Economic Mobility and Income Inequality

Marriage and college degrees as a path out of poverty.

Posted Nov 12, 2018

Poverty has been shown to have a variety of psychological detriments to an individual. For example, it has been cited as a risk factor for mental, emotional, and behavioral disorders in children and youth (Yoshikawa, Aber, & Beardslee, 2012). To assist in formulating effective policies and programs to reduce poverty in the United States, psychological scientists must identify the characteristics of poverty and economic mobility. By doing so, psychological scientists can help some individuals find a pathway out of poverty.

In reviewing the 2017 Census report (Fontenot, Semega, & Kollar, 2018) I have noted a few findings. The categories described here use the labels of the census. The 2017 report uses the formula of the Office of Management and Budget for calculating poverty. A few examples of the poverty threshold for households: One person under the age of 65 years ($12,752), two people under the age of 65 years with no children in the house ($16,414), four people total with two related children under 18 years ($24,858). A few interesting findings are:

  • The large discrepancy in earnings between men and women (female-to-male earnings ratio of .805 for working full-time, year-round median earnings.) (Figure 3 of Fontenot et al).
  • The very high rate of poverty among Blacks (21.2 percent), Hispanics (18.3 percent), foreign-born not a citizen (18.6 percent), disabled (24.9 percent), and those without a high school diploma (24.5 percent) (Table 3 of Fontenot et al).
  • The very high rate of poverty among female-headed households with no husband present (25.7 percent), with no husband present and with related children under age of 6 (48.4 percent), and with no husband present and with related children under age of 18 (40.8 percent) (Table 4 of Fontenot et al.).

Taken together, these data identify demographics at the most risk for poverty. Reducing poverty requires more than simply identifying characteristics of those in poverty. It also requires a clear look at those who are not in poverty and an examination of trends that suggest a path out.

One valuable perspective on mobility across economic segments comes from examining households as the unit of analysis. In his review of the Fontenot et al. data, Mark Perry (2018) examined demographic differences for income inequality by household. The composition of a household comes in many forms of people aggregated together. Dividing income ranges into quintiles (average income for the lowest fifth = $12,319, second fifth = $35,874, middle fifth = $62,331, fourth fifth = $102,183, highest fifth = $221,846), Perry found that the average number of earners per household increased across each quintile, with 63 percent of the households in the bottom quintile having no earners. Married-couple households made up 76.1 percent of the top quintile and single parent or single households made up 82.9 percent of the bottom quintile. The proportion of married-couple households increased for each quintile. For age, the oldest (65 years and older) and youngest (under 35 years) were disproportionately represented in the lowest quintile relative to the other quintiles. Additionally, the top quintile had a much higher number of college degrees than the bottom quintile. Thus, marriage was negatively related to poverty, college degrees were negatively related to poverty, and prime earning age of 35-64 years old was negatively related to poverty. But how rigid is a person’s economic status?

In the United States, there is considerable income mobility (U.S. Department of the Treasury, 2007; Sowell, 2014; Larrimore, Mortenson, & Splinter, 2015). In studies by the U.S. Department of the Treasury that follow individual taxpayers over time, there is evidence that the people at any given time in an income quintile are not the same as the people in that quintile at a different point in time. For instance, between 1996 and 2005, 56 percent of taxpayers moved income quintiles and around 50 percent of those in the bottom quintile in 1996 moved to a higher quintile by 2005. The study also demonstrated that income mobility was the same for 1987-1996 as for 1996-2005. Data from 1999-2011 (Larrimore et al., 2015) support the same trends for income mobility, adding that marriage improved income mobility for men more than women, and divorce decreased income mobility for men more than women. Though marriage provided benefits against poverty for both men and women, it did not provide the same level of benefits against poverty for women as for men.

What about the high end of income? According to the U.S. Department of the Treasury data, there is a great deal of economic movement up and down at the highest level. Of the top .01 percent of income, 75 percent of those in the category in 1996 were out of the category by 2005, and 6 percent dropped out of the top quintile. Fifty-nine percent of those in the top .01 percent had declines in income of over 50 percent during this time period.

Together, these findings highlight: 1) who is most at risk for poverty, and 2) who may most need assistance in identifying a path out of poverty. This helps psychologists in identifying which characteristics or behaviors are controllable by an individual. For instance, parental coordination is useful for parents with children, so two parents have an advantage over one (Surbey, 1998; Mather, 2018) in that they can share parental care duties. By identifying the changeable characteristics, we can begin to better inform policies to combat poverty by empowering some individuals in poverty.

Given the 2017 census data, a married couple with at least one college degree has advantages in distancing themselves from poverty. Interestingly, those are two demographics that are under an individual’s control in climbing out of poverty: a college education and a stable marriage. Taking advantage of federal student loan programs and teaming up with (and sticking with) another individual goes a long way towards upward economic mobility. The census data do not speak to the rankings of the colleges on this advantage. Thus, degrees from affordable public colleges or universities equip individuals to better escape poverty.

College degrees are good for combatting poverty, marriages are good for combatting poverty, divorce and separation are fuel for poverty. The census data categories in those reports speak only to heterosexual marriages. Given the logic of the shared duties/multi-earner advantages for income mobility, there is no reason to believe that other types of marriages would not see the same benefits of economic mobility.

What about the psychology of poverty? An individual’s expectation that his or her actions do not affect their environment is called learned helplessness. Related to learned helplessness is a person’s explanatory style, which is how a person explains their successes and failures. The three dimensions of explanatory style are permanence (permanent or temporary), pervasiveness (universal or specific), and personalization (my fault or someone else’s).  A person’s explanatory style dictates their level of optimism or pessimism, and optimism predicts success for life insurance salespeople, West Point recruits, collegiate and Olympian swimmers, Presidential candidates, Major League baseball teams, and health for Harvard undergraduates over the course of their lifetimes. Learned helplessness (but not really optimism, because rats don’t tend to be optimistic…) also predicts whether or not a rat can successfully fight off a cancerous tumor (Seligman, 1990; Mather & Romo, 2007). Breaking a cycle of learned helplessness is essential to escaping poverty.

Psychologists will disagree with the implications of these data for decreasing poverty. Should programs focus on changing the ideal selves (Higgins, 1987) for those in poverty to include seeing oneself as a college graduate? Should programs include a focus on increasing resilience (Britt et al., 2016) so that individuals can overcome the social pressures a first-generation college student may encounter when their support system does not see the same value in their higher education pursuits? Whatever the next step is, climbing out of poverty is tough but possible for many, as indicated by these data. Conservatives and liberals will disagree over the solutions to these problems, but the data clearly identify the characteristics of poverty and economic mobility within the United States. Psychological scientists must better contribute to informing the search for effective policies and programs to combat poverty in the United States.

Don’t misconstrue this article as an argument that poverty is a choice. But if there is a choice for some individuals to escape poverty, it is our duty to help those individuals in whatever way we can to make that choice and equip them to follow through on executing the plan. Poverty is complicated and reading this article will not give you a feel for what it is like to truly experience poverty. The uncertainty of food, employment, and personal debt affect real people in real ways. But if we fail to initiate meaningful conversations about the issue of poverty in the United States, then we fail our obligation to help others.

References

Britt, T. W., Shen, W., Sinclair, R. R., Grossman, M. R., Kleiger, D. M. (2016). How much do we really know about employee resilience? Industrial and Organizational Psychology, 9, 378-404.

Fontenot, K., Semega, J., & Kollar, M. (2018, September). Income and Poverty in the United States: 2017. Washington, DC: U.S. Census Bureau.

Higgins, E. T. (1987). Self-discrepancy: A theory relating self and affect. Psychological Review, 94, 319-340.

Larrimore, J., Mortenson, J., & Splinter, D. (2015). “Income and earnings mobility in U.S. tax data,” Finance and Economic Discussions Series 2015-061. Washington, DC: Board of Governors of the Federal Reserve System.

Mather, R. D. (2018, October 11). Dove baby parents and the Sunday Night Massacre. Psychology Today (online).

Mather, R. D., & Romo, A. (2007). Automaticity and cognitive control in social behavior. Southlake, TX: Fountainhead.

Perry, M. J. (2018, September 13). Explaining US income inequality by household demographics, 2017 update. AEIdeas.

Seligman, M. E. P. (1990). Learned optimism. New York: A. A. Knopf.

Sowell, T. (2014, January 21). Inequality fallacies. National Review (online).

Surbey, M. K. (1998). Developmental psychology and modern Darwinism. In C. Crawford and D. L. Krebs (Eds.). Handbook of evolutionary psychology: Ideas, issues, and applications (pp. 369-403). Mahwah, NJ: Lawrence Erlbaum.

United States Department of the Treasury (2007, November 13). Income mobility in the U.S. from 1996-2005. United States Department of the Treasury.

Yoshikawa, H., Aber, J. L., & Beardslee, W. R. (2012). The effects of poverty on the mental, emotional, and behavioral health of children and youth. American Psychologist, 67, 272-284.