STATE OF STATES head 55 Economic Mobility The Stanford Center on Poverty and Inequality BY RAJ CHETTY, NATHANIEL HENDREN, PATRICK KLINE, AND EMMANUEL SAEZ he United States is often hailed as the 1, we find that this rank-rank relationship is KEY FINDINGS T “land of opportunity,” a society in which almost perfectly linear, with a slope of 0.34. • There is less intergenera- a child’s chances of success depend little This implies that children growing up in the tional mobility in the united on her family background. Is this reputation highest-income families rank, on average, 34 states than is sometimes warranted? And is it especially warranted in percentiles higher than children growing up in appreciated by the public, some states, regions, or areas of the United the poorest families. but intergenerational mobility States? is not declining. When poor Contrary to popular perception, we find children born in 1971 and 1986 are compared, one finds There is a growing public perception that that such percentile rank–based measures a slight increase (from 8.4 to intergenerational income mobility—a child’s of intergenerational mobility have remained 9.0 percent) in the chances of chance of moving up in the income distribu- extremely stable for the 1971–1993 birth reaching the top fifth of the tion relative to her parents—is declining in cohorts. For example, the probability that a income distribution by age 28. the United States. Is it really true that oppor- child reaches the top fifth of the income dis- • There is substantial variation tunity has declined? tribution given parents in the bottom fifth is within the united states in the 8.4 percent for children born in 1971, com- prospects for escaping pov- In two recent papers, we address these ques- pared with 9.0 percent for those born in 1986. erty. In the highest-mobility areas of the united states, tions by compiling statistics from millions of Children born to the highest-income families mobility rates are higher than anonymous income records.1 These data in 1984 were 74.5 percentage points more rates in most other developed have less measurement error and much larger likely to attend college than those from the countries, and more than 1 in sample sizes than previous survey-based lowest-income families. The corresponding 10 children with parents in the studies and thus yield more precise estimates gap for children born in 1993 is 69.2 per- bottom quintile of the income distribution reach the top of intergenerational mobility across cities and centage points, suggesting that, if anything, quintile by adulthood. poor states over time. Our core sample consists of mobility may have increased slightly in recent children in western states all children in the United States born between cohorts. have the best chances of 1980–1982, whose income we measure in making it to the top. 2011–2012, when they are approximately Figure 2 illustrates the stability of intergenera- • In the lowest-mobility areas of 30 years old. We divide our analysis into tional mobility for children born between 1971 the united states, which tend two parts: an analysis of time trends and an and 1993 (where, for children born after 1986, to be in the south, fewer than analysis of geographical variation in mobility estimates are predictions based on college 1 in 20 poor children reach across areas of the United States. attendance rates). The y-axis, “intergenera- the top quintile, a rate that is lower than in any developed tional persistence,” is a measure of the gap country for which data have Time Trends in average income percentiles for children been analyzed to date. We find that the most robust way to measure born in the poorest versus richest families. On • Mobility rates are relatively intergenerational mobility is by ranking par- average, children with parents in the bottom 1 low in areas with high income ents by parental income (at the time the child percent of the income distribution grow up to and racial segregation. Mobil- was growing up in the family) and by ranking earn an income approximately 30 percentiles ity rates are relatively high in children by their income when they are adults. lower than their peers with parents in the top areas with high school quality, For each percentile of parent’s income, we 1 percent of the income distribution. This dif- local tax rates, social capital, and marriage rates. compute the average rank of the income of ference has remained relatively steady across the children when adults. As shown in Figure the birth cohorts we studied. Pathways • The Poverty and Inequality Report 2015 56 economic mobility Although rank-based measures of mobility remained stable, between the 1950 and 1970 birth cohorts, we conclude that income inequality increased substantially over the period we rank-based measures of social mobility have remained stable study. Hence, the consequences of the “birth lottery”—the over the second half of the 20th century in the United States.4 parents to whom a child is born—are larger today than in the past. A useful visual analogy (depicted in Figure 3) is to envi- Variation within the United States sion the income distribution as a ladder, with each percentile Intergenerational mobility, on average, is significantly lower representing a different rung. The rungs of the ladder have in the United States than in most other developed countries.5 grown farther apart (inequality has increased), but children’s However, mobility varies widely within the United States, and chances of climbing from lower to higher rungs have not we now turn to examine this regional and state variability. changed (rank-based mobility has remained stable). We begin by constructing measures of relative and abso- lute mobility for 741 “commuting zones” (CZs) in the United This result may be surprising in light of the well-known cross- States. Commuting zones are geographical aggregations of country relationship between inequality and mobility, termed counties that are similar to metro areas but also cover rural the “Great Gatsby Curve” by Alan Krueger.2 However, much areas. Children are assigned to a CZ based on their location of the increase in inequality has come from the extreme upper at age 16 (no matter where they live as adults), so that their tail (e.g., the top 1 percent) in recent decades, and top 1 per- location represents where they grew up. When analyzing local cent income shares are not strongly associated with mobility area variation, we rank both children and parents based on across countries or across metro areas within the United their positions in the national income distribution. Hence, our States.3 statistics measure how well children fare relative to those in the nation as a whole rather than to those in their own par- Putting together our results with other recent evidence ticular community. that intergenerational mobility did not change significantly FIGURE 1. Intergenerational Mobility in the United States FIGURE 2. Trends in Intergenerational Mobility in the United States 60070 800.6 70 E 50060 C K TEN S 60 I S 0.4 E RAN 400 M 50 PER O 50 L C D IN , 2010$ , 2010$ L I 300 40 S 40 S CH 1000 1000 0.2 EAN 30 M 200 30 INTERGENERATIONA 20 100 Rank-Rank Slope=0.341 (0.0003) 20 100 0 10 20 30 40 50 60 70 80 90 100 1971 1974 1977 1980 1983 1986 1989 1992 0 0 1983 1989 1992 1995PARENT1998 INCOME 2001RANK 2004 2007 2010 1983 1989 1992 1995CHILd’S1998 BIRTH CO2001HORT 2004 2007 2010 Note: The figure presents a non-parametric binned scatter plot of the Note: The series in solid circles (through cohort 1982) plots estimates from relationshipMedian Net between Worth child andMean parent Net incomeWorth ranks. Both figures are based on OLSMedian regressions Income of childMean income Income rank at age 29–30 on parent income rank, a population sample of the 1980–1982 birth cohorts and baseline family income estimated separately for each birth cohort from 1971–1982. The series in open definitions for parents and children. Child income is the mean of 2011–2012 circles represents a forecast of intergenerational mobility based on income at family income (when the child was around 30), while parent income is mean age 26 for the 1983–1986 cohorts and college attendance for the 1987–1993 family income from 1996–2000. We define a child’s rank as her family income cohorts; for details, see Chetty et al., 2014b. percentile rank relative to other children in her birth cohort and his parents’ rank as their family income percentile rank relative to other parents of children in the core sample. The slopes and best-fit lines are estimated using an OLS regression on the micro data. Standard errors are reported in parentheses. Source: Chetty et al., 2014a. Source: Chetty et al., 2014b. Pathways • The Poverty and Inequality Report 2015 economic mobility 57 We begin this spatial analysis by aggregating CZs up to the But mobility is not strictly a regional and subregional affair. level of states and then grouping states according to their There is also much variation across states that are in close Census region. In Figure 4, the bar for each state pertains to geographic proximity and have similar socio-demographic the probability that a child with parents in the bottom fifth of characteristics. For example, North Dakota has the high- the income distribution reaches the top fifth of the income est mobility in the country (children in the bottom fifth have distribution (in adulthood). an 18.9% chance of reaching the top fifth), whereas South Dakota has much less mobility (a corresponding statistic of The variation between regions is notable.