Chapter 7: Demographic and Socioeconomic Factors of Investors

Topic Covered Literature Review Studies on Gender Effects Studies on Race Effects Studies on the White-Male Effect Studies on the Role of Education The Role of Wealth and Income Case Study: The Florida Department of Education Employees

Literature Review Studies on Gender Effects The literature on gender differences in investor behavior typically indicates a significant difference in the way men and women invest, with women investing more conservatively than men. Bajtelsmit and Bernasek (1996) summarize the literature that explores risk-taking differences between men and women and attempt to reach a consensus on why men and women invest differently. They find that the differences in outcomes are primarily attributable to a few key underlying factors: differences in wealth, income, employment, discrimination, human capital choices, and preferences.

Cont. Agnew (2006) studies the role of gender and income in participant investment decisions.The study finds that men are more likely to own a higher percentage of company stock, which is generally considered a riskier strategy because of the lack of diversification with wage variability, and that women are more likely to participate in the 401(k) plan but that gender plays no role in using a 1/n strategy. To address the issue of education, Lusardi and Mitchell (2007a, 2007b, 2008) evaluate the responses of men and women to gauge the relationship among financial literacy, financial planning, and gender. Their study shows that women are less likely than men to be able to answer financial knowledge questions correctly and that a propensity to plan for retirement correlated with their ability to answer those questions.

Cont. On the other side of the gender argument, Croson and Gneezy (2009) summarize the research covering gender differences in investments and contend that women’s level of risk aversion pushes them to choose less risky portfolios. Drawing from psychology, the authors note that women report a more severe reaction to negative outcomes, leading to greater risk aversion, than men. By contrast, men are more likely to feel anger while women feel fear, making women less likely to take risky gambles. Sunden and Surette (1998) study gender differences in investment allocation decisions, controlling for household assets, marital status, and a risk aversion measure. They find that single men are more likely than single and married women to choose mostly stocks. Marital status has mixed results. When using gender/marital status interaction terms, married men are more risk-averse but when not using the interaction term, marriage does not have a significant effect.

Cont. Studies on Race Effects Blau and Graham (1990) study the accumulated wealth differences of young men and young women, they compare single and married black investors to single and married white investors. They find that measurable characteristics, including income, left more than 75 percent of the difference in accumulated wealth unexplained. Blau and Graham speculate that intergenerational transfers of financial knowledge and income uncertainty may best explain the difference in accumulated wealth. Intergenerational transfers refer to the passing down of knowledge and habits from one generation to the next. In this situation, income uncertainty refers to the proportion of income that is transitory rather than permanent. A higher level of income uncertainty provides an incentive for African American investors to invest more conservatively and save at higher rates than white investors

Cont. Chiteji and Stafford (1999) examine the intergenerational effects of stock allocation. They find that parents holding stocks are more likely to have children who hold stocks as young adults. Gittleman and Wolff (2004) explore this topic further, also using the PSID from 1984, 1989, and 1994 to study the racial differences in wealth accumulation. They report that both higher incomes and higher inheritances contribute to the gap between races.

Cont. Studies on the White-Male Effect To further study gender and racial differences, researchers also examine the “whitemale effect” to explore the socioeconomic differences between white males and all other groups. Flynn, Slovic, and Mertz (1994) find that factors such as trust, status, and power affect an individual’s perception of risk. Their evidence also shows that white males tend to differ from females and nonwhite males in their degree of risk perception and that this may be attributable to these sociopolitical factors. Palmer (2003) finds little connection between the white-male effect found in risk attitudes toward health, technology, and worldviews and risk attitudes toward investing. Her results show no persistent difference in attitudes toward risky investing strategies between white males and all other investors but some difference in attitudes appear toward blue-chip stocks.

Cont. Studies on the Role of Education Many studies focusing on gender and race acknowledge the importance of including a measure of investor education. Grable and Lytton highlight the role of financial education in determining risk taking, with the more financially educated participants more likely to take risk.

Cont. The Role of Wealth and Income Some studies control for the effects of income on investor behavior. For example, Agnew (2006) finds that higher income leads to fewer behavioral biases, with higher income participants holding lower shares of company stock, as well as being less likely to follow a 1/n diversification strategy and more likely to participate in retirement plans. Hinz et al. (1997) find that income could explain some of the allocation differences found across gender, with higher income investors taking on more risk.

Cont. According to life cycle theory, investors should make decisions based not only on their investable wealth but also their expected income stream. This theory suggests that remaining working years, income (both the level and risk), and the level of wealth all play an important role in determining investment risk.

Case Study: The Florida Department of Education Employees