Abstract

This article describes trends in parental wealth homogamy among union cohorts formed between 1987 and 2013 in Denmark. Using high-quality register data on the wealth of parents during the year of partnering, we show that the correlation between partners’ levels of parental wealth is considerably lower compared with estimates from research on other countries. Nonetheless, parental wealth homogamy is high at the very top of the parental wealth distribution, and individuals from wealthy families are relatively unlikely to partner with individuals from families with low wealth. Parental wealth correlations among partners are higher when only parental assets rather than net wealth are examined, implying that the former might be a better measure for studying many social stratification processes. Most specifications indicate that homogamy increased in the 2000s relative to the 1990s, but trends can vary depending on methodological choices. The increasing levels of parental wealth homogamy raise concerns that over time, partnering behavior has become more consequential for wealth inequality between couples.

Introduction

Partnering behavior is a key determinant of various aspects of well-being (Schwartz 2013). From an economic point of view, marriage and cohabitation are a foundation for sharing many public goods, specialization, risk pooling, and the coordination of domestic labor among partners (Browning et al. 2014). Therefore, it is unsurprising that couples do not form at random or irrespective of partner’s characteristics and that marital sorting is a key feature of marriage models (Becker 1973, 1991; Lam 1988). Social scientists have long documented patterns of assortative mating based on ascribed characteristics, such as parental occupation and ethnicity (Kalmijn 1998; Schwartz 2013), as well as on acquired characteristics, such as education and earnings (Blossfeld 2009; Pencavel 1998; Rosenfeld 2008; Schwartz 2010; Schwartz and Mare 2005).

Besides the impact of partnering on individual well-being, assortative mating has been of interest for research on social stratification because it potentially impacts the distribution of resources across households and shapes boundaries between social groups (Kremer 1997; Schwartz 2010, 2013). In this article, we study partner selection based on parental wealth, a characteristic that is of particular interest for social stratification research for several reasons. First, a substantial amount of own wealth is the result of inheritances. These transfers can be observable in the wealth of individuals if parents have deceased, but they are generally a latent expectation of future transfers that are not measurable at the moment of couple formation given that most parents are still alive. Kopczuk and Lupton’s (2007) review of the literature estimated bequests to account for approximately 35% to 45% of the overall wealth of an individual in the United States. Therefore, high levels of parental wealth homogamy may contribute to wealth inequality between households. Second, wealth homogamy can shed light on important questions about intergenerational mobility processes. The extent to which families reproduce their accumulated wealth across generations through dynastic wealth is bound to depend on partnering choices.

To date, few studies have examined the extent to which partners match on parental wealth. To the best of our knowledge, the current literature is limited to a study of parental wealth homogamy using data from 1988 for the United States (Charles et al. 2013) and an article on the concentration of inheritances within couples in France during the 1990s and 2000s (Fremeaux 2014). Both studies indicated that people tend to select partners similar to themselves in terms of parental wealth. Using the 1988 wave of the Panel Study of Income Dynamics (PSID), Charles et al. (2013) estimated the correlation between parents’ (positive) wealth to be about .4 after controlling for age and race.

In this study, we contribute to this emerging literature by studying parental wealth homogamy in Denmark. We use registry data for marriage and union cohorts formed between 1986 and 2013. A major contribution of our work is that we are, to our knowledge, the first to study trends in parental wealth homogamy over time. Earlier research is limited to a finding by Fremeaux (2014) showing that sorting on inheritances remained stable from 1992 to 2010 in France.

Besides presenting trends in parental wealth homogamy, a second focus of our study is on different ways of empirically estimating and interpreting trends in parental wealth homogamy. Studying parental wealth homogamy is fraught with conceptual and methodological challenges, including the measurement of parental wealth, changes in the composition of wealth across time, parental partnering dynamics, and selective mortality.

Compared with earlier research, we believe that our study offers improvements to dealing with these challenges. First, we study cohorts in the year of union formation instead of looking at a cross-section of unions with varying union durations. Second, we use intergenerationally linked registry data for the entire Danish population with precise measurement of parental wealth. Earlier studies used data on inheritances (Fremeaux 2014) or survey data based on respondents’ recollected estimates of their own and spouses’ living parents’ wealth (Charles et al. 2013). Third, we are able to (partly) recover information on parental wealth for individuals whose parents passed away before union formation. Fourth, our data measure parental wealth at the individual rather than the household level, allowing for a more straightforward inclusion of remarried parents. Finally, the longitudinal data structure allows us to verify the sensitivity of estimates to the time at which parental wealth is measured.

Given the methodological challenges in establishing parental wealth correlations, the scope of this article is limited to documenting trends in the overall correlation of partners’ parental wealth. We leave questions about mechanisms underlying correlations in parental wealth, such as homogamy based on other characteristics (e.g., own education and occupation) for future research. Before discussing the empirical challenges of estimating parental wealth correlations, we provide a brief theoretical discussion as to why partners might select each other based on parental wealth and why the importance of such mechanisms might have changed over time.

Parental Wealth Homogamy: Mechanisms

According to Kalmijn (1998), partnering homogamy is influenced by (1) preferences of individuals for partners with certain characteristics, (2) the interference of third parties in the selection process, and (3) constraints on the chances of meeting people due to structural factors. There are good reasons to expect that people prefer partners with high parental wealth, which can have a direct positive influence on the attractiveness of potential partners because wealth is likely to be transferred to children in the future (Boserup et al. 2018; Killewald et al. 2017; Schneider 2011; Spilerman 2000). Parental wealth can also affect attractiveness through indirect routes. It allows parents to invest in their children’s human capital and facilitates access to better health and education (Eads and Tach 2016; Killewald et al. 2017; Pfeffer 2011, 2018; Pfeffer and Schoeni 2016; Rauscher 2016; Thompson and Conley 2016).

Parents are also the most obvious third party with an interest in the partnering choices of their children (Kalmijn 1998; Rosenfeld and Kim 2005). They might have direct preferences for seeing their children partner into a wealthy family, which would imply that their child could potentially access wealth. They might also have indirect reasons for wanting their children to partner into a wealthy family: parents’ class and lifestyle preferences might extend to their child’s partner, and hence parents prefer someone who formed habits with similar access to economic resources.

The third factor influencing homogamy, according to Kalmijn (1998), is the opportunity to meet individuals with similar characteristics. Even without explicit preferences for parental wealth and its related characteristics, homogamy might simply arise because individuals born into wealthier or poorer families are more likely to be in contact with one another. This becomes clear after thinking about the influence that parental wealth can exert on residential, educational, and occupational segregation; lifestyle habits; and social networks. That there is residential segregation due to parental wealth during childhood and potentially young adulthood is obvious. But even when offspring leave the parental home, the family’s wealth and access to resources can enable them to rent or buy residences in different areas than individuals growing up in a less economically advantaged family environment (Charles and Hurst 2002). Further, family wealth influences the likelihood of attending schools and universities and thus moving in social networks acquired through attending these educational institutions (Blossfeld 2009).

Changes Over Time

Theories about modernization generally hypothesize that homogamy based on ascribed characteristics (such as parental wealth) declines over time, whereas acquired characteristics gain in importance (Kalmijn 1991). Educational expansion, longer educational careers, and higher geographical mobility are expected to have increased the importance of own socioeconomic standing, social networks, lifestyles, and preferences relative to parental characteristics (Blossfeld 2009; Rosenfeld and Kim 2005; Schwartz 2013). Declining levels of homogamy have been observed for ascribed characteristics, such as parental occupation (Henz and Mills 2018; Kalmijn 1991; Rosenfeld 2008). One might expect this pattern to extend to parental wealth homogamy, too.

A reason why parental wealth might, on the other hand, have become more important in partner search is that wealth inequality has increased considerably in many Western countries (Piketty 2014). This higher inequality might have made the benefits stemming from wealth stronger and more salient. Studies have found some support for increased homogamy (Monaghan 2015; Torche 2010) and longer partner searches (Gould and Paserman 2003) in contexts of high income inequality. Furthermore, increased wealth inequality can lead to more pronounced differences in tastes and cultural practices and can augment residential segregation, thus reducing opportunities of individuals from different family backgrounds to meet (Smith et al. 2014).

When to Measure Parental Wealth? A Methodological and Conceptual Challenge

So far, our discussion, as well as the existing research on parental wealth homogamy (Charles et al. 2013; Fremeaux 2014), has treated parental wealth as a stable characteristic of individuals. In reality, though, parental wealth changes over time, which poses conceptual as well as methodological challenges on when and how to best measure parental wealth. Even though the wealth of a family at a given point in time is highly predictive of wealth at a later moment, wealth depends on time-varying processes, such as housing prices, stock market fluctuations, individual earnings, and consumption patterns as well as windfalls or unlucky events. A family’s position in the wealth distribution thus depends on the time of measurement, which raises the question of when the wealth of parents should be measured. The answer depends on the mechanisms that one expects to be most relevant for partner selection. We propose three theoretical possibilities that will be translated into specific measures in the empirical section.

If one considers parental wealth as a socialization factor that shapes individuals’ preferences and lifestyles, and therewith structures interpersonal networks and opportunities to meet potential partners in life, parents’ wealth position during childhood and adolescence might be the best indicator to employ. In contrast, if one expects parental wealth to matter for partner selection primarily because it is an economic resource that children signal directly to future partners, the wealth parents have at the time of union formation might be the best indicator of transfers and inheritances a couple can expect to receive in the future. A problem with using parental wealth at the time of union formation as an indicator of future financial help and transfers a person might receive is that wealth is highly dependent on age. Individuals tend to accumulate wealth throughout adulthood with a peak around age 60, after which levels of wealth start declining (Killewald et al. 2017). Therefore, an individual with young parents might have low parental wealth at union formation, but this might be a poor predictor of parents’ future wealth and hence the volume of expected transfers and inheritances. In that case, a measure that indicates parents’ wealth relative to their peers of the same age might be the most relevant measure to employ. In our empirical analysis, we employ measures corresponding to each of these three categories to examine the relevance of measurement timing.

Our Study: Parental Wealth Homogamy in Denmark

In this article, we study trends in parental wealth homogamy in Denmark from 1987 to 2013. Not all the aforementioned mechanisms may apply to Denmark to the same extent. On the one hand, even though income inequality is relatively low in Denmark, wealth inequality is surprisingly high in comparison with other Western countries (Balestra and Tonkin 2018). Wealth inequality has been fairly stable in Denmark over the last decades, except for slightly increasing wealth shares among the top 1% (Jakobsen et al. 2018). On the other hand, with a correlation in wealth across generations of around .4, the intergenerational transmission of wealth in Denmark is low compared with the United States (Boserup et al. 2013), which could reduce the preference for partners with high parental wealth. Furthermore, even though the greatest expansion of tertiary education in Denmark took place before the 1980s, rates of tertiary education attendance rose steadily between 1980 and 2010 (Barro and Lee 2015). Educational expansion might have increased the possibilities of partnering across parental wealth boundaries as tertiary education became less restricted to a select group of individuals. Previous research on Denmark suggested that educational homogamy declined to some extent (Breen and Andersen 2012), with roughly one-half of the sorting on education being due to partners attending educational institutions nearby (Nielsen and Svarer 2009).

Data and Method

Our analysis is based on the Danish register data, which are available for researchers in anonymized form through Statistics Denmark. These comprehensive data on the complete population residing in Denmark during the years 1986–2013 come from several public administration registers, which are linked by Statistics Denmark through unique personal identification numbers provided to all individuals at birth. These unique longitudinal data are accessible to researchers in anonymized form through Statistics Denmark’s secure servers. Information from the population registers allows us to link parents to children.

Our sample includes all different-sex coresiding unions formed during the period 1987–2013. Union formation is determined based on two individuals entering into coresidence, thereby capturing couples who were married, had a registered partnership, cohabited with children, or cohabited without children (Drefahl 2012).1 A requirement for inclusion in our sample is the presence of parental identification numbers of the father and the mother of both partners, allowing us to link parents to children in the registry data. Such parental identification numbers have been systematically recorded for all individuals born after 1960 but are incomplete for earlier birth cohorts (Boserup et al. 2013).2 Therefore, we restrict our sample to couples in which both partners are aged 18–34 at the time of union formation. In robustness checks, we expand this age range to 40 but restrict the period covered by our analysis to 1992–2013.3 Finally, we exclude couples in which one of the parents was not present in the registry data after 1980 (the first year we have information on wealth). Because parents are not present in the registry data if they have passed away or live abroad, our analysis excludes a large part of foreign-born individuals who moved to Denmark without their parents; later, we discuss how this restriction might impact our results.

Parental Wealth

Tax registries in Denmark collect data on the value of individuals’ assets and liabilities, mostly provided by third parties (e.g., assessments of housing values are made by the tax authorities). Denmark taxed wealth until 1996, but the collection of wealth data continued with some slight modifications after its abolishment (Jakobsen et al. 2018). Following Boserup et al. (2013), we define net wealth as total assets (financial assets and housing) minus debts as retrieved by Statistics Denmark from data collected by the Danish Tax Agency. Wealth comes from a large variety of sources, including the value of properties, such as houses, boats, and cars; bonds; stocks; cash in banks; the value of businesses; loans; and mortgages. One component not included in the measurement of wealth is accumulated pension wealth. Most information is provided by third parties, such as banks, financial institutions, and other governmental bodies. The value of properties is assessed by tax authorities based on detailed information on their characteristics (Boserup et al. 2013).4 During the observation period, there are changes in how some sources of wealth are reported, mainly because of the removal of the wealth tax in 1996. Specifically, the value of stocks was self-reported until 1996 but provided by financial institutions ever since, some assets that were self-reported until 1996 were not recorded anymore after that (including cars, boats, and caravans), and the registration of company values changed several times until 1997 (Jakobsen et al. 2018). Boserup et al. (2013) exploited an overlap in both ways of measuring wealth to show how the measurement of wealth from 1997 onward was well approximated by the measurement of wealth up to that point.

Wealth is measured at the individual level. Therefore, we sum the wealth of parents regardless of parents’ marital status. Parental wealth is measured separately for male and female partners. Following earlier research (Solon 2004), we average parental wealth across three years.5 We present our main analysis using three measures that vary in the time at which parental wealth is measured.

Parental wealth in the year of union formation is the primary measure used in our analysis. To construct the measure pw1i capturing the parental wealth of individual i in the year of union formation y = u, let Ry = u, sex(i) be an operator assigning the percentile rank based on the distribution of parental wealth of all individuals that formed a union in the same year y = u and that are of the same sex(i) as individual i. Assigning the rank as a function of gender means that we separately look at the parental wealth distribution of all daughters and of all sons that formed a union in year y.6 Parental wealth wp = wf + wm is calculated as being the sum of the wealth of fathers wf and mothers wm.7
pw1i=Ry=u,sexiwp,i,y=u.
(1)

In robustness checks, we log-transform the total sum of parental wealth in the year of union formation instead of using a rank-based measure.

The second measure we employ indicates parental wealth in the year of union formation normalized by father’s age. In this case, before calculating the rank of parental wealth within a given union cohort, parental wealth is normalized separately by the father’s age. Because this measure reflects the wealth of parents relative to peers from their specific birth cohorts, it also accounts, to some extent, for the distribution of children’s age at union formation given that older individuals are likely to have older parents, on average. Normalization is done by subtracting the average μ and calculating the standard deviation (sd) of the wealth of all parents, where the father has the same age as the father of individual i age(f) = age(fi) and where union formation took place in year u.
pw2i=Ry=u,sexiwp,iμagef=agefiwpsdagef=agefiwp.
(2)
A third and final measure employed is parental wealth at age 18. This measure is based on the level of parental wealth in the year when respondents were aged 18, which is denoted as wp, y = (y| age = 18). We subsequently normalize individuals’ wealth by subtracting the average of parental wealth at age 18 and dividing by the standard deviation. The sample from which we calculate the mean and standard deviation consists of all individuals who are of the same age age = age(i) and sex as i and also formed a union in year u.
pw3i=Ry=u,sexiwp,i,y=yagei=18μage=agei,wp,y=yage=18sdage=ageiwp,y=yage=18.
(3)

Because of the stricter data requirements, the sample used for this measure is smaller than the samples obtained for the two other wealth measures. In additional analyses, we reproduce the three parental wealth measures based on the total value of owned assets only (i.e., without subtracting debt). Further discussion of the implications of changing the time of measurement for conclusions can be found in the section F of the online appendix.

Besides choosing the point in time at which we measure parental wealth, two other measurement complications are important. First, parents might have passed away before wealth is measured. Fremeaux (2014) addressed this issue in his study on inheritance homogamy by combining information on inheritances received with estimates of expected inheritances. Charles et al. (2013) did not have information on the wealth of parents who passed away. Our solution is to measure parental wealth in the last wave before union formation where both parents were still alive.8 In robustness checks, we exclude cases in which a parent passed away before union formation. Our measure of parental wealth at age 18 excludes cases in which parents had passed away before age 18.

Second, parents might be separated at the time of their children’s union formation. If parents repartner, household-based measures of wealth might complicate arriving at a comparable measure of parental wealth for individuals whose parents formed new families compared with those who did not. Charles et al. (2013) therefore excluded individuals with remarried parents. Danish registry data allow for the measurement of wealth at the individual level, enabling us to sum parents’ individual wealth and to disregard the wealth of eventual new partners. In robustness checks, couples with one or more remarried parents are excluded from the analysis.

Sample Description

Table 1 provides descriptive statistics of the overall sample of 803,185 couples with full information on parental wealth in the year of union formation. Besides descriptive statistics for the sample overall, averages are presented for unions formed in 1987 and 2013 to monitor changes over time in the composition of the sample of unions. The descriptive statistics show that men are on average older than women at union formation, and the same applies to their parents. Ages of all individuals involved have slightly increased during the observation period. We treat married and cohabiting couples as one group because cohabitation as an alternative to marriage is widespread in Denmark: in our sample, only 6% of unions started as a marriage.9 Parental wealth is higher for the parents of men than for those of women. One-quarter (25%) of men’s parents report negative wealth, and this share increased from 18% in 1987 to 35% in 2013. Because of the precise measurement of wealth, very few couples had zero wealth (less than 0.2% of cases). In comparison, estimates from the Survey of Consumer Finances indicate that approximately one in five households in the United States had zero or negative wealth in 2016 (Wolff 2017). Negative wealth can arise as the result of recent investments made and accumulated debts. However, a likely source for higher levels of negative wealth in our data is the potential mismatch between the value of houses as estimated by the authorities and the real market value of a property.10 We pay particular attention to cases with negative parental wealth in the analysis and exclude them in robustness checks (online appendix, section G).

Figure 1 breaks down the wealth of the male partners’ parents into housing assets, financial assets, and debt. Housing assets make up most of the wealth across the distribution, even though financial assets become more visible at the top of the wealth distribution.11 Fig. 1 also shows high levels of debt and assets at the very bottom of the distribution. Therefore, very low levels of wealth might indicate recent investments made rather than an economically difficult situation (Killewald 2013).

Figure 2 shows trends in median and mean absolute deflated wealth over time. Median and mean wealth declined very slightly until the mid-1990s, took off dramatically thereafter before decreasing considerably after the onset of the financial crisis. Figure 3 documents how inequality measured by the Gini coefficient in parental wealth followed a reverse pattern, with increasing inequality until the early 1990s, a brief decline, stabilization, and then a subsequent increase in recent years. On average, the Gini coefficient in wealth over the period observed is roughly .7, which is in accordance with other studies of wealth inequality (Balestra and Tonkin 2018; Danish Economic Councils 2016).

Procedure

Because the main aim of this article is descriptive, we concentrate mainly on presenting and interpreting trends in parental homogamy in detail.

We commence the analysis by giving an indication of the likelihood of partnering based on parental wealth. Then we describe how individuals who do form a union select each other based on parental wealth. We first document the relative frequency of couple combinations based on men’s and women’s parental wealth percentiles using a heatmap. In a second step, we show average male partner’s parental wealth according to the female partner’s parental wealth, which provides insights into whether there are nonlinearities in how wealth rank affects partnering behavior. Following this detailed descriptive effort, we summarize the overall strength of assortative mating using yearly correlations in partners’ parental wealth to show how wealth homogamy changed over time. Finally, we test the robustness of these trends by using different measures and sample restrictions.

Results

We start by describing how the probability of forming a new partnership is influenced by parental wealth. The gray line of Fig. 4 represents the probability that an individual aged 18–34 forms a new union in a given year depending on the wealth percentile of the parents, and the black line shows the same measure but for the first partnership observed only.12 We can conclude that individuals from wealthier backgrounds are somewhat more likely to ever enter into a union but at the same time slightly less likely to form a new partnership at any point in time. This suggests that repartnering is more common among individuals with lower parental wealth, but overall differences in first partnering and overall partnering by family background are very small.

Figure 5 is a heatmap showing how frequently men and women with given levels of parental wealth form unions. The graph depicts the joint distribution of parental wealth by percentiles, showing wealth percentiles of men’s parents on the x-axis and those of their female partners on the y-axis. If people married independently of parental wealth, one would expect partnering to be relatively homogeneously distributed across parental wealth percentiles. Men and women in each percentile should form couples with approximately 1% of the members of each parental wealth percentile of the opposite sex.

The graph displays the empirical joint partnering distribution by showing the estimated proportions of couples found in each of the 100 × 100 cells. A value of 1 in Fig. 5 indicates an observed frequency that would be expected if partnering were to be at random, and a value of 2 indicates a relative frequency that is twice greater than expected. Dark areas indicate relatively common combinations (up to 2.5 times the probability of the random match), whereas lighter areas are relatively less common (less than the probability of the random match).

We observe high relative frequencies along the diagonal, indicating positive assortative mating, and a concentration of couples in the top-right corner, corresponding to couples in which both his and her parents are among the wealthiest of their union cohorts. At the same time, the lighter areas in the top-left and bottom-right corners reveal that individuals from the wealthiest families are relatively unlikely to partner with individuals from families in the bottom 30% of the wealth distributions. In sum, individuals from the wealthiest families are the most likely to form homogenous partnerships, and they avoid partnering with individuals from families with low levels of wealth.

Figure E1 in the online appendix shows yearly versions of the heatmap displayed in Fig. 5. These figures illustrate that the wealthy tend to increasingly partner among each other and avoid individuals from families with little wealth over time.13 These trends would suggest an increase in parental wealth homogamy during our observation period. A peculiarity in Fig. 5 and Fig. E1 consists of the relatively dark areas observed along the x- and y-axes, which indicate the likelihood of partnering with an individual from the very bottom of the parental wealth distribution. These individuals have parents with (large amounts of) negative wealth, an issue we address later.

Figure 6 further illustrates the joint parental wealth distribution of partners’ parental wealth and its evolution over time. It shows the average parental wealth percentile of male partners according to female partners’ parental wealth percentile for three groups of union cohorts. In general, the more parental wealth female partners have, the higher the parental wealth of their partner. The tendency of partners’ parental wealth to increase with their own parental wealth is stronger for more recent union cohorts, again indicating a rise in homogamy over time. The largest differences in average parental wealth observed amount to a difference of 12 percentiles in the average parental wealth rank of male partners.

An exception to the generally positive association is observed for women with very low parental wealth whose partners’ average parental wealth is not as low as one might expect. This could be because debt can indicate access to credit rather than a severely disadvantaged economic situation (Killewald 2013). Given that a large portion of debt is mortgage debt or other debt requiring collateral, these parents may have invested in a business, bought a new house, or experienced a decline in their house value because of recession or house price development. As previously mentioned, negative wealth might also reflect that housing values in the data sometimes underestimate actual market values. To understand this issue better, we exclude debt from the analysis for the right panel of Fig. 6. Recalculating parental wealth percentiles based only on assets makes the nonlinear relationship between partners’ parental wealth disappear14 and shows generally stronger levels of homogamy than our measure based on parental wealth (i.e., assets minus debts).

Correlation in Ranks

Figure 7 provides our main result: trends in the correlation between partners’ parental wealth by yearly union cohort. The right panel of the figure reproduces the same correlations based on assets only. Correlations for all three parental wealth measures considered are relatively small across the period and range between .04 and .19. Correlations in parental assets are slightly higher and range between .10 and .23 over the period.

Correlations are highest for parental wealth measured at union formation and ranked by union cohort only. After parental wealth rank is calculated by union cohort after normalizing by father’s age, correlations are systematically lower. Similarly, we observe that correlations of parental wealth at age 18 are mostly lower than those of our main measure of parental wealth at union formation. The divergence in correlations between measures could indicate that parental wealth available at the time of union formation is more relevant for partnering behavior than expected future wealth of parents (and related financial help and transfers) or the wealth that parents own during childhood and adolescence. An alternative explanation is that accounting for parental age partly controls for age homogamy among partners (which arguably also applies, to some extent, to the measure of parental wealth at age 18). Young parents, on average, have less wealth than older parents, and if partners select each other based on own age, a certain level of parental age homogamy will arise as a consequence.15 In later analysis, we observe that correlations indeed drop a bit after controlling for the ages of partners, but the possibility that parental wealth at the time of union formation is the most relevant for partner selection remains.

Trends over time in the parental wealth correlation are relatively consistent across the different measures used. Both measures of parental wealth at union formation show a slight decline in homogamy in the early 1990s, with the lowest correlations observed between .04 and .08. This is followed by steady increases observed for all three measures thereafter, and correlations peak at around .15–.19, depending on the measure considered. For parental wealth at union formation in both its forms, the correlation declines after the financial crisis of the late 2000s, even though it keeps increasing for parental wealth measured at age 18. One interpretation of this result is that wealth during childhood has become increasingly important over time relative to parental wealth at the time of union formation. However, correlations in parental assets keep increasing after the financial crisis for all three measures alike. This raises the question of whether periodical changes in the composition of wealth, such as the share of parents with negative wealth, are driving this divergence in results across measures. We scrutinize this issue further in the next section.

Changing Partner Selection or Changing Distribution of Wealth?

Are trends in parental wealth homogamy driven by changes in partnering behavior or by periodic changes in the composition and distribution of wealth? Compositional changes can affect the wealth correlation even if partnering behavior does not change. Changes in the prices of specific assets might change the position of parents that hold these assets in the wealth distribution. Because this could affect the parental wealth correlation, the parental wealth correlation can change without any changes in partnering behavior taking place—as, for example, in the cases of house price booms in certain areas or stock price developments.

We test for this possibility through additional analysis reported in detail in section F of the online appendix. In these checks, we investigate whether time trends in the parental wealth correlation change when parental wealth is measured five years before union formation instead of one year before union formation. If our results are driven by changes in actual partnering behavior, the time of measurement should matter relatively little for trends in parental wealth correlations over time. Conversely, if changes in the distribution of wealth drive changes in parental wealth homogamy, measuring wealth five years before union formation should result in a parental wealth correlation similar to the correlation observed for parental wealth at union formation of couples formed five years before.

As shown in Fig. F1 in the online appendix, the importance of time of measurement varies depending on the observation period and measure chosen (net wealth or assets only). Even though the homogamy trend is very similar when parental wealth is lagged by five years, we observe that the trend is postponed by several years during most of the observation period, indicating that changes in parental wealth homogamy are not necessarily driven by changes in partner selection. Instead, periodic changes in the distribution of wealth across society probably drive part of the trends in parental wealth correlations, especially for increases in parental wealth homogamy observed during the 2000s.

Substantively, these findings suggest that changes in the distribution of wealth over time appear to benefit or penalize the parents of both partners in similar ways. In other words, if the parental wealth rank of a certain individual rose in the wealth distribution during the 2000s, the parents of this individual’s partner also likely increased their wealth rank during the 2000s. Societal gains and losses in wealth appear concentrated within given social circles. Therefore, part of the correlation between partners’ parental wealth changes in tandem with the changing distribution of wealth in society at large.

Robustness Checks and Comparison With Charles and Colleagues’ Estimates

The main results documented so far lead to two substantive conclusions: (1) estimates of parental wealth homogamy appear much lower in Denmark compared with earlier estimates for the United States (e.g., a correlation of .4 found by Charles et al. 2013), but (2) parental wealth homogamy has become stronger over time. We perform five robustness checks that simultaneously make our results more comparable with those of Charles and coauthors’ (2013) estimates for the United States (see the online appendix, section G).

First, we exclude cases in which a parent passed away before union formation (but for whom we had recovered information on parental wealth from earlier waves); this does not change the results.

Second, we exclude cases with negative parental wealth, which leads to a drop in the correlation for recent periods. In addition, trends over time become less pronounced. Individuals from wealthy families avoid partnering with individuals with the lowest levels of family wealth (i.e., those with negative wealth; see Fig. 1), and this tendency has been increasing over time, driving up the correlation in partners’ parental wealth. Therefore, excluding negative wealth flattens the trend in parental wealth homogamy over time. This also excludes the relatively high levels of negative wealth observed in Denmark as an explanation for the lower parental wealth correlations observed in our study compared with those observed for other contexts.

Third, instead of normalizing and calculating the rank of parental wealth at union formation, we log transform three-year average wealth at union formation. Results are consistent, but the drop observed during the crisis years becomes less pronounced.

Fourth, we exclude cases with remarried parents, which leads to slightly stronger increases in parental wealth correlations over time.

Fifth, we switch from correlations to regressions. Estimates do not change after we exclude control variables. However, including age controls (father’s age, mother’s age, her age, his age) reduces correlations across the period studied in ways that are similar to ranking parental wealth at union formation by father’s age (Fig. 7).

Applying all these changes simultaneously leads to a set of estimates that are the most comparable to those of Charles et al. (2013). These estimates show a robust picture of relatively low but increasing parental wealth homogamy over time in Denmark. Compared with the estimate of .4 for the United States (Charles et al. 2013), the parental wealth correlation in Denmark is low across specifications. However, we are not able to gauge the possible influence of different data sources (survey data instead of registry data) and differences in sample selection (union cohorts vs. a cross-section of unions intact at a given point in time).

In a final additional analysis, we investigated the possible consequences of having excluded (most) foreign-born individuals from our analysis (given that information on parental wealth is mostly not available for them). Fig. H1 (online appendix) shows how both couples consisting of two foreign-born persons and couples consisting of one foreign-born and one Denmark-born individual have increased (from less than 1% to 4%, and 4% to 8%, respectively). If we were to assume that foreign-born individuals are relatively similar in terms of parental wealth, their inclusion in the analysis would probably slightly increase parental wealth correlations and reinforce the upward trend observed over time. However, mixed couples (one Denmark-born and one foreign-born person) are likely to be relatively dissimilar in terms of their parental wealth. Their inclusion might therefore slightly decrease parental wealth correlations and attenuate time trends observed, thus leaving the overall impact of excluding foreign-born individuals on our results unclear.

Last, Fig. H2 (online appendix) shows that the parental wealth rank of Denmark-born individuals forming unions with foreign-born individuals varied, without a clear trend, between the 52nd and the 54th percentile across the observation period. There are therefore no clear changes over time in who partners a foreign-born person based on parental wealth.

Discussion

Who partners with whom has long been a central question of the social sciences. Over the last decades, quantitative studies repeatedly showed that partners match based on a variety of ascribed and acquired characteristics (Becker 1973, 1991; Blossfeld 2009; Browning et al. 2014; Kalmijn 1998; Lam 1988; Schwartz 2013; Weiss and Willis 1997). So far, surprisingly little attention has been paid to assortative mating based on parental wealth. Previous research on survey data from the United States estimated that parental wealth homogamy is quite strong (Charles et al. 2013). High levels of parental wealth homogamy, which are likely to be consequential for wealth inequality between households and the transmission of family wealth across generations, might be an indication of family wealth shaping boundaries between social groups. All these reasons illustrate the importance of studying whether previous findings of strong parental wealth homogamy hold when applied to a different setting and when more accurate data are used.

In this article, we show that the correlation in partners’ parental wealth in Denmark is relatively weak. Correlations range between .04 and .19, depending on the measure employed and the time period considered. This result contrasts with the .4 correlation found by Charles et al. (2013) for the United States. In general, it is perhaps unsurprising that parental wealth homogamy is lower in Denmark than in the United States, given the relatively high levels of intergenerational wealth mobility in Denmark; indeed, low parental wealth homogamy might be a possible mechanism increasing mobility. However, the difference in the estimates between both countries is much larger than the difference found in cross-national comparisons of intergenerational wealth mobility (Boserup et al. 2013:17).

Another possibility is that the large difference in correlations between Denmark and the United States reflects different research designs. We specifically aimed to make our estimates comparable with those of Charles et al. (2013), which actually led to even lower estimates of parental wealth homogamy. However, remaining differences include the use of registry data instead of survey data and the study of unions in the year of formation rather than a cross-sectional selection of unions intact at a given point in time. More research is needed to understand whether the different types of data and empirical strategies employed affect results. Nevertheless, the takeaway from our analysis remains that parental wealth homogamy in Denmark appears considerably lower than in the United States.

However, even if levels of parental wealth homogamy are relatively low, this does not mean that assortative mating based on parental wealth is of little concern. First, we find parental wealth homogamy to be particularly strong among partners from the wealthiest families. Approximately one-half of total household wealth is owned by the top 10% wealthiest households, and roughly one-fifth of total household wealth is owned by the top 1% of households (Jakobsen et al. 2018). A concentration of parental wealth homogamy at the top can be consequential for intergenerational wealth inequality, even if parental wealth homogamy is relatively low for the parental wealth distribution overall. Future research should further explore how consequential patterns of assortative mating based on parental wealth are for the distribution and transmission of wealth across households.

Second, even though levels of parental wealth homogamy were relatively low in the early 1990s in Denmark, our results indicate a modest but steady increase in homogamy during the late 1990s and the 2000s. Our preferred estimates suggest such an increase and show a strengthening of homogamy tendencies among the very wealthy combined with a decreasing likelihood of these individuals from very wealthy families to partner with those from families with low wealth. These developments might lead to increasing social distances between the very wealthy (e.g., the “1 %”) and those with little wealth in society.

A main question for future research is why parental wealth homogamy is increasing over time in Denmark. Our analysis provides some starting points for future research on the mechanisms at play. Additional analysis suggested that the increases in homogamy observed for the 2000s are not necessarily driven by changes in partner selection. Instead, periodic changes in the distribution of wealth appear to benefit or penalize certain groups in society in ways such that if the parental wealth rank of a given individual rises, the parents of that same individual’s partner are likely to rise in the wealth ranking too. An example of such a process would be geographically selective increases in housing prices. For instance, if housing values surged in Copenhagen during the 2000s, but less so in other parts of Denmark, individuals with parents who live in Copenhagen (or with parents who have real estate there) will have experienced increases in their parental wealth rank over time. If there is a certain level of partnering homogamy based on parents’ place of residence, such selective surges in housing prices will drive up parental wealth homogamy, even if partnering behavior does not change.

Therefore, the increases in parental wealth homogamy in Denmark might be an indication of selective changes in the distribution of wealth in society rather than changes in partnering behavior. This does not make the increases in parental wealth homogamy less concerning from an inequality perspective. Even though partnering behavior might have remained relatively stable over time, existing homogamy on other unobserved characteristics seems to lead to an increased concentration of parental wealth within couples under the current development of the wealth distribution. In other words, partnering has become more consequential for the distribution of parental wealth across couples over time, with consequences for the intergenerational transmission of wealth and its concentration in society. Our recommendation for future research is to investigate whether and which selective periodic changes in wealth are driving parental wealth homogamy and to quantify the consequences of parental wealth homogamy for wealth inequality and its transmission more generally.

Another hint pointing toward the underlying mechanisms comes from the observation that homogamy based on parental assets has been increasing steadily over time, whereas homogamy in parental net wealth (including liabilities) fluctuates more. In addition, homogamy based purely on assets is consistently stronger (see Fig. 7, shown earlier). This finding suggests that assets may be a better indicator of the social circles and groups that individuals belong to and interact with than net wealth. For example, perhaps owning a home in a certain neighborhood conditions social circles. Whether a home is mortgaged or owned outright might matter relatively less for partnering, conditional on living in that area. In other words, partner homogamy in parental wealth might be ascribed more to how parental assets structure the opportunities to meet certain partners than to the explicit preferences for individuals with wealthy parents (Kalmijn 1998). This opens up interesting questions for further research on indicators of social stratification.

To sum our results, this study shows that parental wealth homogamy in Denmark is lower than previous research on the United States has shown it to be, but disproportionately strong at the top of the parental wealth distribution, which might be particularly consequential for wealth inequality across households and intergenerational transmission of wealth. Furthermore, we provide indications that parental wealth homogamy has been increasing over time. We thereby shed light on how one of the major processes generating wealth inequality between households has been evolving. Finally, we think that important insights are to be gained from a continued study of homogamy in parental wealth as wealth inequality continues to rise in many places and as we try to understand how social boundaries between groups co-evolve with inequality trends.

Acknowledgments

Sander Wagner was supported in this research by a grant of the French National Research Agency (ANR), Investissements d’Avenir (Labex ECODEC-ANR-11-LABX-0047). Mette Gørtz appreciates generous funding from the Danish National Research Foundation through its grant (DNRF-134) to CEBI, Center for Economic Behavior and Inequality. Diederik Boertien acknowledges research funding from the Beatriu de Pinos program of the Generalitat de Catalunya (2016-BP-00121) as well as the EQUALIZE project led by Iñaki Permanyer (ERC-2014-STG grant agreement No. 637768). We also appreciate input from seminar attendants at the Crest Sociology Lab and the Center for Demographic Studies. The usual disclaimer applies.

Authors’ Contributions

S.W. and D.B. developed the research idea; S.W. managed and analyzed data; and S.W., D.B., and M.G. wrote and edited the paper.

Data Availability

The data set used in this paper is based on several Danish administrative registers through social security numbers. These administrative microdata are located on specific computers at Statistics Denmark and may not be transferred to computers outside Statistics Denmark because of data security considerations. Researchers and their research assistants are allowed to use these data if their research project is approved by Statistics Denmark and if they are affiliated with a research institution accepted by Statistics Denmark. Currently, only researchers from research institutions in Denmark are allowed access to these data. Researchers at universities or other research institutions outside Denmark who wish to use these data may do so by visiting a Danish research institution or by cooperating with researchers working in Denmark. For researchers who want to analyze our data for replication purposes, we will provide guidance with regard to securing project approval at Statistics Denmark.

Compliance With Ethical Standards

Ethics and Consent

The authors report no ethical issues.

Conflict of Interest

The authors declare no conflict of interest.

Notes

1

The category cohabited without children includes only households of two unrelated adults who had an age difference of less than 15 years and who were not related by family ties. A small minority of cases might therefore not regard romantically involved individuals. In robustness checks, we exclude unions that lasted less than three years to filter out such possible arrangements as much as possible, and results are unchanged; see Fig. A1 in the online appendix.

2

Figure B1 in the online appendix shows the distribution of cases that had no parental identification numbers by age and year. In the online appendix, we also discuss various robustness checks that address concerns about whether a changing age composition of the sample affected results (e.g., including sample weights to compensate for possible unequal probabilities of inclusion by birth year).

3

The results are robust. See Fig. C1 in the online appendix.

4

Tax-assessed housing values have historically not always reflected fully the market values at the time. Following Boserup et al. (2013) and Browning et al. (2013), we adjust tax-assessed housing values with a factor that reflects the average relationship between market values of traded houses and average tax-assessed values, thus arriving at an imputed estimate of the market value of housing wealth.

5

All wealth and income components are deflated with a GDP deflator to the 2010 price level.

6

Robustness checks calculating percentiles based on the wealth rank of all parents with children aged 18–35 produce practically identical results; see section D of the online appendix. This wealth rank is also used for our description of partnering probabilities by parental wealth (see Fig. 4).

7

In reality, we calculate the percentiles on the distribution of year normalized wealth. Thus, instead of wpi, y = u, we calculate (wpi, y = u − μy = u(wp)) / sdy = u(wp), meaning that we substract the average of parental wealth in the year of union formation and divide by its standard deviation. This results in the same distribution except that it allows us to pull forward the wealth of deceased parents in a comparable way and integrate it into the wealth distribution of the year that their child formed a union.

8

In these cases, parental wealth is normalized in the year both parents were still alive, and this value is subsequently used in the calculation of the parental wealth rank for each annual union cohort.

9

In 2018, one in four Danish couples were cohabiting rather than married, and the same cohabitation rate applies to couples with children, according to own calculations based on data from Statistics Denmark (www.statistikbanken.dk).

10

Information on tax-assessed housing values should, in principle, reflect market values for comparable traded houses. However, given that the majority of houses are not traded each year, the tax authorities’ estimated market values of houses may be too low (high), which can happen because specific unobserved characteristics (e.g., interior design, such as a new kitchen or bathrooms) are not taken into account by valuation authorities. Thus, the higher actual market values can translate into higher mortgages compared with the value of the house as indicated by the taxable values available in the data.

11

With financial deregulation and various reforms through the 1990s and early 2000s, house owners’ access to, for example, refinancing their mortgage debt, implied on average an increase in debt in relation to housing values (Browning et al. 2013).

12

For part of the sample, we do not observe all partnerships because partners are recorded only from 1986 onward. Some of the first partnerships we observe in the data might therefore in fact be a second, third, or higher-order partner of an individual.

13

An animated version is available at https://media.giphy.com/media/64anFirdCTXZYWRirY/giphy.gif. Section E of the online appendix also provides estimates of changes over time in the chances of partnering. The relationship between parental wealth and forming a first partnership during the observation period is relatively stable across union cohorts. The chances of forming a new partnership in any given year slightly declined for individuals with wealthy parents compared with individuals with less parental wealth due to increases in repartnering over time.

14

Part of the nonlinearity persists for the unions formed before 1997, which likely reflects changes in how some business assets were recorded. Before 1997, business assets were reported net of debts, and our indicator of assets could therefore still take on negative values only before 1997.

15

Robustness checks including controls for all parents’ and partners’ ages lead to similar results; see section G of the online appendix.

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