Modern Marriage in a Traditional Society: The Influence of College Education on Marriage in India

Abstract

India has witnessed a dramatic expansion of higher education, and women have emerged as noteworthy winners in the process. This paper focuses on the role of female college education on four dimensions of marriage: age at marriage, autonomy in the choice of spouse, work and financial empowerment, and quality of marital relationship. The study uses a sample of 35,561 currently married women from the 2011-2012 wave of the nationally representative India Human Development Survey (IHDS). It demonstrates that higher education, particularly college education, enables women to lead lives substantively different from their less-educated peers. College-educated women marry at later ages, enjoy greater autonomy in choosing their husbands, and have a more egalitarian relationship with their spouses. Furthermore, the study finds that educational homogamy and hypogamy afford greater autonomy to women. Even without a concomitant increase in labor force participation, college education among women appears to have a transformative effect on marriage in India.

Keywords

family demography family processes gender and family dating/relationship formation dyadic relationship/quality/satisfaction

Introduction

India has witnessed a remarkable expansion of higher education since the 1990s, and women have emerged as significant beneficiaries in the process (Nozaki et al., 2009; Joshi & Ahir, 2019). Women have historically lagged behind men and majored in predominantly “feminine” disciplines such as the humanities, arts, and education (Chanana, 2000; Nozaki et al., 2009); however, recent data show that the gender gap in higher education has narrowed significantly. For instance, the Gender Parity Index (GPI) for higher education enrollment increased from 0.7 in 2006–07 to 0.97 in 2017–18 in India (Joshi & Ahir, 2019). Moreover, women now outnumber men in several undergraduate and graduate programs, including the highly competitive medical and science programs, according to the All India Survey of Higher Education (Ministry of Human Resource Development, 2019). These accomplishments are noteworthy and are indicative of a cultural shift that has been underway in India. Similar advancements have been noted in several countries across varying levels of development (Esteve et al., 2012; Esteve et al., 2016).

A defining feature of education is its transformative potential. While recognizing that the experience of schooling is not homogenous, education has been argued to increase women’s knowledge, self-esteem, efficacy, and communication abilities (LeVine et al., 2001; Stromquist, 2015; Vikram & Vanneman, 2020). LeVine and colleagues (2011) state that girls develop “communicative effectiveness” in school, enabling them to navigate the outside world successfully. Furthermore, education has been viewed as a vital tool for empowerment that can enable people to make strategic choices in their lives (Stromquist, 2015). However, researchers are circumspect about the role of schooling alone in fostering social change and instilling empowerment among women in the absence of other structural changes (Walker & Unterhalter, 2007; Stromquist, 2015).

Modernization theories suggest that women’s education can lead to more egalitarian gender relations leading to greater cooperation between the married couple (Caldwell, 1980). According to the developmental idealism perspective, education can lead to ideational changes, which can modernize gender relations within the family (Thornton, 2001). However, how education is embodied in women’s identity, demeanor, and behavior is likely to be conditioned by the broader sociocultural and normative context. Jejeebhoy (2000) finds that sociocultural settings determine the extent to which women enjoy decision making and economic autonomy in India. Likewise, the returns from women’s education are likely to be contingent on the patriarchal and patrilineal values that shape the life course of Indian women. In India, critical decisions about women’s lives such as the age at marriage and choice of husband are predominantly arranged by parents and extended families with limited (or no) input from the women themselves (Kaur, 2004; Desai & Andrist, 2010; Banerji et al., 2013; Allendorf & Pandian, 2016). Banerji (2008), using the first wave of the IHDS, finds that education among women does not lead to a shift to “self-arranged” or “love marriages” from “arranged marriages” set up by relatives or parents but allows for a greater say in the choice of spouse in parent-arranged marriages.

This paper takes a closer look at the influence of education, particularly tertiary education, on a range of processes entailed in selecting the spouse, on the age at marriage, as well as the quality of marriage. It underscores the need to examine intra-household processes to observe both subtle and discernible changes that occur as a consequence of female education in India. Using a sample of 35,561 currently married women from the most recent wave (2011–2012) of the nationally representative India Human Development Survey, this paper demonstrates that college education enables women to lead substantively different lives from those of their less-educated peers. Results show that these women marry at later ages, have greater autonomy in choosing their husbands, and enjoy more egalitarian relations within marriage. Moreover, having higher and equal education vis-a-vis their husbands provides women with a relative advantage in critical decisions of their lives compared to women who are married to men with higher educational attainment than themselves. Hence, college education among women is instrumental in bringing about cultural change, which is not always facilitated to the same extent by middle or secondary education.

Women’s Education and Marriage in India

Even though India is modernizing and more women are enrolled in institutions of higher learning, it remains a stronghold of traditional values as reflected in the female disadvantage in the intra-household allocation of resources as well as distribution of household chores (Zimmermann, 2012; Lin & Adserà, 2013; Singh & Mukherjee, 2018). Girls fall behind in school enrollment (Woodhead et al., 2013), grade attainments (Bose, 2012), and investments in education (Zimmermann, 2012; Sahoo, 2017). Moreover, the educational attainment of women continues to be circumscribed by social institutions such as the family, caste, and religion (Siddhu, 2011; Jayachandran, 2015). For instance, Maertens (2013) notes that perceptions of the ideal age of marriage for girls significantly restrict parents' educational aspirations for their daughters in rural India. Moreover, scholars note that education is perceived to increase girls' desirability in the marriage market as it makes women more efficient at housekeeping, caregiving, and child-rearing (Jeffery & Jeffery, 1996; Vlassoff, 1996; Nambissan, 2005). Therefore, the instrumental value of education is defined within the realm of traditional gender roles, and higher formal education is not deemed necessary for meeting these expectations (Maertens, 2013). Besides, anthropological studies have documented that higher education among girls is perceived to result in the creation of “spoiled brides” who are more likely to develop pre-marital romantic alliances and engage in flirtatious behavior in college (Still, 2011; Osella & Osella, 1998). Such girls are assumed to be unable to engage in labor-intensive work and require expensive equipment for daily chores (Still, 2011). Hence, advanced education may be perceived as leading women away from their traditional roles.

Notwithstanding these expectations, there has been an increase in the number of years of education women receive in India. These could be due to structural factors such as increased opportunities for higher education or changing aspirations of parents or their daughters. Greater returns may also be expected from a college education in the marriage market. Figure 1 maps women’s educational levels across marriage cohorts in the IHDS data, and it documents a distinct shift out of low levels of education in recent cohorts to middle and secondary education. Additionally, there is a rise in the proportions of women who have received high school and college education in the more recent marriage cohorts. Along with the trends documented earlier (Joshi & Ahir, 2019; Ministry of Human Resource Development, 2019), it is expected that more women would be entering marriage with higher levels of education.

Due to these developments, the gender gap in education is also anticipated to decrease over time. As shown in Figure 2, the mean years of schooling for this sample have increased over time for both men and women, but the gap in educational attainment between men and women is narrowest for the most recent marriage cohort. Not surprisingly, recent studies have also documented a decline in educational hypergamy and a considerable rise in educational hypogamy in India (Lin et al., 2020). Moreover, the authors note that the odds of being in a hypogamous marriage are four times higher for women with secondary and college education. These highly educated women gain economic mobility as they tend to marry men who belong to higher income families compared to their natal families (Lin et al., 2020). Given these trends, it is vital to examine the implications of such changes on the quality of women’s marital lives.

Women’s education is recognized to be a critical determinant of demographic processes such as age at marriage (Desai & Andrist, 2010; Jones & Yeung, 2014), fertility (Moursund & Kravdal, 2003), contraceptive use (Jejeebhoy et al., 2014), and child health outcomes (Vikram & Vanneman, 2020) in India. Considerable attention has also been devoted to the study of child marriage in India; low education among the parents and the child bride are determinants of child marriage (Marphatia et al., 2017; Modak, 2019). However, a closer examination is warranted on the effect of higher female education on age at marriage, partner selection, and marital quality in India, especially now as many more women enter university. Several studies have documented the role of female education in delayed and non-marriage in Asia (Jones, 2005; Jones & Gubhaju, 2009; Jones & Yeung, 2014). In particular, tertiary education of women emerges as one of the most critical factors determining the mean age at marriage and singlehood in Asia (Jones & Yeung, 2014). The authors further note that increased labor force participation and gender attitudes among women with tertiary education may drive the relationship between higher education and later age at marriage. Secondary and tertiary education also enable women to be in homogamous and hypogamous marriages, providing them with greater leverage vis-a-vis their equally or lower educated husbands (Lin et al., 2020).

Although rising education levels among women may suggest concomitant increases in female labor force participation rates, this has not been observed in India and several other developing countries (Klasen, 2019). In India, female participation in the labor force remains low and follows a U-shaped distribution with education (Chatterjee et al., 2018; Klasen, 2019). Chatterjee et al. (2018) report that the odds of labor force participation decline steadily from no education (53.3%) to completed secondary school (22.4%), after which they increase slightly for college-educated women (28%). However, college-educated women engage in work that is qualitatively distinct from the kind undertaken by their less-educated peers, with a large majority (79%) of them in salaried positions . Hence, even though college education does not lead to comparable gains in labor force participation, it does allow college-educated women to obtain positions that offer relatively higher pay and other benefits.

Research has documented the role of structural transformations such as women’s increased labor force participation and a decline in men’s relative economic status in altering gender roles as men take on more housework (Bittman et al., 2003; Raley et al., 2012). Although rising female education has not led to significant increases in labor force participation among women in India, I argue that higher education is associated with greater bargaining power and a desire for gender equality within marriage. These are likely to be manifested in interactions with family members such as parents, husbands, and in-laws, as college-educated women negotiate for more favorable terms for themselves in different domains of their lives.

Data and Sample

The India Human Development Survey (IHDS) is a nationally representative face-to-face survey of over 41,554 households across all Indian states and union territories (with the minor exceptions of the Andaman and Nicobar Islands and Lakshadweep). It covers both urban and rural areas, including 1503 villages and 971 urban blocks. The IHDS is carried out jointly by the University of Maryland and the National Council of Applied Economic Research. This article uses the second wave of the survey, which was carried out in 2011–12. The overall response rate was 92% (Desai & Vanneman, 2015). I use a sample of 35,561 currently married women aged 15–55 years who were married in and after 1970.

Independent Variables

Education

Women’s education is measured using a series of dichotomous variables representing her level of education: no education, any primary education, any secondary education, any high school education, incomplete college education, and completed college education (bachelors and above bachelors). In India, it is unusual for women to continue schooling once they start cohabitating with their husbands after marriage (called gauna); hence their education can be presumed to be completed before the woman moved to her husband’s residence.

For a subset of the outcome variables that evaluate the quality of marital life, the implication of being in a hypogamous marriage (wife with higher education than husband) and homogamous marriage (wife with equal education as husband) compared to being in a hypergamous marriage (wife with lower education than husband) is also carried out. Since education is measured as the number of years of education from 0 to 16 (15 indicating bachelor’s degrees and 16 indicating education above bachelor’s degrees), a continuous variable is created to measure the spousal difference in educational levels. From this continuous variable, three distinct categories are created to indicate educational hypogamy, homogamy, and hypergamy.

Outcome Variables

Age at Marriage and Gauna

Women in the survey were asked about their age at marriage and gauna. In several parts of India, girls may get married at a very young age, but cohabitation and sexual relations do not begin until a ceremony called gauna or bidai takes place (Joshi et al., 2001). The gap between the marriage ceremony and gauna may extend to several years until the girl attains puberty or is deemed mature to begin a marital relationship (Joshi et al., 2001). After marriage, the bride resides with her parents until the formal gauna ceremony occurs, after which she resides with her husband. Some girls may continue their education after getting married, but this is typically before the gauna ceremony. Therefore, the analysis is carried out for both age at marriage and gauna.

According to the National Family and Health Surveys (NFHSs), age at marriage has been increasing over time in India, but change has been slow as the mean age at marriage continues to be low. For instance, the mean age at marriage among women between the ages of 15–49 was 17 years in 2005–06 and 19 years in 2015–2016.

Marriage-Related Decision Making before Marriage

A series of questions were asked to currently married women to assess their role in the choice of spouse and whether they had the autonomy to interact with their future husbands before the marriage was fixed. They were asked, “Who chose your husband?” which could be answered using four options: respondent herself, respondent chose with her parents or relatives, respondent’s parents or relatives chose for her, and others. The last two categories were combined as the respondent did not play a significant role in the decision in either case.

The second question asked if the respondent could meet her future spouse, talk to him, or send him an email or chat on the internet before the marriage was fixed. Respondents were asked to select all the options that applied to them. Each category was converted into a dichotomous variable.

Marital Quality

Eligible women were asked questions to assess the quality of the marital relationship and communication. One question pertained to whether the respondent and her husband went out by themselves (with or without their children) for movies, mela (fairs), or to restaurants? This is measured as a dichotomous variable. Additionally, women were asked how frequently they talked to their husbands about (1) things that happen at work? (2) what to spend money on? (3) and about things that happen in the community, such as elections or politics? They were required to select an answer from the following categories: never, sometimes, and often. These three variables are combined into a communication scale as they strongly correlate with one another (alpha = .84).

Work and Financial Autonomy

Women’s work and financial autonomy are assessed using four variables—whether the respondent had the most say in decisions about her work, whether she engaged in full-time work, whether her name was on a bank account, and whether she had cash in hand for household expenses. All these are measured as dichotomous variables.

Control Variables

A rich set of covariates are included in all the analyses. A control for husband’s education is included and measured similarly as women’s education: no education, any primary education, any middle and lower secondary education, senior high school, incomplete college education, and completed college education. Husband’s education is included in all but one analysis, choice of husband, as that decision is undertaken primarily in consultation with the natal family. Assets reflect the long-term economic status of the household as measured by the possession of housing goods and amenities. The asset scale sums 30 dichotomous items measuring household possessions and housing quality. A quintile measure of household assets is included. Religion and caste identification of the household is also included in the analysis. Caste is included in five broad categories: Brahmins, other forward castes (includes an undefined category called “other castes”), other backward classes, scheduled castes, and scheduled tribes. Religion is divided into Hindu, Muslim, Christian, and other minority religions. To examine women’s education and marriage patterns over time, ever-married women are categorized into four marriage cohorts, based on the calendar year their marriage took place: 1970–79, 1980–89, 1990–99, and 2000–12. Marriage cohort is considered a better measure of period effects than birth cohorts (Allendorf & Pandian, 2016); hence, it is included in this analysis. A total of 10,853 women did not report their year of marriage but reported their current age and age at marriage; these variables are used to calculate the length of the marriage, and their year of marriage was imputed using the length of the marriage. Analysis with imputed values is largely congruent with analysis without the imputed values. Additionally, the spousal age difference is also included as a control variable in all the analyses.

For age at marriage and gauna and marriage-related decision making, additional variables are included in the analyses: education of respondent’s parents and her childhood place of residence being the same village or town as her husband, another village, another town, or metropolitan area. There are no indicators of her natal family’s economic status at the time of marriage, and hence as a proxy, the current SES status of the respondent is used. For analyses on post-marriage quality of life and financial agency, women’s age, employment status (unemployed; part-time or seasonal work of fewer than 2000 hours per year; full-time work of at least 250 days and at least 2000 hours per year), and presence of mother-in-law in the household are included as controls. All analyses control for the state of residence and whether the respondent lives in an urban or rural area.

Methods

Regression analyses are carried out using the second wave of the IHDS to assess the relationship between women’s education and the outcome variables with all the aforementioned control variables. For age at marriage and gauna, OLS analyses are carried out for our sample of married women. For marriage-related decision making prior to marriage, multinomial logit analysis is used to analyze autonomy in the choice of husband as the dependent variable has three unordered discrete categories (respondent chose herself, respondent chose with her parents or relatives, and respondent’s parents or relatives chose for her). For contact with the husband before marriage, logistic analyses are undertaken for all three outcomes: 1) meeting the spouse; 2) talking to him; and 3) sending him an email or chatting on the internet. Logistic analyses are also undertaken to examine family outings with husband and work and financial autonomy (respondent having the most say in her work decisions, having her name on a bank account, and having cash for household expenditures). Ordinal logistic regressions are used to analyze the frequency of communication between the couple.

Results

Age at Marriage and Gauna

We start with a bivariate analysis of women’s education and age at cohabitation with husband (gauna) by marriage cohort. The trend is similar for age at marriage (shown in the appendix). As shown in Figure 3, the relationship between education and age at cohabitation follows a linear trend. The age at gauna increases incrementally with increases in the level of education across all cohorts. However, in the more recent cohorts, the gains from a college education are the largest—a 5–6 year difference is observed in the age of marital cohabitation between uneducated and college-educated women. In the 1970s marriage cohort, college education did not lead to a substantial delay in cohabitation as the difference between uneducated and college-educated women was a little over 3 years and women across several educational categories married as a child. In the recent marriage cohorts, women across all educational groups married and cohabited at later ages. However, compared to earlier cohorts, the difference in age at marriage and cohabitation between the least and most educated women is higher in the recent cohorts suggesting that higher education is emerging as a significant differentiator of age at cohabitation.

Similarly, the gap between age at marriage and age at cohabitation follows a robust educational gradient (not shown). The gap is largest for uneducated women, presumably because a large proportion of them married as children and thus their gauna was deferred, and lowest for college-educated women. However, as the age at marriage has risen, the time gap between marriage and gauna has decreased.

Regression analyses also show the positive association of education with age at marriage and gauna, with college education boosting both the age at marriage and gauna by over 3 years holding all other variables constant. The size of the coefficient for some college and high school education is half the size of a college education. Compared to those married in the 1970s, women who married in the 2000s were married over 3 years later. On the other hand, the husband’s education has a much weaker effect on the age at marriage and gauna. Interestingly, mother’s education is also positively associated with later age at marriage and gauna of their daughters but not father’s education (Table 1).

Table 1.

Education and Age at Marriage and Gauna.

	Age at Marriage	Age at Gauna
Women’s education: primary (ref: uneducated)	0.12* (0.06)	0.01 (0.05)
Middle school	0.59*** (0.06)	0.49*** (0.06)
High school	1.34*** (0.10)	1.30*** (0.09)
Some college	1.46*** (0.21)	1.37*** (0.19)
Completed college	3.18*** (0.12)	3.11*** (0.12)
Husband’s education: primary (ref: uneducated)	−0.13* (0.07)	−0.11 (0.06)
Middle school	−0.20** (0.06)	−0.06 (0.05)
High school	0.02 (0.09)	0.18* (0.08)
Some college	0.00 (0.17)	0.19 (0.17)
Completed college	0.31** (0.10)	0.51*** (0.09)
Mother’s education	0.04*** (0.01)	0.04*** (0.01)
Father’s education	0.00 (0.01)	0.00 (0.01)
Marriage cohort: 2000s (ref: 1970s)	3.38*** (0.08)	2.46*** (0.07)
1990s	2.15*** (0.07)	1.43*** (0.07)
1980s	1.52*** (0.07)	1.00*** (0.07)
Constant	16.53*** (0.17)	17.63*** (0.17)
Observations	34,995	34,998
R-squared	0.395	0.350

Robust standard errors in parentheses; controls included but not shown: Standard of living, difference in age between the respondent and her husband, women’s natal place (same village as her husband, another village, another town, and metropolitan area), caste, religion, urban, and state of residence controls; ***p < 0.001, **p < 0.01, and *p < 0.05.

Marriage-Related Decision Making before Marriage

Autonomy in the choice of spouse

Figure 4 charts the bivariate relationship between education and autonomy in the choice of spouse. Women with a college education had greater autonomy in the choice of spouse, either self-selected or jointly determined with family members. Autonomy in choosing a husband follows a gradient as women enjoy greater autonomy with each additional level of education. However, even for the college-educated group, only 42% had a say in the choice of their spouse in the most recent marriage cohort indicating that 58% of these women had no say in deciding their future husband. Similarly, as observed in Figure 5, the frequency of meeting and talking to a potential spouse over the phone increases incrementally with higher education. However, the largest increases are observed after middle school. 47% of women with a college education had the opportunity to meet and talk to their potential spouses before selecting them. Communicating via emails or over the internet also increases with middle school education, but the use of internet tools for communication is low. Even among those who completed college, only 10% reported using online tools for communication.

Multinomial logistic estimates show that having a college education, both partial and complete, significantly increases the log-odds that the respondent solely chose her spouse relative to the spouse being selected by others (odds ratio of 2.5 and 2.3, respectively). Having middle and high school education also increases the log-odds of a woman choosing her husband compared to uneducated women (odds ratio of 1.5 and 1.4, respectively), but the coefficient size is about half compared to those with a college education. Being college-educated also increases the odds of a woman having jointly selected her husband with family members compared to women whose family made the selection for them. Having a high school education is also a significant determinant of joint decision making with parents. Furthermore, mother’s education also increases the respondent’s autonomy in this regard. Lastly, results show that women who married in the 2000s had significantly greater autonomy in choosing their spouses than those of earlier cohorts (Table 2).

Table 2.

Education and Choice of Husband, Log odds.

	Respondent Chose Husband	Respondent and Parents/Relatives Chose Husband Together
Women’s education: primary (ref: uneducated)	0.18 (0.13)	−0.00 (0.07)
Middle school	0.41*** (0.12)	0.04 (0.06)
High school	0.35* (0.17)	0.18* (0.08)
Some college	0.90* (0.37)	0.19 (0.16)
Completed college	0.80*** (0.18)	0.33*** (0.10)
Mother’s education (continuous)	0.07*** (0.02)	0.04*** (0.01)
Father’s education (continuous)	−0.02 (0.01)	−0.01 (0.01)
Marriage cohort: 2000s (ref: 1970s)	0.88*** (0.18)	0.27** (0.10)
1990s	0.48** (0.18)	0.15 (0.10)
1980s	0.39* (0.19)	0.06 (0.10)
Constant	−4.02*** (0.48)	−1.32*** (0.16)
Observations	34,996	34,996

Robust standard errors in parentheses; controls included but not shown: Standard of living, difference in age between the respondent and her husband, women’s natal place (same village as the husband, another village, another town, and metropolitan area), caste, religion, urban, and state of residence controls; ***p < .001, **p < .01, and *p < .05.

Contact with husband before marriage was finalized

The logistic regression results show that education is associated with meeting potential spouses, talking on the phone with them, and exchanging emails and messages over the internet before the marriage was fixed. However, the magnitude of the impact of a college education is more robust than that observed for other levels of education—having high school and college education double the odds of meeting husband (a potential spouse) before marriage was fixed when compared to uneducated women. Women with high school and college education are four times as likely to speak to their potential spouse on the phone than those who are uneducated. Although talking on the phone is common before marriage, the odds increase steeply with each additional level of education. However, chatting on the internet or exchanging emails with a potential spouse is primarily done by college-educated women. Those women who have completed college are three times as likely to chat on the internet or exchange emails than those women who are uneducated. Women with high school education also exchange emails and chat on the internet, but the results are not significant for women of other educational categories. Women in recent marriage cohorts are much more likely to interact with potential spouses than earlier cohorts, especially through telephone conversations (Table 3).

Table 3.

Education and Contact with Husband Before Marriage, Odds Ratio.

	Respondent met Husband Before Marriage	Respondent Spoke to Husband on the Phone	Sent Email/Chatted Online
Women’s education: primary (ref: uneducated)	1.18** (0.07)	1.68*** (0.18)	1.30 (0.52)
Middle school	1.44*** (0.09)	3.06*** (0.32)	1.39 (0.42)
High school	1.82*** (0.16)	4.32*** (0.53)	2.45* (0.87)
Some college	2.21*** (0.37)	4.03*** (0.76)	1.67 (0.72)
Completed college	1.85*** (0.18)	4.62*** (0.62)	2.98** (1.00)
Husband’s education: primary (ref: uneducated)	0.90 (0.06)	1.03 (0.13)	1.01 (0.38)
Middle school	1.03 (0.07)	1.09 (0.12)	0.96 (0.25)
High school	1.07 (0.09)	1.33* (0.17)	1.14 (0.33)
Some college	1.05 (0.17)	1.87** (0.38)	0.82 (0.37)
Completed college	1.05 (0.10)	1.30* (0.17)	1.48 (0.45)
Mother’s education (continuous)	1.04*** (0.01)	1.08*** (0.01)	1.11*** (0.02)
Father’s education (continuous)	1.00 (0.01)	0.99 (0.01)	1.00 (0.02)
Marriage cohort: 2000s (Ref: 1970s)	3.47*** (0.32)	15.24*** (3.71)	5.88** (3.27)
1990s	2.09*** (0.19)	3.59*** (0.88)	1.70 (0.94)
1980s	1.45*** (0.13)	1.66* (0.42)	1.18 (0.68)
Constant	0.16*** (0.03)	0.01*** (0.00)	0.00*** (0.00)
Observations	34,845	34,842	34,831

Robust standard errors in parentheses; controls included but not shown: Standard of living, difference in age between the respondent and her husband, women’s natal place (same village as husband, another village, another town, and metropolitan area), caste, religion, urban, and state of residence controls; ***p < .001, **p < .01, and *p < .05.

Marital Quality

As definitions of what constitutes a “good” marriage are likely to vary across contexts, finding suitable indicators of marital quality is not straightforward. However, having conversations and spending time together are critical aspects of a marital relationship as they indicate intimacy between the couple. In India, physical and verbal expressions of intimacy between a couple are usually not displayed in public or discussed openly. However, visiting public places together is a commonly accepted practice. Hence, this study utilizes two indicators that capture two dimensions of marital quality that can be measured efficiently with a survey in India to indicate the degree of spousal closeness. The first question asked whether the women went out with their husbands (with or without their children) to watch movies, attend fairs, or dine at restaurants. The second pertained to the frequency of conversations about (1) things that happen at work, (2) what to spend money on, and (3) events in the community, such as elections or politics, measured using the following categories: never, sometimes, and often. These three dimensions are combined to represent the frequency of conversations with spouse across a range of topics.

We start with a bivariate description of the relationship between education and the frequency of family outings (Figure 6). Across all the cohorts, it is evident that higher education increases the likelihood of family outings, with college-educated women most frequently engaging in such jaunts. Regression analysis also reveals an almost linear relationship between women’s education and outings with their husbands (Table 4). Each additional level of education is associated with a stronger likelihood of family outings. College-educated women are almost three times as likely to go out with their husbands (with or without their children) for movies, mela (fairs), or restaurants compared to uneducated women, holding all the variables constant.

Table 4.

Education and Marital Quality, Results Presented as Odds Ratio.

	Outings with Husband	Communication with Husband
Women’s education: primary (ref: uneducated)	1.16** (0.06)	1.01 (0.04)
Middle school	1.48*** (0.07)	1.20*** (0.05)
High school	1.84*** (0.14)	1.32*** (0.08)
Some college	2.37*** (0.42)	1.72*** (0.24)
Completed college	2.75*** (0.28)	1.53*** (0.12)
Husband’s education: primary (ref: uneducated)	1.07 (0.06)	1.05 (0.04)
Middle school	1.07 (0.05)	1.15*** (0.05)
High school	1.11 (0.08)	1.16** (0.06)
Some college	1.04 (0.15)	1.26 (0.15)
Completed college	1.28** (0.10)	1.14* (0.07)
Marriage cohort: 2000s (ref: 1970s)	1.23 (0.14)	1.22* (0.11)
1990s	1.20* (0.11)	1.22** (0.09)
1980s	1.06 (0.07)	1.12* (0.06)
/cut1		0.25*** (0.05)
/cut2		0.50*** (0.10)
/cut3		1.47 (0.29)
/cut4		5.96*** (1.19)
/cut5		10.87*** (2.17)
/cut6		25.48*** (5.12)
Constant	0.54* (0.14)
Observations	35,181	35,356

Robust standard errors in parentheses; controls included but not shown: Standard of living, difference in age between the respondent and her husband, caste, women’s employment status (part-time and full-time), religion, urban, and state of residence controls; ***p < .001, **p < .01, and *p < .05.

Women’s education is significantly associated with conversations with their husbands, and the odds increase with each additional level of education, although the increases are less steep than those observed for outings with husbands (Table 4). Moreover, women with primary education are not significantly different from uneducated women, our reference category. Surprisingly, the coefficient for women who received some college education is stronger than for those who completed college education. Husband’s education also increases the odds of communication, but the coefficient size is quite similar across the significant categories, that is, middle school, high school, and completed college.

Additional analyses are also carried out to test if educational homogamy or hypogamy, where women are equally or more educated than their husbands, leads to greater communication between the couple. In these results, we exclude education variables from the analyses to prevent collinearity. The results (Table 5) show that being in a hypogamous marriage is associated with more outdoor trips with the husband and higher communication than being in a hypergamous marriage. However, being in a homogamous marriage is not significantly different from being in a hypergamous one.

Table 5.

Education Differentials and Marital Quality and Communication, Results Presented as Odds Ratio.

	Outings with Husband	Communication with Husband
Hypogamous marriages	1.20*** (0.05)	1.09** (0.04)
Homogamous marriages(ref: hypergamous marriages)	1.02 (0.04)	0.98 (0.03)
/cut1		0.25*** (0.05)
/cut2		0.50*** (0.10)
/cut3		1.45 (0.29)
/cut4		5.86*** (1.16)
/cut5		10.67*** (2.11)
/cut6		24.96*** (4.95)

Robust standard errors in parentheses; controls included but not shown: Standard of living, difference in age between the respondent and her husband, women’s employment status (part-time and full-time), caste, religion, urban, and state of residence controls; ***p < .001, **p < .01, and *p < .05.

Work and Financial Autonomy

Even though labor force participation rates are low among women in India, a college education may endow women with greater financial and work autonomy. Each additional level of education is associated with higher odds of having cash-in-hand for household expenditures and having their name on a bank account. College-educated women are the most advantaged; they are four times more likely than uneducated women to have their name on a bank account. Surprisingly, the husband’s education does not predict if women have cash in hand or if their name is on a bank account. Women’s employment status, both part-time and full-time, confers greater access to financial resources via cash-in-hand and bank account.

College-educated women are significantly more likely to be the primary decision-maker about their work and are also more likely to be engaged in full-time work. High school education also offers some benefits, but other educational categories are not significant predictors for the two outcomes as compared to the reference group. On the other hand, husband’s education seems to reduce a woman’s decision-making autonomy about her work but is unrelated to her full-time employment (Table 6).

Table 6.

Education and Financial and Work Autonomy, Odds Ratio.

	Cash-In-Hand	Bank Account has Respondent’s Name	Primary Decision-Maker About Work	Full-Time Work
Women’s education: primary(ref: uneducated)	1.22* (0.10)	1.09 (0.07)	1.09 (0.06)	0.94 (0.08)
Middle school	1.26** (0.11)	1.52*** (0.09)	1.08 (0.06)	0.87 (0.08)
High school	1.31* (0.16)	2.13*** (0.18)	1.29** (0.10)	1.40* (0.19)
Some college	1.41 (0.39)	3.04*** (0.52)	2.23*** (0.38)	2.87*** (0.63)
Completed college	1.72** (0.29)	5.17*** (0.53)	2.36*** (0.22)	4.39*** (0.57)
Husband’s education: primary(ref:uneducated)	0.88 (0.08)	0.92 (0.07)	0.87* (0.05)	1.14 (0.10)
Middle school	0.89 (0.08)	0.97 (0.06)	0.77*** (0.04)	0.89 (0.08)
High school	0.86 (0.10)	0.93 (0.08)	0.70*** (0.05)	0.82 (0.10)
Some college	1.00 (0.25)	0.80 (0.12)	0.66** (0.10)	0.70 (0.17)
Completed college	0.78 (0.10)	1.04 (0.09)	0.69*** (0.06)	1.00 (0.13)
Women’s employment: Part-time work(ref: not employed)	1.24** (0.08)	1.40*** (0.07)
Full-time work	1.86*** (0.26)	1.84*** (0.14)
Marriage cohort: 2000s(ref: 1970s)	2.38*** (0.45)	1.15 (0.16)	1.12 (0.14)	1.53 (0.34)
1990s	2.97*** (0.45)	1.46*** (0.15)	1.22* (0.12)	2.18*** (0.35)
1980s	1.68*** (0.21)	1.25** (0.10)	1.16 (0.09)	1.71*** (0.22)
Constant	0.47* (0.18)	0.12*** (0.04)	0.20*** (0.06)	0.01*** (0.01)
Observations	35,439	25,036	29,259	35,486

Robust standard errors in parentheses; controls included but not shown: Standard of living, difference in age between the respondent and her husband, caste, religion, urban, and state of residence controls; ***p < .001, **p < .01, and *p < .05.

Additional tests show that being in a hypogamous marriage is associated with higher financial and work autonomy compared to being in a hypergamous marriage. Homogamy also provides greater agency in employment, full-time work, and having one’s name on a bank account. This suggests that higher or equal education vis-a-vis their spouse allows women to negotiate for greater financial autonomy, or it may be granted to them because of their educational status (Table 7).

Table 7.

Education Differentials and Work and Financial Autonomy, Results Presented as Odds Ratio.

Variables	Cash-In-Hand	Bank Account has the Respondent’s Name	Primary Decision-Maker About Work	Full-Time Work
Hypogamous marriages	1.23** (0.08)	1.45*** (0.07)	1.33*** (0.06)	1.28*** (0.09)
Homogamous marriages(ref: hypergamous marriages)	1.11 (0.07)	1.19*** (0.05)	1.31*** (0.05)	1.38*** (0.09)
Women’s employment: part-time(ref: not employed)	1.23** (0.08)	1.36***(0.07)
Full-time work	1.87*** (0.26)	1.98*** (0.15)
Constant	0.41* (0.15)	0.08*** (0.02)	0.13*** (0.04)	0.01*** (0.00)
Observations	35,439	25,036	29,259	35,486

Discussion and Conclusion

This article focuses on the increased autonomy of college-educated women in India across several critical dimensions of marriage. Although the proportion of women in India with a college education is relatively low, recent trends in higher education forecast that more women shall enter marriage with a college education in the future. Gains in educational attainment among women are likely to have significant consequences for family life as higher education may expose them to egalitarian ideals, increase their awareness, self-confidence, and communication abilities. These factors may provide them a relatively higher status within families by virtue of their educational attainment, or they may advance their circumstances by negotiating more favorable terms with their natal and marital families.

This paper demonstrates that higher education in India, particularly college education, enables women to exercise agency in their lives' consequential decisions. College-educated women tend to marry at later ages, have higher autonomy in choice of spouse, and have a greater opportunity to evaluate potential spouses' suitability in arranged marriages by meeting them and talking and texting with them on the phone and the internet. Additionally, it increases marital quality as reflected in marital communication and family outings and affords them greater financial and work autonomy. Although it is not possible to rule out endogeneity, the observed relationships remain robust to the addition of several relevant control variables, which suggests that the observed association is not merely a consequence of higher parental or spousal education and economic status. As noted previously by Lin and colleagues (2020), the odds of being in a hypogamous marriage increase disproportionately for women with a college education. The results show that women gain autonomy in hypogamous marriages and occasionally in homogamous marriages, suggesting that women use their higher or equal educational status vis-a-vis their husbands’ to gain greater autonomy and equality within marriage.

Several studies note the remarkable continuity of traditions in India’s marriage patterns and emphasize how caste and class boundaries remain rigid even today (Goli et al., 2013; Desai & Andrist, 2010; Allendorf & Pandian, 2016). In this paper, I argue that modernity in marriages should also be evaluated within the contours of acceptable norms in contemporary India. A significant shift to autonomous “love marriages” with little or no parental role remains far-fetched within Indian society, and so do marital alliances across religious and caste groups, but that should not obfuscate our view of changes that are occurring in India. This paper demonstrates that higher education gradually erodes traditional practices as these women exercise much greater control over several critical decisions of their lives. Furthermore, as more women achieve a higher or equal educational status as their spouses, a cultural shift can be observed as gender hierarchies become more fluid and women gain autonomy within marriages.

Apart from documenting the influence of college education on women’s lives, this article also highlights temporal changes in women’s marriage patterns. Results show that age at marriage and post-marital cohabitation increase for women in the recent marital cohorts relative to those married in the 1970s. Similarly, the probability of self-selecting the spouse has significantly increased in the recent cohorts. For joint decisions with parents regarding the choice of future husband, only women in the most recent marriage cohort (2000–2012) are significantly more likely to do so. Moreover, the likelihood of meeting potential partners and chatting with them over the telephone or the internet to assess suitability for marriage has increased exponentially for women married in the more recent cohorts. These choices are consequential because they also portend higher autonomy after marriage (Banerji and Deshpande, 2021).

These trends accompanied by the increasing educational attainment of women indicate a significant cultural change in the family lives of Indian women and augur more egalitarian spousal relationships, particularly for women with a college education.

Supplemental Material

Supplemental Material - Modern Marriage in a Traditional Society: The Influence of College Education on Marriage in India

Supplementary Material for Modern Marriage in a Traditional Society: The Influence of College Education on Marriage in India by Kriti Vikram in Journal of Family Issues.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Kriti Vikram

Supplemental Material

Supplemental material for this article is available online.

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