Doctor of Philosophy / School of Family Studies and Human Services / Sonya L. Britt / This study explored whether the use of debt, specifically mortgages and student loans, has a negative relationship with wealth accumulation over a consumer’s lifetime. The analysis looked at whether exploration questioned whether consumer debt is incongruent with good personal financial management and consumers should hold a philosophy of avoidance of debt in order to accumulate more wealth. Some financial planners believe in leveraging current assets in hopes of accelerating wealth accumulation. The latter approach is more congruent with a behavioral life-cycle hypothesis perspective (Shefrin & Thaler, 1988), which posits that consumers are the happiest when consumption remains relatively constant over a lifetime through use of debt and savings. To account for wealth accumulation across the lifespan, a measure of relative net worth was constructed by taking current net worth divided by current annual income divided by age. Relative net worth was used rather than net worth in order to allow comparisons between consumers of different ages and income. Data were collected from a sample of convenience, recruited from social media, friends and their acquaintances, and the clients of financial advisors who agreed to distribute the survey. Four ordinary least squares (OLS) regression analyses were conducted to determine the influence of current mortgage relative to the value of the home, mortgage obtained at the time of home purchase as a multiple of income, and student loans at graduation as a multiple of income on relative net worth accumulations. Results suggested that current mortgage debt that is 80% or less of home value, lack of a mortgage, and completing higher education without student debt are associated with higher relative net worth. Using a sample of convenience, the respondent pool was not nationally representative. In comparison to the United States population, the sample population is more highly educated, has a higher percentage of married and individuals in a committed relationship, contains more adults over the age of 50, and does not reflect the ethnic diversity of the United States. This study did not provide deep new insight into the factors contributing to wealth accumulation. It showed that mortgages and student loans alone do not have a large impact on wealth accumulation. This is evidenced by the low R² for all regressions (ranging from .00 to .07). Of the independent variables chosen for regression, the impact was not large and statistical significance for those factors was not present in all regressions. The results of this study do not provide direct support to the ability to use mortgages and student loans as part of wealth accumulation strategies. Future studies may be able to incorporate other elements with debt decisions as well as the impact of financial advice on the use and levels of debt as part of an integrated wealth accumulation strategy. The level of debt to positively impact socioeconomic status is also another area for future study.

This paper analyses the process of wealth accumulation with regard to the path dependence theory. Based on the theoretical foundations of Robert King Merton, Vilfredo Pareto and Pierre Bourdieu, mechanisms of wealth accumulation are analyzed. These mechanisms, which are understood as direct and indirect network effects, are formalized using the statistical computing software R. A base model without any mechanisms of wealth accumulation is developed, which makes it possible to include the analyzed mechanisms step by step and observe their effects on the process of wealth accumulation and social inequality. Piketty's findings from his work Capital in the 21st Century are included in the formalized models of wealth accumulation, in particular the relationship between the rate of return on capital and the growth rate of the economy. (author's abstract)

Using data from the 2006 Health and Retirement Study (HRS), this study examines what types of assets and levels of savings are held by Black near-retirees, while comparing how types of assets and levels of savings of Black near-retirees differ from those of White near-retirees. Through the use of multivariate analyses, this study further investigates the effects of being Black on the levels of savings, the likelihood of holding IRAs, and the likelihood of being financially prepared for retirement. The study sample includes 4,077 individuals between the ages of 51 and 64, and the subsamples consist of 680 Black and 3,397 White near-retirees. Descriptive findings suggest that Black near-retirees hold lower levels of financial assets (i.e., checking accounts, CDs, stocks, bonds, and other savings) and non-financial assets (i.e., business, real estate, vehicles, and residential home) compared to their White counterparts. The descriptive results further indicate that overall, the level of net worth, holding IRAs, and the investment assets-to-net worth ratio for Black near-retirees are lower than that for White near-retirees. The results from both the ordinary least squares (OLS) regression and the logistic regression analyses indicate that with all else being equal, being Black is a significant factor in predicting the levels of savings, the likelihood of holding retirement accounts, and the likelihood of being financially prepared for retirement among near-retirees aged 51-64. This study also explores how human capital factors and socioeconomic factors are associated with the levels of savings among Black Americans aged 51-64. The OLS results suggest that Blacks with higher education and longer job tenure, and who are married hold higher levels of net worth than other Blacks. The logit results indicate that Black near-retirees with a college education are more likely to hold IRAs; those with longer job tenure are more likely to hold IRAs; and those in the top income quartile are more likely to hold IRAs. The findings of the logit results also indicate that Black near-retirees with some college education, longer job tenure, and those in the higher income groups are more likely to be financially prepared for retirement.

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