As Reeves and Sawhill note, there are many ways to measure mobility: should we focus on equality of opportunity or outcomes? "Is the main concern with absolute mobility (how people fare compared to their parents)--or with relative mobility (how people fare with regard to their peers)? Is the right metric for mobility earnings, income, education, or wellbeing, or some other yardstick? Is the primary concern with upward mobility from the bottom or with mobility across the spectrum?" For the purpose of this paper, Reeves and Sawhill are primarily interested in relative intergenerational income mobility (RIIM).
Evidence from the research literature indicates that the U.S. has fairly low rates of RIIM, and that there are strong geographical, racial, educational, and to a lesser extent, gender, patterns to RIIM. Reeves and Sawhill's findings confirm these results. The social mobility transition matrices they constructed based on their data show that "the U.S. suffers from a high degree of intergenerational income 'stickiness,' especially at the top and bottom of the income distribution."
Ideally, in a society with "perfect" mobility, children born to disadvantaged parents (in the lowest quintile of the parent income distribution) would be as likely to end up in the lowest quintile of the child income distribution as they are to end up in any other quintile. In reality, Reeves and Sawhill show:
- "children born to families at the bottom of the income distribution (i.e. whose parents' income falls in the bottom quintile) have a 36 percent probability of remaining stuck there in adulthood [...] and children on the opposite end of the spectrum have a 30 percent chance of remaining in the highest income quintile."
- "Black children face pervasive downward pressure towards the bottom of the income distribution, regardless of parent income [...] Half the black children born into the bottom quintile remain there in adulthood [...] Only 3 percent join the top income quintile. Moreover black children with middle-class roots are more likely to fall than to rise."
- All children receive a boost in RIIM from getting a college degree, even top income children. The reverse is not true, however, of failing to receive a high school diploma: dropping out damages mobility rates for bottom- and middle-income quintiles, but not for children born to top-income quintile parents. In this group, almost as many remain on the top rung as fall to the bottom. In other words, as Matt O'Brien of the Washington Post's Wonkblog put it: "poor kids who do everything right don't do much better than rich kids who do everything wrong."
- Success begets further success: the "head start" that children get from being born advantaged propulses them through all stages of life.
These patterns, Reeves and Sawhill argue, are alarming in light of the fact that income inequality has been rising in recent decades: "when the rungs of the ladder are far apart, it becomes more difficult to climb the ladder ... Inequality in one generation may mean less opportunity for the next generation to get ahead and thus still more inequality in the future." They continue: "There is a moral justification for a society with high inequality offset by high mobility, grounded in liberal ideas of freedom and fairness, and a moral justification for a society with low mobility, softened by low inequality, based on left-of-center egalitarian ideals. But there is little justification for a society with a large gap between rich and poor, and little movement between the two."
More encouraging findings from their analyses suggest that targeted interventions, such as preschool programs, could do a great deal to close the gap in the lifetime incomes between children born into lower and higher income families.
Income Inequality in the US (http://www.teachingwithdata.org/resource/3182)
An Analysis of Earnings (http://www.teachingwithdata.org/resource/3159)
NYT Interactive: What Percent Are You? (http://www.teachingwithdata.org/resource/3913)
Social Class and Attitudes about Inequality: A Data-Driven Learning Guide (http://www.teachingwithdata.org/resource/3459)
Income Differences (http://www.teachingwithdata.org/resource/3113)