Abstract
While most studies on wealth inequality focus on the inequality between households, this paper examines the distribution of wealth within couples. For this purpose, we make use of unique individual level micro data from the German socio-economic panel study. In married and cohabiting couples men’s net worth, on average, is 33,000 euros higher than women’s. We look at five different sets of factors (demographics, income, labor market, inheritances, financial decision-making in the partnership) that might explain this wealth gap. We find that all factors contribute to the explanation of the wealth gap within partnerships, with inheritances and income being particularly relevant. Furthermore, we find that specific characteristics (e.g., self-employment, no migration background, inheritances, high income) that decrease the wealth gap for women increase it for men. For men the respective coefficients are even stronger in absolute terms. When examining intra-partnership financial decision-making, we find the gap to be significantly smaller when the female partner manages the money and larger if the male partner has the last word in financial decisions.
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Notes
Kan and Laurie (2010) report that there is a general downward trend for UK couples over the period 1995–2005 in joint holdings of savings, investments, and debts, “which may suggest a growing independence in financial arrangements between couple members over that period” (p. 1).
Given the main focus of our research on analyzing the gender wealth gap within couples, we refrain from considering homosexual partnerships.
Most survey data does not capture public pension entitlements as these are, for the most part, not known to the respondent. For the relevance of public pension entitlements in wealth inequality research, see Frick and Grabka (2013).
We use wealth and net worth interchangeably in the paper. Net worth is defined as the difference between total assets and liabilities.
The results are robust to including the square and the cubic of the inverse hyperbolic sine of the couple’s total wealth.
In the case that the income information is missing for some years, we only use the available years for the computation of the mean. All income information is transformed to 2005 euros.
We refrain from considering the amount of an inheritance/bestowal in order to avoid any assumptions about appreciation (e.g., appreciation differs for property and financial assets) and investment patterns given the timing of inheritances and correction of item-non-response. We do perform robustness checks with uncorrected amount variables (see Sect. 4.2.1).
It should be noted that managing the money in a couple does not necessarily imply controlling the financial resources (Pahl 1995). We also find this to be the case in our data based on the two variables (“last word in financial decisions” and “money management”).
An explicit treatment of financial decision-making in Italy can be found in Bertocchi et al. (2012).
The original wording of the five answer categories is (a) everyone looks after their own money, (b) we put the money together and both of us take what we need, (c) we put a share of the money together, and both of us keep a share of it for ourselves, (d) I look after the money and provide my partner with a share of it, (e) my partner looks after the money and provides me with a share of it.
One cannot assume a perfect match of the answers by both partners. However, there is a large overlap. For robustness purposes we considered different codings of the power variables. We used (a) only the male partner’s information, (b) the woman’s answer and an additional dummy variable indicating a deviating answer of the man, and (c) only the information of couples without contradictions. For all these codings the results did not change meaningfully. In terms of financial decision-making, the highest overlap of about 95 % can be found for those stating that both have the last word. If the female answer that the partner has the last word, there is an overlap of at least 70 %. While if she declares to have the last word the accordance is about 67 %. For the latter two groups about 27 % of the male partners have the opinion that a joint decision-making process is taking place. There is also no full overlap between the answers of both partners with respect to money management. The share of overlaps varies from 76 % for part of money is shared to 95 % for all money is shared.
Cohort effects play a particular role between East and West Germany. The socialist German Democratic Republic prior to 1989 had a policy of gender equality granting women equal rights and equal obligations and resulting in a higher share of women employed full-time in East than in West Germany. These cultural differences could also translate into a gender wealth gap and, in fact, our findings confirm this. For those living in East Germany when the Berlin Wall came down, the mean intra-partnership wealth gap is less than 14,000 euros, while the respective figure for West Germans is roughly 39,000 euros.
Business assets strongly contribute to the intra-partnership wealth gap. The mean value of business assets is 3,600 euros for all married and cohabiting women while this figure is 28,000 euros for all men. Thus, women only have 13 % of the corresponding business assets of men. For all other wealth components, this proportion/is much higher. Owner-occupied property is more equally distributed. Here, women have achieved a share of about 80 % (54,000 euros compared to 67,000 euros). When we exclude the population of self-employed for a robustness check, the general results are confirmed. Similarly, the results are also robust to the exclusion of couples in which one of the spouses works as a civil servant.
For a robustness check, we include the uncorrected logarithm of the amount of inheritances together with the year of the inheritance. The results indicate that, ceteris paribus, a 10 % increase in inheritances of females decreases the wealth gap by more than 9 %. Conversely, the gap increases by about 8 % for a 10 % increase in the males inheritances. The coefficients of the other variables do not change meaningfully and the model fit improves slightly (R2 increases by 0.003). These results are available from the authors upon request.
In an additional robustness check we exclude information about age given that previous literature (e.g. Lundberg and Ward-Batts 2000) used the age difference as a control for bargaining power within the household. However, the general results could be confirmed.
We explicitly want to consider these three different groups that differ in qualitative terms. A quantile regression technique would subdivide the total population by percentiles only. We also run a multinomial logit where the reference group consists of couples where the individual wealth share varies between 40 and 60 % of total couple’s wealth in order to relax the strict assumption of having identical net worth. The main findings are confirmed. In an alternative specification we estimated an ordered probit model, which provided very similar results.
The χ 2 test gives information whether the covariates from specification F > M and M > F are significantly different from each other.
This finding could also reflect reverse causality, given that women with more wealth may persuade their partners to work less and do more housework.
For example, separate money management might lead a woman to return to full-time employment sooner after giving birth than she would if the couple practices joint decision-making and would thus impact the individual wealth level (see also Kenney 2006). To analyze the causal relationship, one could think about instrumental variables, but finding an adequate (strong) instrument is a challenge. An alternative could be the use of randomized experiments, but our research setting does not allow for this possibility. Having longitudinal data at hand would of course enable us to analyze the change of individual and household wealth for new couples between 2002 and 2007 as a function of financial decision-making. However, we only have 59 cases in which information for both new partners is available.
A special case could be debts. Even if only one partner holds a mortgage (which would be assigned in the questionnaire to that person only) in case of a divorce, banks usually force the other partner to amortize the outstanding debt.
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Acknowledgments
The authors would like to thank Francesco Figari, Adam Lederer, Deborah Anne Bowen, the participants of the 2012 IARIW conference, the 2013 ECINEQ conference, 2013 ESA conference, two anonymous referees and the editor Shoshana Grossbard for helpful suggestions and comments. Markus M. Grabka thanks the Hans-Boeckler-Foundation for the project on ‘Vermögen in Deutschland. Status quo-Analysen und Perspektiven’ (HBS-Project-Nr. 2012-610-4).
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Grabka, M.M., Marcus, J. & Sierminska, E. Wealth distribution within couples. Rev Econ Household 13, 459–486 (2015). https://doi.org/10.1007/s11150-013-9229-2
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DOI: https://doi.org/10.1007/s11150-013-9229-2