Abstract

Education matching has become a key principle for the construction of marriage relationships in China. Meanwhile, with the improvement of women’s social status over the years, greater equality is emerging between the two sexes in traditional marriages. Questions about how educational assortative mating may transform couples' lives, marital satisfaction, and within‐family gender inequality have gained increasing attention. Based on China Family Panel Studies (CFPS) 2014 data, we matched information about married men with that of their wives to study the influence of the education gradient upon marital satisfaction. Couples were grouped into three categories—educational hypergamy (wives less educated than their husbands), homogamy, and hypogamy (wives more educated than their husbands). The findings showed that educational level positively predicted marital satisfaction. Specifically, hypergamy was linked to greater satisfaction among wives, while homogamy predicted greater satisfaction among husbands.

Keywords

Marital satisfaction; education; education match; China

Introduction

The marriage matching model is an important factor affecting one’s personal life and social structure. Akerlof (2000) argued that an increase in the proportion of assortative matching in the marriage market would exacerbate income inequality in society. Different marriage patterns can also have a significant impact on an individual's future life (Alexandra Killewald, 2013). With the rapid development of the economy and accompanying systematic changes in China over the past few decades, it is unclear how such changes have impacted marriage patterns – particularly with respect to the matching model. In addition, identifying the ideal marriage match has traditionally been a topic of public concern. For example, door-to-door and patriarchal systems have historically been the main approaches for mate selection, but as the economy has developed an increasing number of people choose to marry based on personal factors and “love”, and therefore the criteria for mate selection has grown more extensive (Mare, 1991). As such, the ways that varying marriage matching patterns impact life among married couples, particularly considering the more recent social and economic developments, are not well understood in China.

Previous research has begun to identify several factors that might alter marriage satisfaction, such as the age, occupation, family socioeconomic status and family concept of couples (Zhou, 2016). Educational level is considered a dominant component and manifestation of human capital, and it is the most important indicator of social and economic status. It has a decisive influence on the quality of life, professional achievement and social stratification of individuals. Schwartz (2010) argued that an individual's educational level ultimately affects their subjective well-being, where greater education level is associated with elevated “professional” status, which impacts access to resources and subsequently increases subjective well-being.

At the same time, education level also plays a decisive role in the quality of marriage. For example, research has shown that greater education level among married women provides greater employment opportunities (George A. Akerlof and Kranton, 2010), which impacts their dependence on husbands and, in turn, improves marriage quality (Alexandra Killewald, 2013). The degree of educational matching between a wife and husband not only determines the agglomeration of family resources and wealth, but also significantly affects the social stratification and mobility of the next generation through intergenerational transmission. More importantly, educational matching is related to the broader sense of “wife” and “husband”, and in that respect the degree of a “normal match” is closely related to the quality of marriage (Yan, 2011).

Marriage matching can broadly refer to the degree of matching between men and women in age, education, marriage, household registration, etc. It is an effective indicator for assessing the openness of social structure and is a strong focal point of current marriage and family research (Raley, 2010). Gradient matching is one of the most common forms of marriage matching. Gradient matching suggests that, when choosing a spouse, women tend to look for classifications that are higher than their own condition. From the perspectives of religion, occupation, family background and income, previous research has found that the average index of women in marriage matching is lower than that of men. Thus, women tend to choose marriage partners who have a higher level on many of these factors. This is true of education where, according to the theory of marriage gradient, the proportionate degree of education is greater among males than among females (Singer and Willett, 2009).

In the United States, in light of the recent gender‐gap reversal in educational attainment, there has been a growing number of couples in which wives have more education than their husbands (Yue, 2017). Consistent with this, the traditional practice of women “marrying up” in terms of education level is eroding (Esteve, 2012). These profound changes in marriage patterns have spurred increased attention to the impact of educational assortative mating on marital and family lives (A Killewald and García-Manglano, 2016). One area that remains underdeveloped is how educational assortative mating may transform the long‐term economic advancement of married women and men.

Further, the notion of “linked lives” suggests that the manner in which income evolves for both spouses during the course of a marriage depends not only on their own educational levels but also their education relative to that of their spouse (Blossfeld and Buchholz, 2009). With the polarization of employment into high‐skill, high‐wage jobs and low‐skill, low‐wage jobs, education has become the leading indicator of earnings capabilities (Hout and Diprete, 2006). Similarly, with the increase in dual‐earner families, both spouses (although especially wives) have become more likely to convert education into earnings (Blossfeld and Buchholz, 2009). As an indicator of comparative advantage in market activities, married individuals’ education relative to that of their spouses may very well shape their long‐term income trajectories. However, previous research has found that spousal attributes (e.g. human capital, long work hours) has a greater impact on the careers of wives compared to husbands (Shauman, 2010).

In traditional Chinese society, men are always expected to take on a greater share of responsibilities and occupy a more dominant position compared to women. If a man finds a woman with a better background and a stronger ability than himself, he may experience some negative social and personal repercussions due to perceived “violation” of these traditional customs (Juhua and Zhaohua, 2014). The extra psychological cost may therefore weaken his level of marital satisfaction. In contrast, there are some direct financial benefits to this situation, which may increase marital satisfaction due to reduced social and financial struggles. In a similar way in this marriage situation, the wife may experience variable levels of satisfaction in that her relative status and position may afford her the ability to make life choices. In this respect, marriage matching would have a significant impact on life over the course of a marriage (Luo and Klohnen, 2005).

The purpose of the present study was to investigate the relationship between education matching on marital satisfaction in a Chinese sample. Specifically, it was predicted that: (1) Education will be positively related to marriage satisfaction, (2) Marriage satisfaction will be greater among couples with matching education levels (homogomy) and (3) Mariage satisfaction will be greater when the husband’s education is higher than the wife’s (hypergamy).

Method

Data and Sample
In current research a correlational research design was utilized. As per (Fraenkel, & Hyun, 2012), a correlational research design is used to assess strength of association between multiple variables without altering them, making it a suitable choice for this research.

Research Methodology

The China Family Panel Studies (CFPS) is a nationally representative, annual longitudinal survey of Chinese communities, families, and individuals launched in 2014 by the Institute of Social Science Survey (ISSS) of Peking University, China. The CFPS is designed to collect individual-, family-, and community-level longitudinal data in contemporary China. The survey focuses on the economic and non-economic wellbeing of the Chinese population, with a wealth of information covering such topics as economic activities, education outcomes, family dynamics and relationships, migration, and health. The CFPS is funded by the Chinese government through Peking University.

According to the specific research needs, this paper focused on the relationship between education matching and marital satisfaction between wives and husbands. In order to create a suitable database, data was initially filtered to include those identified as married (removing those identified as divorced, cohabiting, unmarried, widowed etc.). Next, according to the method of Diener (1999), women were selected as subjects and then the family variable was matched where one married woman was selected in each household and her husband was matched using the family ID variable. To ensure the integrity of the husband's data, it was added to the female sample to form a three-dimensional database of the husband and wife.

Measurement

The dependent variable examined in this paper was marital satisfaction. The CFPS 2010 questionnaire allows respondents to self-evaluate overall marital satisfaction. The question “Are you satisfied with your marriage?” is scored on a 1-5 scale (1 = very dissatisfied, 2= dissatisfaction, 3 = general, 4 = satisfaction, 5= very satisfied).

The independent variables were based on questions regarding education and educational assortative mating. Individuals were asked about their own educational levels at the time of marriage (less than high school, high school diploma, some college, and college degree or higher). Educational assortative mating identifies a spouses' relative education, including educational hypergamy (husband's educational level is higher than that of wife), educational homogamy (husband's educational level is equal to that of wife; reference category), and educational hypogamy (husband's educational level is lower than that of wife). Such operationalization of the education‐related variables was used in recent research on patterns and consequences of educational assortative mating (Schwartz, 2010).

The selection of control variables was based on key variables that have a major impact on the explanatory variables in previous relevant literature. This included gender, age, income, age at marriage, number of children, ethnicity, region (urban/rural), religious beliefs, physical health, subjective and objective social economic status, and number of children. The number of children, age, age at marriage and income were treated as continuous variables.

Analytic Strategies

The latest version of Stata was employed for data analyses. T-tests or chi-square tests were used to compare the differences on categorical and continuous variables across groups. Logistic regression analysis was performed to examine the factors related to marital satisfaction, where the variables which were significant in the bivariate analysis were chosen as the independent variables.

Result

Table 1 illustrates the sample characteristics, as well as comparisons between wives and husbands on key variables utilized in the present study. The current sample was predominantly middle-aged. With respect to key comparison variables, there were significant differences between wives and husbands in income, religious beliefs, physical health, subjective SES, objective SES, education, educational assortative mating and marital satisfaction. Specifically, wives were slightly younger, had lower income, greater religious beliefs, slightly higher subjective and objective SES, and lower education compared to husbands. The data also showed that hypogamy was much less common than either homogamy or hypergamy.

Table 1. Comparison of socio-demographic and study variables (N=12,413)

Variables	Wives M±SD/f (%)	Husbands M±SD/f (%)	t/ χ2	p
Age	47.47 (14.10)	49.47 (14.36)	-66.62	0.000
Income	8,064.18 (16,969.55)	16,382.77 (24,594.96)	-24.62	0.000
Income2	19.23 (2.11)	20.21 (1.74)	-19.34	0.000
Region			0.30	0.768
Urban	5,524 (46.54%)	6,212 (53.12%)
Rural	6,345 (53.46%)	5,483 (46.88%)
Number of children	1.37 (0.90)	1.37 (0.90)	1.28	0.199
Religious beliefs			16.95	0.000
No	8,919 (71.85%)	9,794 (78.90%)
Yes	3,494 (28.15%)	2,619 (21.10%)
Physical health	2.84 (1.25)	3.07 (1.22)	-16.97	0.000
Age at marriage	22.87 (15.12)	22.62 (14.08)	-0.50	0.616
Subjective SES	3.18 (0.97)	3.15 (0.92)	3.42	0.000
Objective SES	38.35 (8.67)	37.54 (8.76)	5.58	0.000
Education
Primary school	2,690 (23.56%)	3,149 (26.09%)	-4.06	0.000
Junior school	3,059 (26.79%)	3,948 (32.71%)	-11.93	0.000
High school	1,278 (11.19%)	1,777 (14.72%)	-9.85	0.000
Some college	439 (3.84%)	564 (4.67%)	-4.56	0.000
College or above	234 (2.05%)	333 (2.76%)	-5.20	0.000
Educational   assortative mating
Hypergamy (H > W)	4,583 (40.56%)
Homogamy (H = W)	4,596 (40.68%)
Hypogamy (H < W)	2,120 (18.76%)
Marital satisfaction	4.38 (0.95)	4.56 (0.81)	-17.54	0.000

        Notes: SES = Social Economic Status, H = Husband, W = Wife

Logistic regression analysis was used to explore potential predictors of marital satisfaction, including all variables from Table 1. Table 2 shows the outcomes separated across wives (Models 1 and 2) and husbands (Models 3 and 4). The outcomes demonstrate that, within the sample of wives, there was a significant effect of “superior” status, where marrying a husband of higher “standing” increased her level of marital satisfaction. Models 1 and 2 both show that income, self-rated health, education (primary school as reference), subjective SES and objective SES had positive effects on women's marital satisfaction. Satisfaction was greater among wives in marriages with higher income, greater objective and subjective SES, who were in greater physical health, and reached junior school education (in comparison to primary school education). A similar pattern emerged for marital satisfaction among husbands in Models 3 and 4. The only area of difference between wives and husbands was that religious beliefs positively impacted satisfaction among wives but not husbands.

With respect to the key variable of interest of assortative mating (using hypogamy as the reference), the regression analyses showed that marital satisfaction was greater among women in hypergamous contexts, but greater among husbands in more homogomous arrangements.

Table 2. Logistic Regression Models for Marital Satisfaction.

Variables	Model 1		Model 2		Model 3		Model 4
Age	b	SE	b	SE	b	SE	b	SE
Income	-0.005	0.005	-0007	0.006	-0.003	-0.003	-0.006	0.005
Income2	5.550	1.692	4.501	1.741	4.660	1.690	4.620	1.731
Region	3.172***	1.121	3.172***	1.113	3.281***	1.113	3.290***	1.131
Number of   children	-0.033	0.054	-0.038	0.057	-0.040	0.054	-0.047	0.056
Religious beliefs	-0.008	0.030	-0.004	0.031	-0.002	0.029	0.029	0.031
Physical health	0.243***	0.208	0.238***	0.211	-0.165	0.067	-0.170	0.071
Age at marriage	0.105***	0.022	0.106***	0.023	0.106***	0.022	0.107***	0.023
Subjective SES	0.009***	0.005	0.010	0.006	0.008	0.008	0.009	0.006
Objective SES	0.070***	0.027	0.066***	0.028	0.067***	0.027	0.062***	0.028
Education	0.001***	0.003	0.001***	0.003	0.001***	0.003	0.001***	0.003
Primary school   (ref.)
Junior school	0.065***	0.076	0.088***	0.086	0.086	0.076	0.066***	0.086
High school	0.002	0.092	0.034	0.103	0.020	0.092	0.196	0.102
Some college	0.172	0.125	0.210	0.135	0.140	0.125	0.193	0.135
College or above	0.154	0.136	0.215	0.168	0.131	0.154	0.020	0.169
Educational   assortative mating
Hypogamy (H <    W) （ref.)
Hypergamy   (H >    W)			0.103***	0.063			0.067	0.065
Homogamy    (H =    W)			-0.008	0.059			0.078***	0.046

        Note. *p<0.05, **p<0.01, ***p<0.001

Discussion

The present study found some level of support for the first hypothesis that marital satisfaction is related to education level. Specifically, for both wives and husbands, satisfaction increased significantly only as education level increased from primary to junior level. This does demonstrate that at least minimal increases in education level can impact future marital satisfaction, possibly to the extent that it at least increases slightly the potential for positive employment and lessens the risk of being in the most disadvantaged social and economic categories. However, given that assortative matching was also a significant predictor of satisfaction, these outcomes may indicate that absolute education level is less relevant to marital outcomes than relative or comparative levels between spouses. In this respect, the second and third hypotheses were partially supported in that they demonstrated a differential impact on marital satisfaction between wives and husbands. Specifically, marital satisfaction was greater for wives when the husband had greater education but was greater for husbands when there was matched levels of education.

In some ways, the present outcomes do suggest that Chinese society still maintains a traditional marriage education matching structure of “the husband is higher and the wife is lower” at the macro level. This was more evident for marital satisfaction among the women in the current sample, but was also indirectly evident among men in that marital satisfaction was lowest when the wife had higher educational status than the husband. This conclusion is consistent with previous findings of continued evidence for “upward marriage” among women in current Chinese culture.

It is important to observe, however, that the present outcomes do support the possibility of change in the notion that men should have “greater” education in a marriage to the extent that marital satisfaction was greatest among men when there was matched education. While having a wife with greater education may be seen as a cultural specific threat to men in some respects, there may be strong benefits to having a wife with equivalent education levels – predominantly in terms of economic and family social position. Specifically, having higher education could potentially mean higher employment positions for wives, which may translate into greater long-term income potential.

It should be noted, of course, that marriage is a long process, and due to the lack of historical or longitudinal data regarding participants’ marriages, the current data reflects only a brief cross-sectional view of the included factors. Future research may benefit from an examination of more historical data to gain a more dynamic understanding of how satisfaction changes as key factors such as education, economic status, family dynamics, and employment emerge and transform over time.

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