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Working Paper #2007-02

The effects of sexual orientation and maritalstatus on how couples hold their money

Marieka M. Klawitter

The effects of sexual orientation and marital status on how couples hold their money

August 2007

Marieka Klawitter Evans School of Public Affairs University of Washington Box 353055 Seattle WA 98195-3055 marieka@u.washington.edu 206.616.1673 Abstract: Previous research has shown that intrahousehold bargaining power in different-sex couples affects household expenditures and how families hold their money. This paper examines the portfolio of bank accounts held by same-sex and different-sex couples and its relationship to bargaining power and individual and relationship characteristics. Data from the U.S. Survey of Consumer Finances suggest that married couples are much more likely to hold money jointly than are same-sex or unmarried different-sex couples, even after accounting for the effects of other characteristics. However, many couples of all types hold money in joint accounts and do so more often in longer term relationships and when rearing children. Proxies for bargaining power help predict whether money will be held in individual accounts for unmarried different-sex and same-sex couples, but not for married couples. These patterns could reflect greater matching of married couples on preferences or the effects of legal and social institutions that differ by marital status and sexual orientation.

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Introduction Couples grapple to negotiate many aspects of collective life, and decisions about holding and spending money are certainly no exception. In the last twenty years, research has suggested that intrahousehold bargaining power—the ability of individual family members to drive household decisions--affects how money is managed and used by families. Concurrently, a growing body of social science research has compared the formation and experiences of married couples with unmarried couples--including both different-sex and same-sex partners. This paper builds on these literatures by examining the effects of individual bargaining power on family money management and how it differs by marital status and sexual orientation. Differences between married and unmarried, different-sex and same-sex couples color debates about evolving state and federal laws governing marriage, divorce, taxes, inheritance, and parenting rights. Conceptions of family life for various types of couples have influenced the structure of public policies, and, in turn, these policies create different legal frameworks for family finances across marital status and sexual orientation. Beyond the influence of state institutions, how couples manage money reflects individual and family characteristics, the intrahousehold bargaining power of partners, social and cultural influences, and the levels of trust and interdependence within couples. The system for managing and holding money chosen by a couple may later affect who has access to money and how the money will be used. Intrahousehold bargaining models seek to explain family decision-making and money management, and their predictions are critically important to understanding the effects of public policies or changing labor markets on individual and household behavior and well-being. This paper uses data from the U.S. Survey of Consumer Finances on joint and individually held liquid assets to compare money management for married, unmarried different-sex, and same-sex couples. The results show that married couples are much more likely to hold money jointly than are other couples, even after accounting for the effects of individual and family characteristics. However, many couples of all types hold money in joint accounts, especially those in longer term relationships and those living with children. Proxies for bargaining power help predict whether money will be held individually for unmarried different-sex and same-sex couples, but not for married couples. I first review research on intrahousehold decision-making and on family money management. I describe the data, sample, and empirical strategy, and then turn to results.

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Literature Review Many microeconomists have moved away from theories that focus only on households as the unit of analysis to develop models that describe the influence of individual family members on household decision-making. These models highlight the role of differing preferences and bargaining power for partners on household decisions and the resulting distribution of well-being between adults or between adults and children within the family (see Lundberg and Pollak, 1996 for a review). Along similar lines, sociologists have used exchange models to explain intrahousehold negotiations about housework and about the use of money (Bittman et al, 2003). Economists have also used models of interconnected marriage and labor markets that suggest that those more valuable as potential partners to others will garner a larger share of resources within a relationship (via a “quasi-wage”) (Grossbard-Shechtman, 1993). Both exchange theory and bargaining models predict that household decisions will more closely reflect the preferences of family members who have more bargaining power. Bargaining power derives from a variety of sources, depending on the type of model, but all the models predict that partners with better opportunities for work or income outside the current relationship will have greater power within the relationship. This suggests that potential earnings and income as well as potential home productivity (via a new relationship) should increase a partner’s ability to drive household choices (Pollak, 2005). Laws, government transfers, and social customs could also affect bargaining power by changing post-relationship opportunities for one or both partners. Similarly, models of marriage markets for spousal labor predict that the division of household labor and resources will be responsive to the quality of partners’ other options in marriage, remarriage, and labor markets. There is a growing body of empirical work designed to test the implications generated by these models, primarily whether differences or changes in factors related to individual bargaining power or marriage market options will lead to greater influence on household expenditures or activities. Nearly all the studies use data for married couples, though a few also include unmarried different-sex couples who are cohabitating. Gender differences in power and its use have usually been the focus of these studies. The two critical aspects of these empirical tests are the choice of proxies for bargaining power and the type of household decisions examined as outcomes subject to bargaining. In order to apply similar empirical tests of the effects of bargaining power to same-sex couples, one must use individual measures of power and individual outcomes rather than those that rely on gender differences in transfer income or preferences for family outcomes.1

1 Some studies have used extra-family gender-specific changes in government income for women or men (Bradbury, 2004; Lundberg et al, 1997), sex ratios, or changes in divorce or welfare laws that favor men or women as measures of power. Family or child outcomes such as

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For example, some studies assess the effects of an individual’s potential wage as a proxy for bargaining power on partner-specific outcomes such as individual time devoted to housework (Bittman et al, 2003). Individual outcomes should be systematically better for partners with more power, even if the distributions of the power measures are identical by gender (or for the head of household and the partner of head in the case of same-sex couples).2 Household Money Management Traditional theoretical economic models of families suggest that the original source of money and the holding of money should not affect household expenditures. However, if bargaining power affects household expenditures, then this relationship could also be evident in how money is held within the family. And, legal restrictions on accounts, transactions costs, and asymmetric information could mean that the how money is held could itself affect control of the money. Here, I look at family liquid assets, primarily bank accounts, to explore money management and its relationship to power. A substantial body of qualitative and quantitative work by sociologists has examined family systems for handling household money through pooling or maintaining separate pots of money (Kenney, 2006; Paul, 1995, 1990; Heimdal and Houseknecht, 2003; Elizabeth, 2001; Vogler, 1998; Burgoyne and Morison, 1997; Vogler and Paul, 1994). These show that women’s employment and family income are important determinants of respondent’s reports of whether money was pooled and of control over money. In a qualitative study of 22 same-sex couples, individual employment, earnings, and education also seemed to affect family money management systems and reported power over expenditures (Burns et al, 2007). A few quantitative studies have directly examined the relationship of proxies for bargaining power to money management within different-sex couples. Dobbelsteen and Kooreman (1997) assessed the relative merits of two competing influences on reports of household money management: individual

levels of family net worth for retirement (Lundberg and Ward-Batts, 2000; Gibson, Le, and Scobie, 2006), expenditures for children (Lundberg et al, 1997), and child mental health care choices (Zimmerman, 2006) have been used to assess the effects of differences in power assuming that there are gender differences in preferences. 2 A couple of studies have tried to measure individual preferences and to assess the effects of bargaining power on the ability of partners to assert their preferences (Kusago and Barham, 2000; Dosman and Adamowicz, 2006). These studies found that men and women had different preferences, on average, and for Kusago and Barham, that husbands and wives in the same households usually differed in their preferences even given matching (or lack of it) on preferences.

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bargaining power dictating who will control money and household production dictating who will use their time to manage finances. They found that for all but “everyday household spending,” the bargaining power model seemed to predominate given that higher women’s wages predicted more control over money. Similarly, women’s employment, education, and income have all been found to be associated with women having more individual bank accounts and fewer joint accounts (Treas, 1993; Woolley, 2003). Taken together, these empirical studies support the notion that bargaining power affects the system of money management used by couples. Only one of these studies, however, has used a sample of same-sex couples and most have been limited to married couples. Also, few quantitative studies have investigated whether bargaining power operates differently in determining money management within married and unmarried different-sex couples.3 Couple Type and Money Management Systems of money management and their relationship to intrahousehold bargaining power could differ by the type of couple for several reasons: couples may, on average, have different characteristics that interact with bargaining processes (such as relationship duration and child rearing); couples may match up differently; and couples face different legal institutions and social or cultural norms associated with marital status and sexual orientation. Multivariate methods can control for differences in observed characteristics and the associations of those characteristics with accounts separately for each type of couple. However, the contributions of matching processes for partners and of legal, cultural, or social institutions are harder to assess, especially within a single country and time period. Homogamy—the demographic similarity of individuals within couples—could affect the congruence of partner preferences for consumption, time use, risk aversion, and future orientation, among others. Lich-Tyler (undated) suggests that partners will match up on preferences and that this matching will reduce the importance of bargaining to household decisions.4 Demographers have generally found that married couples who are more similar in religion, education, ethnicity, and nationality are less likely to divorce (Kalmijn et al, 2005; Jalovaara, 2003; Weiss and Willis, 1997). Demographic homogamy could thus signify matching preferences that would facilitate relationship longevity, perhaps by

3 Most often differences in quantitative outcomes are allowed by marital status only through changes in the overall average by using an indicator of marital status, rather than with interactions with bargaining power proxies. 4 He suggests that partners will match on similar preferences for consumption and opposite degrees of flexibility and adaptability. This is similar to the argument of Lam (1988) who explained that, in contrast to earlier models by Becker, wages are positively correlated for spouses because of the matching on preferences for household public goods.

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minimizing disagreements over household decisions and the importance of bargaining power. 5 Same-sex couples and unmarried different-sex couples are less homogamous in age, education, and race than are married couples (Jepsen and Jepsen, 2002; Klawitter, 1995; Kurdeck and Schmitt, 1987), but the factors that affect relationship quality and longevity are similar for married different-sex couples and gay and lesbian couples (Kurdeck, 2004). The greater demographic differences between same-sex partners and unmarried different-sex couples could map into differences in preferences that might make household negotiations more difficult and bargaining power more important. Homogamy may be greater for different-sex couples than for same-sex couples because of the larger “markets” of potential partners for heterosexuals, and the greater roles of social norms, cultural institutions (like churches), and families in finding and selecting different-sex partners. Married couples may also be former unmarried different-sex couples that have survived the test of time. Same-sex couples, then, might be a mix of couples akin to married couples in commitment and similarity of preferences (who would marry if given the opportunity) and couples who are akin to unmarried different-sex couples in commitment and preferences. Same-sex couples, by definition, however, are homogamous in gender and many studies find differences in preferences by gender.6 Being of the same gender could mean that partners in same-sex couples have, on average, more similar preferences than do partners in different-sex couples. If the gender differences swamp other demographic differences, bargaining may be less important to household decision-making for same-sex couples than for different-sex couples. As noted above, married and unmarried, different-sex and same-sex couples face very different legal and cultural institutions and these could affect bargaining power within relationships, and the degree to which partners use power. These institutional influences, in particular marital status, affect access to income in the case of death of a partner or dissolution of the relationship, and the degree to which couples can make binding agreements (such as those that facilitate specialization within the family) and have them enforced by courts.7 For example, unmarried couples may be less likely to hold money jointly and more likely to have solely-owned accounts because courts are unlikely to enforce an

5 Though Zimmerman (2006) finds that bargaining power seems to matter only in low conflict households and attributes this to the power of domestic violence, he may not be capturing differences in preferences per se. 6 Most studies, for example, find that women tend to be more risk averse or less risk tolerant than men (for a review see Bajtelsmit and Bernasek, 1996; Barsky et al ,1995; Powell and Ansic, 1997; Jianakoplos and Bernasek, 1998). However, a few studies have found no significant differences by gender in experiments where participants had to make risky choices (Van Praag and Booij, 2003; Brinig, 1994; Jianakoplos and Bernasek, 1998). 7 Chambers (1996) provides an extensive review of US legal benefits of marriage.

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equitable division of assets in the case of separation or because their employers do not offer health benefits for unmarried partners which would create an opportunity for specialization and therefore for sharing. Cultural influences and social circles could also influence money management by creating norms for household organization and support. Same-sex couples or unmarried different-sex couple may keep money separate because they do not view themselves as an economically interdependent family, their families do not given them joint gifts of money, or because their peers do not have joint accounts. Arguments about the role of marital status and social institutions point to the idea that unmarried different-sex and same-sex couples might be less likely to hold money jointly than married couples, and that bargaining power might be more important in determining how money is held by those couples. Similarity of preferences could encourage joint money management, but here there are arguments on both sides: same-sex couples may have more similar preferences than different-sex couples due to gender, but less similar preferences because of size of markets for heterosexuals and marriage as a selection process. Previous research suggests that more bargaining power will lead an individual to be more likely to hold money in his or her own account, rather than jointly, though it is not clear whether those findings will apply within all types of couples. Data and sample The data for this paper come from the U.S. Survey of Consumer Finances (SCF), a cross-sectional study which combines a random sample of U.S. households with a sample of high income families drawn from U.S. tax records. Survey weights adjust for the addition of the non-probability sample and for non-response bias. The SCF also creates five replicate observations for each household with imputations for missing data.8 The SCF collects extensive information on household assets and debts in order to characterize the levels and composition of net worth for U.S. households over time. In addition, the survey collects demographic and labor market information for household members who are financially interdependent.9 In a panel of questions on household assets the SCF asks respondents about all money held in checking accounts, savings accounts, money market accounts, and in certificates of deposit. For these assets, the survey asks for the amount of money held in each account and whether money is held jointly or by one

8Montalto and Sung (1996) describe the SCF imputations and the statistical procedures for analysis using multiple imputations for missing data. All analyses here use the multiple imputations. 9The SCF collects most data for a “primary economic unit” defined as consisting of an “economically dominant” individual or couple and all other individuals in the household who are financially interdependent.

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individual.10 I use this information to construct the outcome measures for this study: indicators of the existence and the dollar share of aggregated joint accounts, accounts held by the head of household, and accounts held by the partner. For some analyses, I also separate checking accounts from savings accounts (including money market and certificates of deposit) given that couples may hold them differently due to their different purposes. The SCF does not collect information on ownership of other assets such as stocks and bonds, family businesses, real estate, capital equipment, so this analysis is limited to more liquid family assets. This study pools data from the surveys done in 1992, 1995, 1998, 2001 and 200411 in order to get a reasonable size sample of same-sex couples. Same-sex couples, married couples, and unmarried different-sex couples are identified by using information on the relationship to the survey respondent (spouse or partner) and the sex of the respondent and partner or spouse.12 To reduce computational time, I use only 10 percent of married couples and adjust the survey weights to compensate. This SCF sample consists of 1295 married couples, 1031 unmarried different-sex couples, and 110 same-sex couples. In different-sex couples, the SCF designates the male partner as the head of household and the female partner as the partner. In same-sex couples, the oldest partner is designated as the “head” and the younger partner is designated as “partner.”13 Empirical Strategy and measures I model the existence of accounts by using a set of three indicators for whether or not a couple has any joint accounts (JOINT), any accounts solely in the head’s name (HEAD), and any solely in the partner’s name (PARTNER). A couple may have any combination of these accounts. The probability that a couple i reports having each type of account can be expressed as a function of the intercept, α, the relative bargaining power of partners, p, relationship characteristics, r , other individual and family characteristics, x, and an error term, ε:

10 The survey asks, for example: “Is this a joint checking account, or is the account in your name, in your husband's (wife’s/partner’s) name, or something else?” 11 Beginning in 2004, Massachusetts allowed same-sex couples to legally marry and it is possible that there are a few in the data set for 2004. Until 2004 no U.S. state recognized marriages for same-sex couples so there were no legally married same-sex couples (though some partners in these couples could be legally married to other people). 12 Respondents were asked their relationship to each household member and asked to identify a spouse or partner. Unmarried couples were indicated by having a “”partner” rather than a “spouse” and same-sex couples were those with partners with same reported gender. 13 This configuration should not affect my results given that my multivariate analyses control for age, and male partners in different-sex couples are nearly all older than female partners.

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jiijijijji xrpJOINT εγδβα ++++== ]1Pr[ hiihiihhi xrpHEAD

hεγδβα ++++== ]1Pr[

piipiipi xrpPARTNERpp

εγδβα ++++== ]1Pr[

Other factors, not in the model, may affect the family’s decisions about all three types of accounts resulting in the correlation of the error terms across these three equations. To account for this, I estimate the three equations as a multivariate Probit system, in which the error terms have a multivariate normal distribution with means equal to zero, variances equal to 1, and correlations ρJointHead, ρJointPartner, and ρHeadPartner. These correlations could reflect the influence of the degree of trust and cooperation between partners, the role of legal, cultural, or social norms that vary across couples, or any other factors not captured by the variables in the model. In addition to modeling the existence of accounts, I model the share of liquid assets held in each type of account designated by JntP, HeadP and PartnerP. Because the share of money held in each type of account is a proportion between 0 and 1, I estimate these relationships using a system of three Tobit models:

jpiijpijpijpjpi xrpJntP εγδβα ++++= 1*0 << iJntPif 0*0 ≤= ii JntPifJntP and *11 ii JntPifJntP ≤=

hpiihpihpihphpi xrpHeadP εγδβα ++++= 1*0 << iHeadPif 0*0 ≤= ii HeadPifHeadP and *11 ii HeadPifHeadP ≤=

ppiippippippppi xrpPartnerP εγδβα ++++= 1*0 << iPartnerPif 0*0 ≤= ii PartnerPifPartnerP and *11 ii PartnerPifPartnerP ≤=

The shares must add to 100 percent, so the coefficients from the models for the three types of accounts are restricted to add to 0, indicating that an increase in the share held in, say, the joint account would require a decrease in the share in one or both of the individual accounts. As with the probability of having accounts above, the three error terms for these share equations are likely to be correlated because of unobserved or omitted family characteristics and these correlations are captured by the parameters ρJointHead, ρJointPartner, and ρHeadPartner. To begin with, I estimate these models by including all couples and adding dummy variables for unmarried different-sex, male same-sex, and female same-sex couples, with married different-sex couples as the reference group. This allows direct comparison across the types of couples and maximizes the sample size for estimating the effects of the other factors. The indicators of couple type

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will capture systematic differences in accounts due to matching markets, cultural or social norms, and legal marital status associated with couple type. Previous research comparing couples has shown that married couples keep finances jointly more often than do unmarried couples. This suggests that the coefficients on the indicators of unmarried different sex and same-sex couples will be negative in the models predicting the existence and size of joint accounts and positive in models predicting individual accounts. However, if similarity of preferences for same-sex couples outweighs other influences, then the coefficients in the joint account model for same-sex couples could be positive. In a second set of analyses, I estimate separate systems of equations by couple type to allow the effects of bargaining power and other characteristics, as well as the correlations in the error terms to differ by couple type. For these analyses, I group male and female same-sex couples together because of the small sample sizes and because they have similar values for the outcome measures.14 The models include several measures of bargaining power drawn from the wide variety used in the literature: relative years of education, relative years of work experience, and relative level of reported health (measured on a 1 to 4 scale). Each is defined as the partner’s level minus the head’s level as a percentage of the head’s level. Together, these measures might capture differences in the ability of partners to assert their own preferences within the household because they have options for income and relationships outside of the current partnership. The measures are not highly correlated and appear to capture different aspects of potential power.15,16 For couples with some earnings, I also estimate an alternative model using the proportion of total earnings that came from the partner as the measure of bargaining power. This model will more closely capture labor market possibilities, but suffers from the problems of not fully reflecting future earnings capacity and of encapsulating current negotiated differences in work time (Pollak, 2005). Because the SCF provides no access to information on geographic location, I cannot use measures of state or local variation in marriage or matching markets, transfer income, or in marriage, divorce, civil union, or domestic partner policies, some of which have been found to be related to bargaining power.

14 The size of the coefficients in the nonlinear models for different couple types cannot be directly compared. To more directly compare, I also test couple differences in the effects of bargaining power and relationship variables in a pooled model with interactions with couple type. However, these models do not allow for differences in the error term correlations or other variables. 15 A principal components analysis showed each of the measures loading on separate factors. I use differences as a percentage of the head’s level to better filter out differences in absolute levels by couple type. For example, married couples have higher average levels of work experience because they are both older on average. 16 Although, health is related to opportunities in both labor and matching markets, it is also possible that individuals in poor health would require additional household resources in order to pay for health care creating a negative relationship between relative partner health and access to money.

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Given previous research, I expected that these measures of the relative power for the partner compared to the head would be positively associated with money being held accounts for the partner rather than the head or jointly. As discussed above, bargaining power could be less important in married couples than in the unmarried different-sex or same-sex couples because married couples might have more closely aligned preferences, be protected by legal institutions, have made agreements during the marriage market, or be guided more strictly by cultural or social norms. This would suggest that the bargaining power measures would provide more predictive power in the models for unmarried different-sex and same-sex couples. Alternatively, if gender differences in preferences are a dominant driver of bargaining within relationships, outcomes for same-sex couples may not show strong associations with proxies for power within the household. In addition to measures of bargaining power, the models include family and individual characteristics. The duration of the relationship and whether or not a couple has children under the age of 18 living at home could both be associated with greater jointness of finances because they serve as markers of further commitment to the relationship or because duration and child rearing directly encourage the conjoining of money.17 Family income could also affect account holdings by affecting norms, changing the distribution of work within families, or increasing the total number of accounts used by a family (and therefore the potential distribution).18 The SCF provides race information only for the survey respondent; the model includes indicators for African American, Hispanic, and other race respondents with the reference group being white respondents.19 Other studies have found that people of color are less likely than whites to hold money jointly (Kenney, 2006; Treas, 1993). Age, education levels (indicators for any college and college degree, with less than college as the reference group), and indicators of whether each partner is in good or excellent health (compared to poor or fair health) are also included. Appendix 1 provides descriptive statistics for the explanatory variables by couple type.

17 The SCF measures relationship duration slightly differently for married and unmarried couples. Married couples are asked about time since marriage, but unmarried couples are asked how long they have lived together. 18 Income could also be associated with the “quasi-wage” for household labor as predicted by a joint marriage/labor market model and this could lead to income being associated with money management. 19 The SCF combines Asian, Native American/Alaska Native, and Native Hawaiian/Pacific Islander with “other” in its public use dataset.

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Results

Before turning to the multivariate models, I first describe differences by couple type in the accounts they hold and in the degree of homogamy. Table 1 shows the types of accounts held and the proportion of money held in accounts for each type of couple. The table demonstrates that married couples are the most likely type of couple to hold money jointly, and unmarried different-sex couples are least likely. The top panel shows the proportion of couples with accounts held jointly by the couple, accounts held solely in the name of the head, and those held solely by the partner. As described above, a couple can have any combination of these accounts. Over 80 percent of married couples had at least one joint account, but only a quarter of unmarried different-sex couples had a joint account. Among same-sex couples 54 percent of male couples and 63 percent of female couples had joint accounts. Individual accounts were held fairly equally by heads and partners and rates were similar for the three types of unmarried couples—between a third and a half of heads and partners had individual accounts. Many fewer individuals in married couples had their own accounts, but again rates were similar for heads (16 percent) and partners (18 percent). The share of money held in joint accounts showed the same pattern of much higher levels for married couples (82 percent) and the lowest levels for unmarried different-sex couples (24 percent). Slightly more than half of the money in liquid accounts was held jointly for male and female same-sex couples. For each type of couple, the shares held in individual accounts for heads and partners were relatively similar. Some research has suggested that because checking accounts and savings accounts differ in purpose and in the time required for management, their associations with family characteristics might differ. Here, the overall patterns by type of couple and head/partner status hold for both checking and savings accounts: joint accounts are most common for married couples and least for unmarried different-sex couples, and there are not large differences by head and partner status. Fewer couples of each type hold savings accounts than checking accounts. These patterns in account holdings by type of couple could potentially be explained by characteristics of individuals within these couples, characteristics of the couples such as duration of relationships or child-rearing, or by differences in the relative bargaining power of partners and its importance. The multivariate analysis helps to disentangle these influences. How do couples compare on levels of homogamy? As discussed above, more similar couples may be more closely matched on preferences which could

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decrease the importance of bargaining power within the household. Table 2 shows the correlations between characteristics for members of married, unmarried different-sex, and same-sex couples. Married and same-sex couples are more closely matched on age (rho=.92 to .95) and education (rho≈ .65) than are unmarried different sex couples (rho=.85 for age and .53 for education). Work experience is least correlated for members of married couples and similar for unmarried different-sex and same-sex couples, most likely due to household specialization within married couples. Married couples are more closely matched on health than are the other couples, but same-sex couples are less similar than are unmarried different-sex couples. On all but work experience, married couples are most closely matched demographically (and therefore potentially matched on preferences), but same-sex couples are close behind in all but health. Accounts for all couples Table 3 shows coefficients and standard errors for the multivariate Probit model of the likelihood of a couple having joint accounts, head accounts, and partner accounts. The sample is all couples and the model includes indicators for unmarried different-sex, male, and female couples with married couples serving as the reference group. This model allows direct comparison by the type of couple while controlling for measures of relative bargaining power and family and individual characteristics.20

After controlling for the other factors, both different-sex and same-sex unmarried couples were less likely than were married couples to have joint accounts (left side columns) and more likely to have accounts for heads (center) and partners (right hand side).

Almost none of the measures of relative bargaining power are statistically significant in this model that groups all couples and the measures as a group are only marginally significant for partner accounts (p=.08).

Two other family characteristics have important effects here and in all of the other multivariate models. Couples with longer relationships and those with children under 18 in the household were more likely to have joint accounts and less likely to have individual accounts for both heads and partners. Even after controlling for family and individual characteristics, there were significant correlations between the probabilities of having individual and joint accounts. These correlations suggest that couples were likely to choose either a system of individual accounts or joint accounts: the chance of having a joint

20 I also ran this model and those separately by couple type with dummy variables for each survey year. A few of the year dummies were statistically significant, but the other results were virtually unchanged.

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account was negatively related to the chances of having either a head or partner individual account (ρ=-.52 and -.50, respectively) and the chances of having head and partner accounts were positively correlated (ρ=.44).

Accounts by Couple Type

To further explore the determinants of money management, Table 4 shows results from the multivariate Probit analysis separately for each couple type. The table shows only the effects of bargaining power and family characteristics (relationship duration and child-rearing) on the chances a couple holds joint or individual accounts. [The full results are in Appendix 2.] Female and male same-sex couples were combined because of small sample sizes and an indicator for male couples was added to allow a difference in the overall probability of account types.21 On the whole, the results support the notion that measures of bargaining power might matter more for financial management for unmarried different-sex couples and same-sex couples than for married couples.22 In addition, relationship duration and child-rearing affect money management for each type of couple. The top panel shows the bargaining power and family characteristic coefficients predicting joint account ownership for each couple type. None of the power measures is significantly related to the chances of having joint accounts for any of the couple types. Also, for each type of couple, we cannot reject the joint hypothesis that the power measure coefficients are all zero. However, relationship duration and having children under 18 years old increased the chances of having joint accounts for all couples (with one exception--the coefficient on child-rearing for same-sex couples was positive, but not statistically significant). The chances of having individual accounts for the head showed a closer relationship to the power measures for the unmarried different-sex and same-sex couples. For married couples, none of the bargaining power measures was individually statistically significant, nor were they as a group (p=.71). In unmarried different-sex couples, heads were less likely to have accounts when their partners had more work experience (relative to the head) and better relative

21 Indicators of Hispanic and other race categories were also dropped from the model for same-sex couples because of small numbers of observations in those groups. 22 These results were very similar to those from those from a model that pooled all couples and used interactions of couple type with the power and family variables to directly test differences. In the pooled results none of the power variables was significant for married couples, the interactions were significant for same-sex couples for the head and partner accounts, but for unmarried different-sex couples the power measures did not quite reach statistical significance in the head account equation with p=.13. The Table 4 results, however, also allow differences in the effects of other factors and the error term correlations by couple type that affect the other estimates.

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health. For same-sex couples, head accounts were less common when partners had relatively more education as expected, but head accounts were more likely when partners had relatively more work experience. For unmarried different-sex and same-sex couples, we can reject the joint hypothesis that the power measure coefficients are all zero (p=.01 for both). Accounts for the head were less likely for different-sex couples with longer relationships and for unmarried different-sex and same-sex couples with children at home. Partner accounts were not closely related to the measures of power—the accounts were more likely only for same-sex couples in which partners had more work experience relative to the head. As with accounts for heads, partner accounts were less common with more years in the relationship and when the couple had children for married and unmarried different-sex couples, however, the coefficients were not significant for same-sex couples. The correlations across the error terms for each type of couple again suggest that, after accounting for the explanatory factors, couples are likely to choose between a system of joint or individual accounts creating negative correlations between joint accounts and individual accounts and positive correlations between head and partner accounts. This pattern of bargaining power being more important in unmarried different-sex and same-sex couples than for married couples also held when using relative earnings as an alternative measure of bargaining power and when looking separately at patterns of checking accounts and savings accounts. [Results available from author.] Figure 1 shows the predicted probability of having a joint account over the relationship duration by the type of couple. The predicted probabilities are based on the multivariate Probit models for each type of couple from Table 4 and hold constant all factors other than relationship duration.23 The graphic demonstrates that, holding constant family and individual characteristics, unmarried different-sex and same-sex couples have lower chances of having joint accounts than do married couples at any time in their relationship. However, the increase in joint accounts with relationship duration is much greater for same-sex and unmarried different-sex couples than for married couples, so the probabilities of having joint accounts are much closer for longer relationships.24

23 The results assume that the couple has children, has full-sample average levels for the bargaining power measures, income, and ages, that both have some college, both are in good health, and that the respondent is white. For same-sex couples, the line for female couples is shown; the line for male couples is very similar, but slightly lower. For each type, relationship duration in the sample ranges between zero and at least 40 years. 24 A small part of these differences could be attributable to how duration is measured: for married couples the question asks about time since marriage; for other couples the question asks about

15

Share of Money in Accounts To further assess the patterns of accounts, I use multivariate Tobit models of the proportion of money held in joint, head, and partner accounts. Models that pool all couples show that, as with the existence of accounts, married couples hold a larger share of their money in joint accounts and less in individual accounts than do unmarried different-sex or same-sex couples after controlling for other family and individual characteristics (results not shown here). Table 6 shows results from multivariateTobit analyses of the account shares separately for the three types of couples. These analyses of account shares by couple type generally support the earlier results--bargaining power measures affected the share in individual accounts for unmarried different-sex couples and same-sex couples, but not for married couples.25 For unmarried different-sex couples, greater relative education and work experience for partners was associated with smaller shares in head accounts and larger shares in partner accounts. Partner accounts were also larger when partners were in relatively better health. For same-sex couples, when partners had relatively more education the share in joint accounts was larger and the share in accounts for partners was smaller. The effects of relationship duration and child-rearing were not as striking in predictions of shares as with account ownership, but when significant they were positively related to the size of joint accounts and negatively related to the size of individual accounts. Parallel to the models of account existence, the estimated correlations between the error terms in the share models (rhos) for the size of joint accounts and both types of individual accounts are negative and significant for each type of couple. In the share models, however, the correlation between errors for head and partner accounts are positive and significant (reinforcing the idea of choosing a system of joint or individual accounts) only for married couples.

time living together. However, time together prior to marriage for married couples is unlikely to exceed 5 years and could not account for these large differences. 25 In a pooled sample of all couples interactions between the power variables and couple type again followed the results from these separate models with these exceptions: 1) for same-sex couples relative work experiences became significant in the partner equation and significant (and negative) in the joint equation, and 2) for unmarried couples the effect of relative health was not significantly different than for married couples. Again, these results do not allow for differences in the effects of other factors and in correlations in the error terms (clearly the case in the tobit models) .

16

Conclusions The overall picture painted by these analyses is clear: married couples are much more likely to hold money jointly than are unmarried different-sex and same-sex couples even after accounting for individual and relationship characteristics. Couples of each type, however, do hold money jointly and relationship duration and child-rearing are important predictors of money management. Perhaps more intriguing are the findings regarding the connection of individual power to account portfolios for different types of couples. These results suggest that bargaining power proxies are better predictors of account holdings for same-sex and unmarried different-sex couples than for married couples. The findings are preliminary because of the very small samples of same-sex couples and the variation across measures of bargaining power. However, the empirical results at least point to the possibility of different bargaining structures across marital status and sexual orientation. Differences in the size and operation of “marriage markets” by couple type, in legal, cultural, and social institutions, in homogeneity of preferences within couples, and in gender roles could all help to explain the findings. The influence of gender could be better assessed if sample sizes allowed us to separately examine the relationship of bargaining power to money management for male and female same-sex couples. These findings of differences in money handling by couple type could be unique to this point in time for a number of reasons. New legal institutions (like domestic partnership registries, civil unions, and same-sex marriage) are developing for unmarried different-sex and same-sex couples and these could profoundly affect their financial frameworks. New generations of same-sex couples and unmarried different-sex are coming of age under vastly different social constraints and supports than faced by earlier generations—these too could greatly change the ways in which they view their finances and the pressures they face from families and friends. Finally, for all types of couples, on-line banking, bill-paying, and credit card statements alter the time costs of financial management and the degree of financial information sharing within couples in ways that could create new incentives for either joint or individual accounts. Further research using additional sources of data with larger samples of same-sex couples would help establish a baseline for exploring potential future trends.

17

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20

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21

Tabl

e 1:

Exis

tenc

e an

d Si

ze o

f Joi

nt a

nd In

divi

dual

Acc

ount

s by

Typ

e of

Cou

ple

Mar

ried

Diff

eren

t-Se

x C

oupl

es

Unm

arrie

d D

iffer

ent-S

ex

Cou

ples

Mal

e Sa

me-

Sex

Cou

ples

Fem

ale

Sam

e-Se

x C

oupl

es

Indi

vidu

al a

nd J

oint

Acc

ount

s:C

oupl

e ha

s jo

int a

ccou

nt83

%24

%54

%63

%H

ead

has

indi

vidu

al a

ccou

nt16

%42

%42

%36

%Pa

rtner

has

indi

vidu

al a

ccou

nt18

%46

%35

%33

%

Shar

e of

Liq

uid

Asse

ts in

Acc

ount

s fo

r tho

se

with

at l

east

one

acc

ount

:Sh

are

in jo

int a

ccou

nts

82%

24%

53%

58%

Shar

e in

hea

d's

acco

unts

9%36

%25

%24

%Sh

are

in p

artn

er’s

acc

ount

s9%

40%

22%

18%

Che

ckin

g Ac

coun

ts:

Cou

ple

has

join

t acc

ount

82%

22%

54%

60%

Hea

d ha

s in

divi

dual

acc

ount

14%

40%

40%

34%

Partn

er h

as in

divi

dual

acc

ount

15%

45%

34%

33%

Savi

ngs

Acco

unts

:C

oupl

e ha

s jo

int a

ccou

nt52

%13

%41

%37

%H

ead

has

indi

vidu

al a

ccou

nt12

%25

%35

%17

%Pa

rtner

has

indi

vidu

al a

ccou

nt13

%25

%22

%24

%

Sam

ple

Size

1295

1031

6545

Not

es: P

ropo

rtion

s es

timat

ed u

sing

wei

ghts

and

acc

ount

ing

for m

ultip

le im

puta

tions

of m

issi

ng d

ata.

22

Table 2: Correlations of Partner Demographics by Type of Couple

Married Different Sex

Couples

Unmarried Different Sex

CouplesMale Same-Sex

CouplesFemale Same-Sex Couples

Age 0.95 0.85 0.93 0.92

Education 0.64 0.53 0.67 0.65

Work Experience 0.39 0.60 0.75 0.57

Health 0.45 0.39 0.28 0.29

Note: Correlations are computed using weighted data for multiple imputations.

23

Table 3: Multivariate Probit Results for Likelihood of Joint, Head, and Partner Accounts for All Couples

Joint Account Head Account Partner Account

Coeff. Std Error Coeff. Std Error Coeff. Std Error

Unmarried Different-Sex -1.239 ** 0.077 0.769 ** 0.077 0.664 ** 0.076

Female Same-Sex -0.834 ** 0.209 0.538 ** 0.209 0.565 ** 0.212Male Same-Sex -0.903 ** 0.177 0.734 ** 0.174 0.734 ** 0.173

Relative Education (partner-head/head) 0.025 0.088 -0.075 0.102 0.013 0.078Relative Work experience (partner-head/head) -0.009 0.025 -0.091 ** 0.037 0.013 0.023Relative Health (partner-head/head) -0.109 0.073 -0.004 0.066 0.156 ** 0.065

Joint test of power measures: F value and p value 0.82 0.48 2.21 0.08 1.99 0.11

Relationship Duration 0.022 ** 0.004 -0.021 ** 0.004 -0.017 ** 0.004Children under 18 at home 0.269 ** 0.069 -0.243 ** 0.064 -0.210 ** 0.063Income ($10,000) -0.001 0.002 0.004 ** 0.002 0.003 0.002

African American Respondent -0.421 ** 0.107 -0.217 ** 0.102 -0.105 0.097Hispanic Respondent -0.618 ** 0.120 -0.173 0.112 -0.165 0.109Other Race Respondent -0.044 0.175 0.016 0.154 -0.302 * 0.159Age of Head -0.005 0.005 0.023 ** 0.005 -0.006 0.005Age of Partner 0.005 0.006 -0.006 0.006 0.022 ** 0.005Some College Head 0.260 ** 0.096 0.317 ** 0.090 0.024 0.088College Degree Head 0.254 ** 0.091 0.506 ** 0.088 0.100 0.085Some College Partner 0.087 0.092 0.067 0.085 0.328 ** 0.082College Degree Partner 0.122 0.091 0.223 ** 0.083 0.382 ** 0.081Good Health Head 0.000 0.097 0.071 0.095 0.137 0.092Good Health Partner 0.307 ** 0.108 0.166 0.107 -0.006 0.100Intercept 0.069 0.183 -1.721 ** 0.179 -1.385 ** 0.172

Rho Head and Partner Accounts 0.444 ** 0.032Rho Head and Joint Accounts -0.515 ** 0.035Rho Partner and Joint Accounts -0.501 ** 0.032

Note: Coefficients and Standard Errors from Multivariate Probit analysis of joint, head, and partner accounts including multiple imputations for missing data. * indicates significant at 10 percent; ** indicates significant at 5 percent;

24

Tabl

e 4:

Mul

tivar

iate

Pro

bit R

esul

ts fo

r Lik

elih

ood

of J

oint

, Hea

d, a

nd

Part

ner A

ccou

nts

by C

oupl

e Ty

pe

Mar

ried

Unm

arrie

d D

iff.-s

exSa

me-

sex

Coe

ff.St

d Er

ror

Coe

ff.St

d Er

ror

Coe

ff.St

d Er

ror

Join

t Acc

ount

s:R

elat

ive

Edu

catio

n (p

artn

er-h

ead/

head

)0.

194

0.19

8-0

.023

0.12

01.

752

1.81

8R

elat

ive

Wor

k ex

perie

nce

(par

tner

-hea

d/he

ad)

0.02

20.

043

-0.0

320.

045

-0.4

480.

298

Rel

ativ

e H

ealth

(par

tner

-hea

d/he

ad)

-0.0

620.

110

-0.1

310.

104

-0.1

270.

324

Join

t tes

t of p

ower

mea

sure

s: F

val

ue (p

valu

e)0.

510

0.67

40.

760

0.51

70.

860.

463

Rel

atio

nshi

p D

urat

ion

0.02

3**

0.00

50.

030

**0.

008

0.04

4*

0.02

6C

hild

ren

unde

r 18

at h

ome

0.20

6*

0.10

50.

226

**0.

099

0.64

40.

459

Hea

d Ac

coun

ts:

Rel

ativ

e E

duca

tion

(par

tner

-hea

d/he

ad)

0.05

10.

184

-0.1

330.

156

-4.2

56**

1.82

1R

elat

ive

Wor

k ex

perie

nce

(par

tner

-hea

d/he

ad)

-0.0

270.

054

-0.1

19**

0.04

80.

809

**0.

306

Rel

ativ

e H

ealth

(par

tner

-hea

d/he

ad)

0.10

90.

107

-0.1

85*

0.09

80.

569

0.37

2

Join

t tes

t of p

ower

mea

sure

s: F

val

ue (p

valu

e)0.

450

0.71

43.

630

**0.

012

3.71

**0.

011

Rel

atio

nshi

p D

urat

ion

-0.0

23**

0.00

5-0

.022

**0.

008

-0.0

410.

029

Chi

ldre

n un

der 1

8 at

hom

e-0

.001

0.09

6-0

.378

**0.

094

-1.4

60**

0.48

1

Part

ner A

ccou

nts:

Rel

ativ

e E

duca

tion

(par

tner

-hea

d/he

ad)

-0.1

310.

187

0.05

70.

089

-1.2

001.

512

Rel

ativ

e W

ork

expe

rienc

e (p

artn

er-h

ead/

head

)-0

.027

0.04

60.

021

0.03

51.

050

**0.

379

Rel

ativ

e H

ealth

(par

tner

-hea

d/he

ad)

0.16

40.

103

0.14

80.

094

-0.1

900.

341

Join

t tes

t of p

ower

mea

sure

s: F

val

ue (p

valu

e)1.

160

0.32

31.

130

0.33

72.

49*

0.05

9

Rel

atio

nshi

p D

urat

ion

-0.0

18**

0.00

5-0

.021

**0.

008

-0.0

420.

030

Chi

ldre

n un

der 1

8 at

hom

e-0

.168

*0.

097

-0.1

84**

0.09

1-0

.445

0.45

5

Rho

Hea

d an

d P

artn

er A

ccou

nts

0.58

7**

0.04

10.

237

**0.

055

0.83

8**

0.10

1R

ho H

ead

and

Join

t Acc

ount

s-0

.673

**0.

042

-0.3

78**

0.05

9-0

.678

**0.

175

Rho

Par

tner

and

Joi

nt A

ccou

nts

-0.6

12**

0.04

2-0

.368

**0.

054

-0.6

33**

0.14

4N

ote:

Coe

ffici

ents

and

Sta

ndar

d Er

rors

from

Mul

tivar

iate

Pro

bit a

naly

sis

of jo

int,

head

, and

par

tner

acc

ount

s in

clud

ing

mul

tiple

impu

tatio

ns fo

r mis

sing

dat

a.

* in

dica

tes

sign

ifica

nt a

t 10

perc

ent;

**

indi

cate

s si

gnifi

cant

at 5

per

cent

;

25

Figu

re 1

: Pr

edic

ted

Prop

ortio

n of

Cou

ples

with

Joi

nt A

ccou

nts

by C

oupl

e Ty

pe

Not

e: B

ased

on

Mul

tivar

iate

Pro

bit m

odel

s fo

r eac

h co

uple

type

dis

play

ed in

Tab

le 4

.

0%10%

20%

30%

40%

50%

60%

70%

80%

90%

100% Y

ears

inR

elat

ions

hip

510

1520

2530

35

Sam

e-S

ex

Mar

ried

Unm

arrie

d D

iffer

ent-S

ex

26

Tabl

e 5:

Mul

tivar

iate

Tob

it R

esul

ts fo

r Sha

re o

f Mon

ey in

Joi

nt, H

ead,

and

Pa

rtne

r Acc

ount

s by

Cou

ple

Type

Mar

ried

Unm

arrie

d D

iff.-s

exSa

me-

sex

Coe

ff.St

d Er

ror

Coe

ff.St

d Er

ror

Coe

ff.St

d Er

ror

Join

t Acc

ount

s:R

elat

ive

Educ

atio

n (p

artn

er-h

ead/

head

)-0

.001

0.11

1-0

.029

0.13

52.

024

*1.

204

Rel

ativ

e W

ork

expe

rienc

e (p

artn

er-h

ead/

head

)0.

031

0.04

5-0

.004

0.03

5-0

.390

0.31

5R

elat

ive

Hea

lth (p

artn

er-h

ead/

head

)-0

.075

0.06

2-0

.026

0.05

9-0

.068

0.17

7

Rel

atio

nshi

p D

urat

ion

0.00

30.

003

0.01

9**

0.00

50.

007

0.01

5C

hild

ren

unde

r 18

at h

ome

0.20

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151

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70.

325

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d Ac

coun

ts:

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ativ

e Ed

ucat

ion

(par

tner

-hea

d/he

ad)

-0.0

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0.15

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835

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ativ

e W

ork

expe

rienc

e (p

artn

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171

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ativ

e H

ealth

(par

tner

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d/he

ad)

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ldre

n un

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8 at

hom

e-0

.094

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-0.5

61**

0.22

0

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ner A

ccou

nts:

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ativ

e Ed

ucat

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(par

tner

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ad)

0.01

50.

095

0.30

2*

0.15

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elat

ive

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k ex

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nce

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ren

unde

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d an

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rtner

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ount

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ount

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nt A

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6

Not

e: C

oeffi

cien

ts a

nd S

tand

ard

Erro

rs fr

om M

ultiv

aria

teTo

bit a

naly

sis

of jo

int,

head

, and

par

tner

acc

ount

s in

clud

ing

mul

tiple

impu

tatio

ns fo

r mis

sing

dat

a. C

oeffi

cien

ts a

re re

stric

ted

to s

um to

zer

o fo

r the

thre

e m

odel

s.* i

ndic

ates

sig

nific

ant a

t 10

perc

ent;

**

indi

cate

s si

gnifi

cant

at 5

per

cent

;

27

Appe

ndix

1: D

escr

iptiv

e St

atis

tics

by C

oupl

e Ty

pe

Mar

ried

Unm

arrie

d di

ff.-s

exM

ale

Sam

e-Se

xFe

mal

e Sa

me-

sex

Varia

ble

Mea

nSt

d Er

ror

Mea

nSt

d Er

ror

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nSt

d Er

ror

Mea

nSt

d Er

ror

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ativ

e Ed

ucat

ion

(par

tner

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ad/h

ead)

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001

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0.06

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ativ

e W

ork

expe

rienc

e

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.05

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270.

17R

elat

ive

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lth (

part

ner-

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d)-0

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urat

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06

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me

($10

,000

)0.

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850.

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14

Whi

te R

espo

nden

t0.

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010.

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rican

Am

eric

an

Res

pond

ent

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pani

c R

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t0.

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ther

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e R

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e of

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d48

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e of

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tner

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lege

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d0.

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07So

me

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lege

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d0.

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06C

olle

ge D

egre

e H

ead

0.42

0.01

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0.42

0.08

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Col

lege

Par

tner

0.46

0.01

0.56

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0.06

0.33

0.07

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e C

olle

ge P

artn

er0.

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010.

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e Pa

rtne

r0.

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08G

ood

Hea

lth H

ead

0.81

0.01

0.77

0.01

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0.05

0.75

0.07

Goo

d H

ealth

Par

tner

0.81

0.01

0.79

0.01

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0.04

0.77

0.07

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ner E

arni

ngs

as

Perc

enta

ge o

f Tot

al0.

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06

Not

e: W

eigh

ted

stat

istic

s us

ing

mul

tiple

impu

tatio

ns.

28

Appendix 2: Full Multivariate Probit Results by Couple Type

Married Unmarried diff.-sex Same-sex Variable Coeff. Std.Err. Coeff. Std.Err. Coeff. Std.Err.

Joint AccountsIntercept 0.243 0.287 -1.176 ** 0.223 -0.926 1.088Male Same-sex couple -- -- -0.225 0.332Relative Education (partner-head/head) 0.194 0.198 -0.023 0.120 1.752 1.818Relative Work experience (partner-head/head) 0.022 0.043 -0.032 0.045 -0.448 0.298Relative Health (partner-head/head) -0.062 0.110 -0.131 0.104 -0.127 0.324Relationship duration 0.023 ** 0.005 0.030 ** 0.008 0.044 * 0.026Children under 18 at home 0.206 * 0.105 0.226 ** 0.099 0.644 0.459Income ($10,000) -0.003 0.002 0.003 0.006 0.012 0.023African American Respondent -0.520 ** 0.175 -0.347 ** 0.136 -1.482 * 0.879Hispanic Respondent -0.588 ** 0.177 -0.659 ** 0.174 --Other Race Respondent -0.099 0.225 0.107 0.259 --Age of Head -0.018 ** 0.008 -0.001 0.007 0.006 0.026Age of Partner 0.013 0.010 0.002 0.008 -0.006 0.041Some College Head 0.334 ** 0.149 0.215 0.133 0.577 0.603College Degree Head 0.394 ** 0.142 0.108 0.135 0.705 0.804Some College Partner 0.156 0.143 0.015 0.125 -0.630 0.656College Degree Partner 0.125 0.139 0.028 0.133 -0.276 0.718Good Health Head 0.183 0.144 -0.176 0.140 -0.089 0.476Good Health Partner 0.161 0.158 0.452 ** 0.157 0.170 0.673

Head AccountsIntercept -1.947 ** 0.295 -0.824 ** 0.211 -1.577 1.224Male Same-sex couple -- -- -0.047 0.346Relative Education (partner-head/head) 0.051 0.184 -0.133 0.156 -4.256 ** 1.821Relative Work experience (partner-head/head) -0.027 0.054 -0.119 ** 0.048 0.809 ** 0.306Relative Health (partner-head/head) 0.109 0.107 -0.185 * 0.098 0.569 0.372Relationship duration -0.023 ** 0.005 -0.022 ** 0.008 -0.041 0.029

Children under 18 at home -0.001 0.096 -0.378 ** 0.094 -1.460 ** 0.481Income ($10,000) 0.003 0.002 0.105 ** 0.033 0.139 0.131African American Respondent -0.011 0.183 -0.319 ** 0.133 0.452 0.541Hispanic Respondent -0.248 0.213 -0.128 0.141 --Other Race Respondent -0.271 0.213 0.522 * 0.268 --Age of Head 0.022 ** 0.008 0.021 ** 0.007 0.045 * 0.026Age of Partner 0.003 0.009 -0.011 0.008 -0.031 0.043

Some College Head 0.268 * 0.154 0.303 ** 0.127 0.548 0.548College Degree Head 0.401 ** 0.148 0.605 ** 0.134 0.383 0.721

Some College Partner -0.004 0.136 0.141 0.122 0.405 0.620College Degree Partner 0.142 0.129 0.307 ** 0.129 0.308 0.738Good Health Head 0.151 0.154 -0.021 0.135 0.922 * 0.490Good Health Partner 0.019 0.159 0.262 * 0.147 0.125 0.655

Continued on next page.

29

Partner AccountsIntercept -1.426 ** 0.281 -0.719 ** 0.200 -3.263 ** 1.303Male Same-sex couple -- -- 0.486 0.335Relative Education (partner-head/head) -0.131 0.187 0.057 0.089 -1.200 1.512Relative Work experience (partner-head/head) -0.027 0.046 0.021 0.035 1.050 ** 0.379Relative Health (partner-head/head) 0.164 0.103 0.148 0.094 -0.190 0.341relationship duration -0.018 ** 0.005 -0.021 ** 0.008 -0.042 0.030Children under 18 at home -0.168 * 0.097 -0.184 ** 0.091 -0.445 0.455Income ($10,000) 0.003 0.002 0.003 0.008 -0.007 0.023African American Respondent 0.197 0.179 -0.250 ** 0.122 -0.110 0.605Hispanic Respondent 0.059 0.197 -0.290 ** 0.138 --Other Race Respondent -0.266 0.209 -0.451 * 0.247 --Age of Head 0.007 0.008 -0.014 ** 0.007 0.020 0.027Age of Partner 0.013 0.009 0.028 ** 0.007 0.033 0.045Some College Head -0.252 * 0.146 0.218 * 0.120 0.567 0.527College Degree Head 0.033 0.138 0.147 0.125 0.022 0.677Some College Partner 0.119 0.131 0.527 ** 0.114 0.105 0.577College Degree Partner 0.299 ** 0.127 0.457 ** 0.118 0.696 0.687Good Health Head 0.085 0.144 0.213 0.130 0.263 0.465Good Health Partner 0.015 0.155 -0.044 0.139 0.882 0.636

Rho Head and Partner Accounts 0.587 ** 0.041 0.237 ** 0.055 0.838 ** 0.101Rho Head and Joint Accounts -0.673 ** 0.042 -0.378 ** 0.059 -0.678 ** 0.175Rho Partner and Joint Accounts -0.612 ** 0.042 -0.368 ** 0.054 -0.633 ** 0.144Note: Coefficients and Standard Errors from Multivariate Probit analysis of joint, head, and partner accounts including multiple imputations for missing data. * indicates significant at 10 percent; ** indicates significant at 5 percent;