Studies on intergenerational educational mobility (IEM) in India rarely focus on women, and those that do often rely on secondary data, lacking insights into current trends. Using data from a longitudinal survey of 304 women across 18 villages in Uttar Pradesh. We provide firsthand insights into intergenerational education mobility (IEM) patterns and their underlying causes using transition matrices and mobility measures. Findings indicate that 75% of women experienced upward mobility respect to their mothers, and 70% respect to their fathers. Overall, IEM is predominantly upward. The primary reasons for daughters attaining more education than their parents include parental support, particularly from mothers, and their own motivation to study. Conversely, those with lower education levels than their parents cited financial constraints, the need to assist with family farming, business, or household work, socio-cultural factors, and inadequate school facilities for girls. This study highlights the continued existence of gender disparities in education and emphasizes the crucial role of parental education in shaping daughter’s educational outcomes. By offering both quantitative estimates and qualitative insights, this study contributes to the discourse on intergenerational educational mobility in India. The findings underscore the need for targeted policies to improve girl’s education, address structural barriers, and raise awareness of its long-term benefits. Strengthening schools and implementing programs that support girls can help more daughters achieve higher education than their parents, ensuring fair learning opportunities for all women.
daughter–fatherdaughter–mothereducational mobilityIndiaintergenerational mobilityThe author(s) declared that financial support was not received for this work and/or its publication.section-at-acceptancePopulation, Environment and DevelopmentIntroduction
Though India has made impressive improvement in terms of literacy rate among women – from 8.9% in 1951 to 65.5% in Chandramouli (2011), it is still one of the lowest among the Asian countries. Also, the gross enrolment ratio for women is about 27% and “share of women students is lowest in Institutions of National Importance” (AISHE, 2020). The reasons for poor condition of women education in India have been discussed in existing literature, and often are related to lower educational attainment/endowment trap—a situation going back to historical times (at least dating back to 800 BCE) where women education was neglected and discouraged due to rampant gender based discrimination; a starting position of lower educational achievement superimposed with societal conditions where the educational achievement of one generation (of women) depends on the educational achievement of the previous one—leads to a cycle of low educational achievement for women over generations (Choudhary and Singh, 2017 and the references therein).
The above argument seems persuasive when seen in the light of extant scholarship linking educational attainment of children (especially girls) to that of their parents in general and mothers in particular (Chudgar, 2011; Singh et al., 2013) can be seen for an extensive review in the global as well as Indian context). This in some sense can also be related to the notion of high degrees of inequality of opportunity in India given the fact that an individual does not choose one’s family, but her/his life chances are substantially determined by her/his parental endowment (Motiram and Singh, 2012; Roemer, 2013).
Education plays a key role in reducing social mobility barriers (Vaid, 2018). However, women’s choices, aspirations, and attitudes are often mediated by the educational attainment of parents (Vaid, 2017). In the Indian context, the persistently poor condition of education of women accompanied by the role of parents in the educational attainment have promoted a limited but growing body of research examining intergenerational educational mobility among women. Using data from secondary sources, the studies like – (Jalan and Murgai, 2008) (based on National Family Health Survey [NFHS]); (Majumder, 2010) (based on National Sample Survey [NSS]); (Choudhary and Singh, 2017) (based on India Youth Survey); and (Choudhary and Singh, 2019) (based on India Human Development Survey [IHDS]) – have examined intergenerational mobility in education among Indian women. These studies suffer from some well-documented (in the literature on intergenerational educational mobility in India) data limitations, such as, sample selection problems, for example, in NFHS and NSS parental education is available only for daughter-parent pairs living together in the same household; given the low age of marriage in India, majority of the adult women are either the daughter-in-law or wife of household heads’, a group for which parental education is not known and therefore excluded from the analysis. Also, (Choudhary and Singh, 2017) is based on women in the age group of only 15–24 years.
The more important limitation is related to the fact that, the existing narrative offers no comment on the trends and patterns underlying the intergenerational educational mobility estimates beyond the estimates of intergenerational educational mobility itself, due to absence of relevant data for making such comments; a point well noted in Choudhary and Singh (2017) Probably, that is why; one consistent suggestion for future work in the aforementioned studies has been to conduct a detailed primary study which can provide some insights on the trends and patterns of the estimates of intergenerational educational mobility among women in India.
Given the above, the present study examines intergenerational educational mobility among women (with respect to both the parents) in the Indian context using a primary survey (details provided in the subsequent section). Also, it not only provides the estimates of mobility using standard measures adopted from the literature on intergenerational mobility but also offers plausible reasons and observations (gauged from the survey itself) underlying the estimates. Therefore, the present study not only complements the existing studies but also adds substantially to the existing scholarship on intergenerational educational mobility in India. The next section briefly outlines the survey, data, methods and measures used in the analysis presented in the present paper. It is followed by a section reporting the main findings of this paper. Section 4 and 5finally concludes the paper along with some discussion on the main findings and policy recommendations.
Data, study sample, methods, and measuresData and study sample
The data for the estimation is taken from an ongoing longitudinal primary study investigating the socioeconomic characteristics of women and its effect on the human capital (education and health) formation of their children in the Varanasi district of the state of Uttar Pradesh in India. The study comprises of 304 women spread over 18 villages across two blocks (nine each from Araziline and Kashi Vidyapeeth) of the Varanasi district in the eastern part of the state of Uttar Pradesh. The sample study villages are presented in Table 1.
Eligible pregnant women selected from 18 villages across 2 blocks: Arajiline and Kashi Vidyapeeth, Varanasi, India, 2016.
Block name
Village name
Number of pregnant women
Percent
Arajiline
Sajoi
17
5.59
Parmandapur
35
11.51
Bhadav
30
9.87
Koraut
33
10.86
Gopipur
2
0.66
Lohrapur
5
1.64
Aydhoyapur
13
4.28
Sarvanpur
9
2.96
Shirsha (Girjapur)
9
2.96
Kashi Vidyapeeth
Mangalpur
8
2.63
Oonche Ganv
37
12.17
Korauta
32
10.53
Ghatampur
16
5.26
Udayrajpur
10
3.29
Pilkhini
13
4.28
Anantpur
3
0.99
Bankat
5
1.64
Bhatti
27
8.88
Total
304
100
The eastern parts of Uttar Pradesh constitute one of the most disadvantaged regions of India when it comes to demographic, economic and social indicators. Within eastern Uttar Pradesh, Varanasi (historically known as Kashi, one of the most ancient cities of India) is known for its rich cultural, historical and social heritage. It is also known for its social (based on caste) and religious mix. Caste defines the social fabric in India, and Deshpande’s Grammer of Caste (Deshpande, 2011) offers an insightful exploration of this structure.
Varanasi itself comprises eight blocks; from these blocks, two blocks – Araziline and Kashi Vidyapeeth – were purposively chosen to give a sample rich in terms of caste and religious composition. Finally, 18 villages (nine from each block) were randomly selected for the study. The first round of the survey was spread over a period of 9 months, starting in April 2016 and concluding in December 2016. The second round was conducted in mid-2017, 42 days after childbirth (post-partum period). All the women who were in the first trimester of pregnancy during April 2016 in the selected villages were included in the study sample. This resulted in a total sample of 304 women on which the present analysis is based.
This longitudinal study has multiple objectives including – examination of socioeconomic characteristics and transitions in socioeconomic characteristics of women; effect of socioeconomic characteristic, nutritional intake and utilization of healthcare during pregnancy on child birth and child outcomes; and (but not limited to) effect of socioeconomic characteristics, nutritional intake and utilization of healthcare during (and after) pregnancy on long term human capital consequences for children. The present paper is based on the first objective (that is, transitions in socioeconomic characteristics experienced by women) for which information was collected on the education of women as well as their parents (and spouses) using modules on education and intergenerational educational mobility. Reasons and factors related to educational achievement (both in absolute terms as well as relative with respect to parents) was also captured using structured and unstructured responses. The socio-economic-demographic characteristics of the surveyed women is presented in Table 2.
The socio-economic-demographic characteristics of the surveyed women, Varanasi, India, 2016.
Background variable
Mean
SD
Number
Block sample
Arajiline
50.33
153
Kashi Vidyapeeth
49.67
151
Pregnant women age
24.75
3.27
304
Age at marriage
18.78
1.78
Household size
5.20
2.34
Background variable
Percentage
Number
Women education
Illiterate
8.55
26
Literate but below primary
3.95
12
Primary
15.79
48
Middle
17.11
52
Secondary
21.71
66
Higher secondary
21.05
64
Graduate or higher
11.84
36
Religion
Hindu
95.39
290
Muslim
3.29
10
No religion
0.99
3
Other
0.33
1
Caste
Schedule caste
19.74
60
Schedule tribe
3.62
11
No caste/tribe
70.39
214
Do not know
6.25
19
Type of family
Joint
43.42
132
Nuclear
56.58
172
Occupation of pregnant women
No work
2.63
8
Housewife
61.18
186
Farmer
12.5
38
Agriculture labour
6.25
19
Non-agriculture labour
1.64
5
Skilled labour/machinery/fisherman
2.3
7
Clerk
0.33
1
Other
13.16
40
Toilet facility
No facility (open field)
33.55
102
Pit latrine (household’s)
58.88
179
Flush Toilet
6.91
21
Other
0.66
2
Source of drinking water
Pipe
0.66
2
Tube well
4.61
14
Well
4.28
13
Hand pump
89.8
273
Other
0.66
2
Total
100
304
Health insurance
Yes
17.11
52
No
82.89
252
Ethical approval for the study was obtained from the Institutional Ethical Review Board of the Indian Institute of Technology Bombay, India, and all the necessary guidelines and protocols for studies involving human subjects were followed. The questionnaires were administered to the eligible women by trained ASHA (Accredited Social Health Activities) workers. The government appoints a trained female community health activist (ASHA who is primarily a woman resident of the village preferably in the age group of 25 to 45 years) worker for every village under the National Rural Health Mission of India. Although the ASHA workers administering the questionnaires were appointed by the government, neither they nor the government had any role in influencing the study or its outcomes. These ASHA workers serve as the primary point of contact for health-related needs in rural areas, particularly for women and children who face systemic barriers to accessing care. Beyond providing basic first aid and essential health supplies, they play a vital role in community mobilization around critical issues such as sanitation, nutrition, maternal and child health, and water safety, while also facilitating access to institutional health services.
Introduced in 2005 under the National Rural Health Mission (NRHM), the Accredited Social Health Activist (ASHA) program was conceived to enhance rural public health service delivery and foster community participation in health governance (National Rural Health Mission, 2005, Government of India). Each village, typically comprising around 1,000 individuals, is assigned one ASHA usually a local woman who undergoes an initial 23-day training in fundamental health care.
Methods and measures
We have used ‘transition’ or ‘mobility’ matrices and mobility measures which are extensively used in the scholarship on intergenerational educational mobility. Educational transition (or mobility) matrices give the percentages of women who belong to the various educational categories corresponding to the educational categories of their mothers. Following the body of literature, these percentages can also be interpreted as conditional probabilities, i.e., the probability that a woman belongs to a certain educational category given the condition that her mother belongs to a particular educational category (Motiram and Singh, 2012; Choudhary and Singh, 2017).
In addition to transition/mobility matrices to draw inferences, we have also used a mobility measure especially developed in the literature on intergenerational mobility to analyze such mobility (Choudhary and Singh, 2017; Formby et al., 2004; Motiram and Singh, 2012; Van de Gaer et al., 2001). Using the same notations as in Choudhary and Singh (2017); let pij (i,j = 1,…,m) be the value in the ith row and jth column of the transition matrix (T), that is, the probability that the daughter’s educational category is j given that her mother’s educational category is i; where m is the number of categories:
The mobility measure, M is:
M=1m∑i=1m∑j=1j≠imPij=(1−1m∑i=1mPii)
It is the probability that a daughter (or the expected proportion of daughters) will leave the mother’s educational category. It can also be interpreted as the normalized distance between the transition matrix and the identity matrix of order m (Motiram and Singh, 2012; Choudhary and Singh, 2017). The identity matrix (which comprises of a leading diagonal of 1’s and the rest of the entries as 0’s) represents perfect immobility since whatever the educational category of the mother be, the daughter falls in the same category.
Since the above measure in itself captures only the overall mobility but cannot be used to comment on the extent of upward or downward mobility (there always exists a possibility where the mobility measure has a very high value indicating a high level of mobility in a society but the mobility could be predominantly downward mobility, that is, daughters’ acquiring lower education than that of their mothers in case of education), we decompose (following Choudhary and Singh, 2017) the overall mobility measure M into downward and upward mobility as follows:
If the education levels are ranked in the increasing order, that is, i,j = 1,2,…,m, where, i,j = 1 is the lowest education level and i,j = m is the highest education level, then from Equation 1,
That is, using Equation 2, M can be clearly represented as an exact sum of downward and upward mobility. Evidence on upward and downward mobility is important from both, academic and policy perspectives because it informs the direction of mobility; if on one hand upward mobility has to be supported on the other negative mobility has to be neutralized with suitable policy interventions.
Empirical results and analysis
As mentioned earlier we have used data from an ongoing longitudinal primary study investigating the socioeconomic characteristics of women and its effect on the human capital (education and health) formation of their children in the Varanasi district of the state of Uttar Pradesh in India. Table 2 presents the socio-economic and demographic characteristics of the surveyed women in Varanasi. The sample is almost evenly distributed across the two selected blocks, with 50.3% of respondents from Araziline and 49.7% from Kashi Vidyapeeth, ensuring balanced block-wise representation. In terms of educational attainment, the majority of women had some level of formal schooling. While 8.6% were illiterate and 4.0% were literate but below the primary level, nearly 33% had completed primary or middle-level education. A notable share of women had attained higher levels of education: 21.7% completed secondary schooling, 21.1% higher secondary education, and 11.8% were graduates or had higher qualifications. The religious composition of the sample is predominantly Hindu (95.4%), with Muslims accounting for 3.3%, while less than 1% reported no religion or other religious affiliations. Caste-wise, 19.7% of respondents belonged to Scheduled Castes and 3.6% to Scheduled Tribes, while a substantial majority (70.4%) reported no caste or tribe affiliation; 6.3% were uncertain about their caste status.
Regarding household structure, 56.6% of women lived in nuclear families, whereas 43.4% resided in joint families. Occupationally, most women were not engaged in formal paid employment. A large proportion (61.2%) identified as housewives, while 12.5% were engaged in farming and 6.3% worked as agricultural labourers. Smaller shares were involved in non-agricultural labour (1.6%), skilled occupations (2.3%), clerical work (0.3%), or other activities (13.2%). Only 2.6% reported not working at all, highlighting women’s predominant involvement in unpaid domestic and agricultural work. Access to basic amenities remains limited. About 33.6% of households lacked toilet facilities and practiced open defecation, while 58.9% used household pit latrines and only 6.9% had flush toilets. Drinking water access relied heavily on hand pumps (89.8%), with minimal access to piped water (0.7%). Health insurance coverage was low, with only 17.1% of women insured, leaving 82.9% without financial protection against health-related risks.
The survey captures education levels for the women and their parents using the following categories: no formal schooling (1); schooling less than primary [5th standard] (2); completed primary but less than middle school [8th standard] (3); completed middle school but less than secondary [10th standard] (4); completed secondary but less than higher secondary [12th standard] (5); completed higher secondary but less than graduation [graduate degree typically BA/BSc/BCom with different subjects] (6); completed graduation and above (7). The above categorization is based on the Indian schooling system where primary, middle school, secondary, higher secondary (also called intermediate), graduation and above are important milestones of educational attainment.
We have first presented the intergenerational educational mobility estimates for the overall sample. Finally, we have explored and documented the main reasons behind the observed mobility.
Intergenerational educational mobility
Table 3 provides the distribution (percentage) of women (daughters, mothers as well as fathers) by educational categories. It can be seen from the table that the education level of mothers is quite dismal. About 67% of the mothers in the overall sample do not have any formal schooling with the situation being worse if we consider that almost 80% of the mothers have less than a primary education. Also, less than 1% of the mothers have a schooling of 12 or more years. In terms of fathers’ education, about 54% have less than a primary education, whereas, about 6% have a schooling of 12 or more years. The situation is relatively better for the daughters. Among them, about 33% have a schooling of 12 years or more.
Distribution (percentage) of females by educational categories: Varanasi, India, 2016.
Educational categories
Mother
Daughter
Mother
Daughter
(N)
(N)
(%)
(%)
(1)
203
26
66.78
8.55
(2)
41
12
13.49
3.95
(3)
33
48
10.86
15.79
(4)
17
52
5.59
17.11
(5)
8
66
2.62
21.71
(6)
2
64
0.66
21.05
(7)
0
36
0
11.84
Total (N)
304
304
100
100
(1) No formal schooling (2) Literate but below primary (3) Primary (4) Middle (5) Secondary (6) Higher secondary (7) Graduate or higher.
Sources: Author’s calculation based on survey data 2016.
The education transition/mobility matrices (daughter–mother pair) are presented in Table 4. Some important results worth reporting from Table 4 (a) are – (i) about 11.3% of the daughters of mothers with no formal schooling end up with no formal schooling; (ii) about 8.9% of the daughters born to mothers with no formal schooling end up acquiring schooling of 15 or more years; (iii) also, about 27.6% of the daughters born to mothers with no formal schooling end up acquiring schooling of 12 or more years; (iv) approximately, 24.2% of the daughters of mothers with primary schooling end up with primary schooling but surprisingly 3% end up with no formal schooling at all; (v) again, about 27.2% of the daughters born to mothers with primary schooling end up acquiring schooling of 12 or more years; (vi) one positive observation from the table is that none of the daughters of mothers who have completed at least 8 years (middle) of schooling, have completed less than primary schooling.
Educational transition/mobility matrices: mother and daughter, Varanasi, India, 2016.
Educational categories of mothers
Educational categories of daughters (percentage)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
11.3
5.9
17.2
20.2
17.7
18.7
8.9
(2)
4.9
0
7.3
9.8
31.7
29.3
17.1
(3)
3
0
24.2
15.2
30.3
12.1
15.2
(4)
0
0
5.9
11.8
23.5
35.3
23.5
(5)
0
0
12.5
37.5
25
25
0
(6)
0
0
0
0
0
100
0
(7)
0
0
0
0
0
0
0
(1) No formal schooling (2) Literate but below primary (3) Primary (4) Middle (5) Secondary (6) Higher secondary (7) Graduate or higher.
Sources: Author’s calculation based on survey data 2016.
The education transition/mobility matrices (daughter–father pair) are presented in Table 5. Some important results worth reporting from Table 5 (b) are – (i) about 17.2% of the daughters of fathers with no formal schooling end up with no formal schooling; (ii) about 3.3% of the daughters born to fathers with no formal schooling end up acquiring schooling of 15 or more years; (iii) also, about 34.2% of the daughters born to fathers with no formal schooling end up acquiring schooling of 12 or more years; (iv) surprisingly, 5% of the daughters of fathers with primary schooling and 2% of the daughters of fathers with secondary schooling, respectively, end up with no formal schooling at all; (v) one encouraging observation from the table is that about 86% of the daughters born to fathers with higher secondary schooling end up completing at least higher secondary schooling.
Educational transition/mobility matrices: father and daughter, Varanasi, India, 2016.
Educational categories of fathers
Educational categories of daughters (percentage)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(1)
17.2
6.6
23
21.3
16.4
12.3
3.3
(2)
4.9
9.8
19.5
14.6
17.1
24.4
9.8
(3)
5
0
10
12.5
32.5
22.5
17.5
(4)
0
0
16.7
25
25
19.4
13.9
(5)
2.1
0
4.2
10.4
33.3
31.3
18.8
(6)
0
0
0
7.1
7.1
50
35.7
(7)
0
0
0
0
0
33.3
66.7
(1) No formal schooling (2) Literate but below primary (3) Primary (4) Middle (5) Secondary (6) Higher secondary (7) Graduate or higher.
Sources: Author’s calculation based on survey data 2016.
The estimates of the mobility measures for daughter-mother and daughter-father pairs have been presented in Table 6. The mobility measure, M1 varies between “0” (no mobility at all) and “1” (perfect mobility); the overall mobility for the daughter-mother pairs is about 0.75. About 69% of the overall mobility is upwards. The overall mobility for the daughter-father pairs is about 0.70. Approximately, four-fifth of the total mobility is upwards. Some plausible reasons and observations (gauged from the qualitative part of the survey itself) underlying the estimates have been presented in the next subsection.
Educational transition/mobility matrix M1, Varanasi, India, 2016.
Mobility matrix
M1
Daughter–mother
0.754
Daughter–mother (upwards)
0.520 (69%)
Daughter–mother (downwards)
0.234
Daughter–father
0.697
Daughter–father (upwards)
0.567 (81%)
Daughter–father (downwards)
0.130
Upward/downward mobility as a percentage of total mobility (M1).
Sources: Author’s calculation based on survey data 2016.
Intergenerational educational mobility: some explanations and insights
This section focuses on the educational achievements of the daughters with respect to their parents. It comprehensively explores whether the daughters attained a level of education which is higher, similar, or lower compared to their mothers and fathers and the reasons/insights behind these educational outcomes. These insights are based on the information collected through the survey (semi-structured) questionnaire. Before administering survey questionnaires for (conducting) the main study, a pilot phase/survey was conducted. This preliminary phase involved multiple methods to gather information and development (as well as refinement) of the questions. The methods include focused group discussions (FGDs) and Key Informant Interviews (KIIs), where conversations were held with the selected women in the study area. The FGD was particularly aimed to understand the subjective perspectives and experiences of these women regarding their educational attainment in relation to their parents. From the understanding, the final questionnaire was developed for the main survey where reasons were listed, allowing respondents to provide detailed, nuanced explanations for their educational paths in comparison to that of their parents.
The Table 7 shows the distribution of daughters’ educational attainment with respect to that of their mothers. Out of the 304 daughters for whom the data was collected, 261 (86%) daughters have completed more years of education than their mothers. About 12.5% of the daughters have similar educational qualification as of their mothers, whereas around 1.6% of the daughters have an educational qualification which is lower than that of their mothers.
Distribution of daughter’s education attainment with respect to their mothers, Varanasi, India 2016.
Status of education
Number (N)
Percentage (%)
Higher
261
85.9
Similar
38
12.5
Less
5
1.6
Total
304
100
The main reasons for the higher educational attainment of the daughters compared to their mothers have been presented in Figure 1. Of those who attained more education than their mothers, around 30% mentioned that their mothers desired them to pursue more education than themselves; about 23% expressed their personal aspiration to pursue more education than their mothers; 19.2% indicated that their fathers encouraged them to study more than their mothers; 18.4% stated that both parents wanted them to study further than their mothers; and about 10% credited someone else for motivating them to pursue more education than their mothers.
Percentage of daughters who studied more, similar, and less than their mothers: main reasons, Varanasi, India, 2016.
Bar chart displaying factors affecting daughters' education levels compared to their mothers'. For those attaining higher education, influences include their mother (30.3%), personal desire (22.6%), father (19.2%), and both parents (18.4%). Obstacles for similar education levels are financial constraints, lack of facilities, and transportation issues. For lower education levels, reasons include family responsibilities (40%) and poverty (20%).
Also, the primary factors contributing to daughters attaining the same level of education as that of their mothers are: 26.3% of the daughters (who have a level of education same as that of their mothers) cited a lack of financial resources for education; 18.4% attributed their situation to poverty, and 13.2% mentioned the high cost of education as the barrier. Additionally, about 10.5% reported that their involvement in household chores prevented them from going for higher levels of education, while 7.9% cited the unavailability of transportation as the reason. Besides, about 5.3% expressed a lack of understanding of education’s importance and around 2.6% highlighted societal restrictions, insufficient facilities for girls in schools, and the need to work outside the home as the reasons for their inability to pursue higher levels of education.
Moreover, the main reasons behind the daughters having an educational attainment lower than their mothers are as follows: about 40% of the daughters (who have a level of education lower than that of their mothers) said that they were required to help in family farming or business; 20% cited poverty as the barrier to pursuing education beyond their mothers’ attainment levels; another 20% mentioned their lack of interest in studies and the absence of adequate facilities for girls in the schools as the reasons for their lower educational achievements compared to their mothers.
Looking into the daughters’ educational attainment vis-a-vis their fathers’ level of education, the results indicate that among the 304 daughters – 220 (about 72%) exceeded their fathers in terms of educational achievements; about 20.7% matched their fathers’ educational levels, whereas surprisingly around 6.9% fell below their fathers’ educational attainments (see Table 8).
Distribution of daughter’s education attainment with respect to their fathers, Varanasi, India 2016.
Status of education
Number (N)
Percentage (%)
Higher
220
72.4
Similar
63
20.7
Less
21
6.9
Total
304
100
The main reasons for daughters having higher, similar, and less educational achievements than their fathers are presented in Figure 2. The findings indicate that, approximately 31% of daughters (of those who attained more education than their fathers) mentioned that their mothers motivated them to study more than their fathers; about 22.3% indicated that both parents shared the aspiration of the daughter being more educated than the father; around 20% expressed their personal inclination to pursue more education than their fathers; nearly 16.8% highlighted their fathers’ encouragement for them to study more than their father’s education level; and finally 10% attributed external encouragement from someone other than their parents who motivated them for higher levels of educational attainment.
Percentage of daughters who studied more, similar, and less than their fathers: main reason, Varanasi, India, 2016.
Bar chart depicting reasons for educational attainment differences between daughters and fathers. For higher attainment, the main reason is maternal encouragement (30.9%). For similar attainment, main barriers are financial and cultural (15.9% each). For lower attainment, financial constraints dominate (23.8%). Factors include societal culture, poverty, and chores. Percentages are shown.
Also, the primary factors contributing to the daughters attaining a similar educational level to that of their fathers are: nearly 16% of the daughters (who have a level of education same as that of their fathers) cited financial constraints as the hindrance to higher levels of education; about 11% attributed societal pressures, while another 11% pointed to poverty as the barrier preventing them from achieving education levels higher than that of their fathers; additionally, about 9.5% mentioned helping in family farming/business, and an equal percentage highlighted engagement in household chores as the reasons for not achieving education levels higher than that of their fathers; another 9.5% faced challenges due to distant schools, while 7.9% could not achieve higher levels of education due to lack of – transportation and proper facilities in the school. Furthermore, around 6.3% found education too costly, whereas an equal percentage failed to grasp its significance.
Finally, the main reasons as to why the daughters who had a lower educational achievement than their fathers had that lower educational attainment are: about 23.8% (of those who have a level of education lower than that of their fathers) said that lack of money did not allow them to go for higher levels of educational; around 14.3% blamed society for the same, while, another 9.5% said that poverty was the main constraint; also nearly 9.5% said that they had to take care of small kids in the households, whereas, another 9.5% said that they had to help in family farming or business; about 4.8% said that there were no proper facilities for girls at the school, while nearly 4.8% said that education was too expensive; moreover, around 4.8% said that they were required to help in household chores, whereas, about 4.8% said that school was too far away. The findings both – quantitative estimates as well as qualitative insights have been further discussed in the next section and then further concludes this paper.
Discussion
The present study comprehensively and critically examines intergenerational educational mobility among women (with respect to both the parents) in the Indian context using a primary survey. Also, it not only provides the estimates of mobility using standard measures adopted from the literature on intergenerational mobility but also offers plausible reasons and observations (gauged from the survey itself) underlying the estimates. Therefore, the present study not only complements the existing studies but also adds substantially to the existing scholarship on intergenerational educational mobility in India.
The main findings from the present study are: the education level of mothers is quite dismal; about 67% of the mothers in the overall sample do not have any formal schooling with the situation being worse if we consider that almost 80% of the mothers have less than a primary education; in terms of fathers’ education, about 54% have less than a primary education, whereas, about 6% have a schooling of 12 or more years; the situation is relatively better for the daughters, where, nearly 33% have a schooling of 12 years or more; also, about 11.3% of the daughters of mothers with no formal schooling end up with no formal schooling, whereas, around 27.6% of the daughters born to mothers with no formal schooling end up acquiring schooling of 12 or more years; one positive finding is that none of the daughters of mothers who have completed at least 8 years (middle) of schooling, have completed less than primary schooling; moreover, about 17.2% of the daughters of fathers with no formal schooling end up with no formal schooling; whereas, nearly 34.2% of the daughters born to fathers with no formal schooling end up acquiring schooling of 12 or more years; one point worth noting is that about 86% of the daughters born to fathers with higher secondary schooling end up completing at least higher secondary schooling. Further, the overall mobility for the daughter-mother pairs is about 75% and nearly 69% of the overall mobility is upwards, whereas the overall mobility for the daughter-father pairs is about 70% and almost four-fifths of it is upwards. The above findings are in line with the existing literature on the subject, for example, Choudhary and Singh (2019) who (using a secondary data and similar mobility measures) found that intergenerational educational mobility among Indian women is about 70% and nearly 80% of the total mobility is upwards.
The compelling reasons for the higher educational attainment of the daughters (those who attained higher) compared to their parents are their parents (mostly mothers) motivated them to pursue more education than themselves and personal aspiration to pursue more education than their parents. The main reasons for the lower (or same) educational attainment of the daughters (those who attained lower or same) compared to their parents are (but not limited to): lack of financial resources for education; poverty, help in family farming or business; involvement in household chores (including taking care of siblings); high cost of education; societal norms/restrictions; absence of adequate facilities for girls in schools and lack of transportation. Surprisingly, a large proportion of daughters (and the households they belong to) could not understand the significance or importance of education.
Though the study has strengths in terms of using standard and well acceptable methods (as well as measures) and primary data, it also has a few limitations. The first being that the sample size is not very large, and the generalizability of the study should be taken with this caveat. Second, we did not use regression techniques to estimate the likelihood that a daughter will be in the same educational category given the mother’s/father’s educational category with controls for various relevant variables; however, as detailed in Motiram and Singh (2012) and Choudhary and Singh (2017). In using such a regression, there are several problems of, for example, potential endogeneity of explanatory variables and omitted variable bias, further, such a regression would be unable to distinguish between daughters’ educational categories that are “close” to the mother’s/father’s educational category and those that are “distant” from the mother’s/fathers’ educational category. So, as suggested by the above studies, we have used mobility measure specifically developed to comprehend and investigate mobility and which does not suffer from the aforesaid limitations (Van de Gaer et al., 2001; Formby et al., 2004; Motiram and Singh, 2012).
The findings of this study have some policy implications, such as, special attention needs to be given to increase the awareness about the importance of girls’ education in rural areas (the federal Indian and the state governments have already launched various programs to this effect); dedicated programs to improve the education among mothers and older women who could not get formal schooling in their childhood (a policy also suggested by Choudhary and Singh, 2019); improving and providing adequate facilities in schools for girls; improving accessibility of schools and lowering of local transportation costs; and finally, policies to counter and reform the social norms and culture which discourage girls education in even the present day modern India.
Conclusion
This study highlights substantial intergenerational educational mobility among women in India, particularly upward mobility among daughters despite historically low levels of parental education. While significant progress is evident, persistent structural, economic, and social barriers continue to constrain educational attainment for many girls. The present conclude that parental encouragement, especially from mothers, emerges as a crucial factor in promoting upward mobility. Addressing both material constraints and deep-rooted social norms remains essential for sustaining and accelerating educational gains among future generations of women.
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Ethics statement
The studies involving humans were approved by Institutional Ethical Review Board of the Indian Institute of Technology Bombay, India. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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The author(s) declared that Generative AI was not used in the creation of this manuscript.
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Edited by: Mohd Usman, Symbiosis Medical College for Women (SMCW), India
Reviewed by: Md Gulzarul Hasan, Manipal Academy of Higher Education, India
Marina Silva Cunha, State University of Maringá, Brazil