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Wealth Holdings and Portfolio Allocation of the Elderly: The Role of Marital History

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Abstract

This paper investigates the role of marital history in terms of explaining differences in wealth holdings and portfolio allocation of older individuals by studying data from the first wave of Health and Retirement Study which was conducted in 1992. The results generally suggest that both men and women suffer from the negative shocks of past marital dissolutions in terms of household wealth accumulation. The significance level, however, differs across currently married couples, single males, and single females. The examination of the asset components of net worth also indicates that both the probability of owning a particular asset and the fraction of wealth allocated to that asset might vary depending on the elderly individuals’ marital history.

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Notes

  1. For some additional examples of studies in this area, see also Fan and Zick (2006), Grafova (2007), Hatcher (2002), Lai (2008), Kim and DeVaney (2005), Meeks et al. (1999), O’Neill (2007), Spratlin and Holden (2000), and Su (2008) among many others.

  2. Indeed some recent studies such as Baek and Hong (2004), Beverly et al. (2003), Lee et al. (2007), and Wakita et al. (2000) considered the factors associated with asset accumulation and debt holding, and they noted the importance of life cycle stages and age effects in determining the levels of household savings and consumer debt.

  3. Some of the exceptions are Hurd (2002), Lupton and Smith (2003), and Wilmoth and Koso (2002 ).

  4. An alternative strategy to cross-sectional approach would be to employ panel data to investigate the relationship between marital shocks and changes in wealth holdings and asset allocation. The limited number of household dissolutions that have occurred during the sample period covered by the available waves of the HRS restricts us taking a step in this direction. Indeed, my preliminary analysis using the panel data with very few household disruptions provided only very week identifications, which were not very fruitful. Thus, I opted to use cross-sectional data from the first wave, which yielded interesting results. Although, the HRS is a panel data, remembering that population coverage is the adults who were between the ages of 51 and 61 in the first wave of the data, I suspect that marital disruptions such as divorce and separation mostly occur relatively earlier over the life cycle which is why we get limited number of observations in the HRS for disrupted households. The PSID, on the other hand, covers a longer horizon starting from 1968 and has many divorce cases, yet wealth is collected only in a few supplemental files. For some descriptive statistics regarding the distribution of marital transitions between the first and second waves of the HRS and the changes in wealth levels between the two waves conditional on those transitions, please see the Appendix at the end of the paper.

  5. Obviously, although in a short-run evaluation they may not matter much, in a longer horizon evaluation cohort effects might be significantly different which need to be taken into account when making general statements about the conclusions of the paper.

  6. Although the current study rather examines the relationship between household net worth and marital history, I would like to point that there is some recent research which looks at the differing roles of assets and consumer debt in marriage as well as the role of financial strain. For some examples, please see Chang and Lee (2006), Dew (2007), and Gudmunson et al. (2007 ).

  7. Kezdi and Willis (2003) showed that expectations are significant determinants of wealth holdings and portfolio allocation. Therefore, those variables were also included in the regressions presented in this paper. Information on inheritance expectations was drawn from the second wave of the HRS, because it had been collected beginning from that wave, and was unavailable in the first. In the HRS, each respondent was asked a question which involved four levels of risk taking behavior in terms of keeping the current family income safe. Depending on the answer the respondent’s risk aversion was classified as the least, 3rd most, 2nd most, and most. Mental health score took a value from 1 to 8 and measured the state of the respondent’s feelings. The higher the score, the more unhappy and depressed the respondent.

  8. A measure of permanent income, either at the individual or household level, would be appropriate to include in the regression. However, within the context of household dissolution, it is really not clear how to measure the permanent income in a sensible way. Nevertheless, the inclusion of current nominal household income as an additional independent variable only reduces the partial correlation of wealth and education, age and health status leaving the other results unaffected. Moreover, even though possibly endogenous, controlling for individuals’ current labor force participation also does not alter the substantive results of the present study.

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  1. School of Accounting, Economics and Finance, Deakin University, 221 Burwood Highway, Burwood, VIC, 3125, Australia

    Aydogan Ulker

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Appendix

Appendix

Table A1 indicates the distribution of marital transitions between the first and second waves of the HRS data. The total number of married and partnered individuals in the first wave of the HRS is 10,172. Of those married or partnered individuals only 121 had divorced or separated between the first two waves and only 96 had been widowed. 8,879 individuals, on the other hand, had stayed stably married or partnered until the second wave and 1,076 individuals were reported as missing due to nonresponse or death. In percentage terms, those who had been divorced or separated since the first wave of the data constitute only 1.1% of the overall population of 10,172 married or partnered individuals. This is clearly well below the divorce rate of an overall representative sample of the U.S. population and using this limited number of observations to make general statements about the link between marital transitions and wealth levels/portfolio allocation at the national level provides only weak identifications in which I would not have very much confidence. In addition to the issue of limited number of marital disruption observations, there is an issue of missing wealth or portfolio variables for some of those divorced or separated individuals in the second wave of the data which exacerbates the problem of the weak identification in a panel data approach. Looking at the marital transitions between the two waves by gender also yields similar percentage figures.

Table A1 Marital transitions between the first and second waves of the HRS
Full size table

Table A2 provides descriptive statistics for wealth levels conditional on marital transitions by using the observations with nonmissing values. In Table A2 please notice the noisy jump in the standard deviation of wealth (given the relative average wealth level) especially for those who divorced or separated between the first two waves of the HRS. I suspect this is mainly due to the limited number of observations problem mentioned above which might lead to inaccurate results. Given these informative tables, I did not go any further to look at the marital transitions and the portfolio allocations due to the overriding concern of keeping the paper focused and saving some space in terms of the length of the paper.

Table A2 Average wealth levels conditional on marital status changes between the first and second waves of the HRS
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Ulker, A. Wealth Holdings and Portfolio Allocation of the Elderly: The Role of Marital History. J Fam Econ Iss 30, 90–108 (2009). https://doi.org/10.1007/s10834-008-9139-2

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