
Delhi*widow (base)Bangalore*widow
Mumbai*widow
Chennai*widow
Kolkata*widow
Hyderabad*widow

Mean

Sd.

Min

Max

Obs

0.1561713
0.1309824
0.1801008
0.2329975
0.181302
0.1360202
46.4005
1791949.243073
9.239295
2.953401
2.770781
0.1183879
0.0151134
0.138359
0.0264484
0.0352645
0.0403023
0.0050378

0.3632465
0.3375937
0.3845136
0.423071
0.3855592
0.343026
12.6108175746.6
4.649111
4.626332
1.713118
1.699448
0.3232705
0.1220807
0.1169581
0.1605656
0.184638
0.1967912
0.070843

0
0
0
0
0
0
22
24000
0
0
0
0
0
0
0
0
0
0
0

1
1
1
1
1
1
71
3500000
18
18
9
9
1
1
1
1
1
1
1

794
794
794
794
794
794
794
794
794
794
794
794
794
794
794
794
794
794
794

Table 5: Estimation Results(1)
live_together
0.755(1.33)(2)neighbor-0.344(-0.47)(3)
housework
0.457(0.78)

(4)
care
0.509
(0.98)(5)aid
1.672**(2.64)-0.00613(-1.32)-0.0179***(-3.39)-0.00978*(-2.21)-0.0112**(-2.67)-0.0102*(-2.23)h_income

0.000000303(0.99)-0.00000116(-1.79)-2.15e-08(-0.06)-0.000000573(-1.33)-0.000000168(-0.43)

self_edu

0.0629***(4.12)

0.00885(0.56)

0.0617***(4.23)

0.0369**(2.74)

0.0350*(2.43)

spouse_edu-0.0557***(-3.79)0.0266(1.61)-0.0313*(-2.21)0.000590(0.04)-0.0194(-1.38)sibling_self-0.0159(-0.45)0.0187(0.47)-0.0438(-1.25)-0.0124(-0.39)0.0209(0.61)

sibling_spouse

0.0532(1.54)-0.0431(-1.06)0.0507(1.49)

0.0358(1.15)

0.116***(3.40)

hindu*widow

0.0694(0.15)

0.124(0.22)-0.298(-0.61)-0.210(-0.51)-0.347(-0.61)

Bangalore*widow

0.453(0.82)

0.504(0.72)

1.166*(2.00)

0.860(1.55)

0.340(0.60)

Mumbai*widow-0.996(-1.80)1.596**(2.58)-0.280(-0.52)-0.279(-0.57)-

Chennai*widow-0.741(-1.51)-0.0790(-0.12)-0.307(-0.59)-0.760(-1.50)-1.444**(-2.86)

Kolkata*widow

0.0501(0.11)--0.722(-1.32)0.234(0.53)-0.641(-1.44)

Hyderabad*widow-0.428(-0.51)0.643(0.73)

0.0386(0.05)-0.226(-0.29)-0.240(-0.32)_cons-1.080***(-3.36)794-0.437(-1.23)762-0.798**(-2.60)794-0.580*(-2.01)794-1.059***(-3.42)
773

widow

age

N
t statistics in parentheses*

p < 0.05, ** p < 0.01, *** p < 0.001