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Recent Trends in Intergenerational Mobility † American Economic Review: Papers & Proceedings 2014, 104(5): 141–147 http://dx.doi.org/10.1257/aer.104.5.141 BIG DATA IN MACROECONOMICS: NEW INSIGHTS FROM LARGE ADMINISTRATIVE DATASETS Is the United States Still a Land of Opportunity? Recent Trends in Intergenerational Mobility † By Raj Chetty, Nathaniel Hendren, Patrick Kline, Emmanuel Saez, and Nicholas Turner* There is a growing public perception that reaching the top quintile of the income distri- intergenerational income mobility—a child’s bution starting from the bottom quintile. Based chance of moving up in the income distribution on all of these measures, we find that children relative to her parents—is declining in the United entering the labor market today have the same States. We present new evidence on trends in chances of moving up in the income distribution intergenerational mobility using administrative relative to their parents as children born in the earnings records for children born between 1971 1970s.( ) and 1993. For the 1971–1986 birth cohorts, we Although these rank-based measures of measure intergenerational mobility based on the mobility have remained stable, income inequal- correlation between parent and child income ity increased over time in our sample, consistent percentile ranks. For more recent cohorts, we with prior work. Hence, the consequences of the measure mobility as the correlation between a “birth lottery”—the parents to whom a child is child’s probability of attending college and her born—are larger today than in the past. A useful parents’ income rank. We also calculate transi- visual analogy is to envision the income distribu- tion probabilities, such as a child’s chances of tion as a ladder, with each percentile represent- ing a different rung. The rungs of the ladder have grown further apart inequality has increased , * Chetty: Harvard University, Littauer Center 226, ( ) Cambridge, MA 02138 e-mail: [email protected] ; but children’s chances of climbing from lower ( ) to higher rungs have not changed rank-based Hendren: Harvard University, Littauer Center 235, Cam- ( bridge, MA 02138 e-mail: [email protected] ; mobility has remained stable . ( ) Kline: University of California, Berkeley, 631D Evans This paper is an abbreviated) version of NBER Hall, CA 94720, e-mail: [email protected] ; working paper 19844 Chetty et al. 2014b . Saez: University of California,( Berkeley, 530 Evans Hall,) ( ) CA 94720 e-mail: [email protected] ; Turner: The working paper contains a complete descrip- US Treasury,( 1500 Pennsylvania Ave, Room) 1222A, tion of the data, additional empirical results, and Washington, DC 20220 e-mail: nicholas.turner@treasury. ( further discussion of the findings in the context gov . The views expressed in this paper are those of the of the prior literature. authors) and do not necessarily represent the views or poli- cies of the US Treasury Department or the Internal Revenue Service. We thank Sarah Abraham, Alex Bell, Alex Olssen, I. Measuring Intergenerational Mobility: and Evan Storms for outstanding research assistance. Conceptual Issues We thank David Autor, Greg Duncan, Lawrence Katz, Alan Krueger, Richard Murnane, Gary Solon, and numerous We decompose the joint distribution of parent seminar participants for helpful comments. Financial sup- and child income into two components: i the port from the Lab for Economic Applications and Policy at ( ) Harvard, the Center for Equitable Growth at UC Berkeley, joint distribution of parent and child ranks, for- and the National Science Foundation is gratefully acknowl- mally known as the copula of the distribution, edged. The statistics reported in this paper can be down- and ii the marginal distributions of parent and loaded from www.equality-of-opportunity.org. ( ) † Go to http://dx.doi.org/10.1257/aer.104.5.141 to visit child income. The marginal distributions deter- the article page for additional materials and author disclo- mine the degree of inequality within each gen- sure statement s . eration, typically measured by Gini coefficients ( ) 141 142 AEA PAPERS AND PROCEEDINGS MAY 2014 or top income shares. The copula is a key deter- of children in each birth cohort to parents based minant of mobility across generations. Some on dependent claiming, obtaining a sample with commonly used measures of mobility—such 3.7 million children per cohort online Appendix as correlations between parent and child per- Table 1, column 4 . ( centile ranks and quintile transition matrices— To obtain data on) earlier birth cohorts, we use depend purely on the copula. Other measures, the Statistics of Income SOI annual cross sec- such as the log-log intergenerational elasticity of tions since 1987, the earliest( ) year with depen- income, combine features of the marginal distri- dent information Auten, Gee, and Turner 2013 . butions and the copula. These cross sections( are stratified random sam)- We characterize changes in the copula and ples covering approximately 0.1 percent of tax marginal distributions of income separately to returns. Using the SOI cross sections, we con- distinguish changes in inequality from inter- struct a sample of children in the 1971–1982 generational mobility. We find that the copula birth cohorts, which we refer to as the SOI sam- has not changed over time: children’s chances ple. We construct this sample by first identifying of moving up or down in the income distribu- children between the ages of 12 and 16 claimed tion have remained stable. However, the mar- as dependents in the 1987–1998 SOI cross sec- ginal distributions of income have widened tions and then pooling all the SOI cross sections substantially. that contain information for a given birth cohort. Together, these two facts can be used Using the sampling weights, we estimate that the to construct various measures of mobility. SOI sample represents 88 percent of children in For example, if one defines mobility based on each birth cohort based on vital statistics counts, relative positions in the income distribution— with slightly lower coverage rates in the earliest e.g., a child’s prospects of rising from the bot- cohorts online Appendix Table 1, column 3 . tom to the top quintile—then intergenerational Summary( statistics for the SOI sample using) mobility has remained unchanged in recent sampling weights and the population-based( decades. If instead one defines mobility based sample are very similar) for the overlapping 1980– on the probability that a child from a low-income 1982 birth cohorts online Appendix Table 2 . family e.g., the bottom 20 percent reaches a ( ) fixed upper-income( threshold e.g., )$100,000 , Variable Definitions.—We define parent fam- then mobility has increased (because of the) ily income in real 2012 dollars as adjusted increase in inequality. However, the increase gross income( plus tax exempt interest) and the in inequality has also magnified the difference nontaxable portion of social security benefits in expected incomes between children born to for those who file tax returns. For nonfilers, low- e.g., bottom-quintile versus high- we define income as the sum of wage earn- top-quintile( income families.) In this sense, ings form W-2 , unemployment benefits form mobility( has) fallen because a child’s income 1099-G( , and social) security and disability( ben- depends more heavily on her parents’ position efits form) SSA-1099 . In years where parents in the income distribution today than in the past. have (no tax return and) no information returns, Since the appropriate definition of intergen- family income is coded as zero. erational mobility depends upon one’s norma- In the population-based sample, we define tive objective, we characterize the copula and parent income as mean family income over marginal distributions separately in this paper. the 5 years when the child is 15–19 years old. In the SOI sample, parent income is observed II. Data only in the year that the child is linked to the parent, and therefore we define parent income as Sample Construction.—For children born family income in that year. In both samples, we during or after 1980, we construct a linked drop observations with zero or negative parent parent-child sample using population tax records income. spanning 1996–2012. This population-based We define child family income in the same sample consists of all individuals born between way as parent income, always using data from 1980–1993 who are US citizens as of 2013 and the population files. We define a child’s college are claimed as a dependent on a tax return filed in attendance as an indicator for having a 1098-T or after 1996. We link approximately 95 percent form in the calendar year the child turns 19. VOL. 104 NO. 5 TRENDS IN INTERGENERATIONAL MOBILITY 143 70 ple: 1971–1974, 1975–1978, and 1979–1982. 1971–74 1975–78 To reduce noise, we divide parent income ranks 60 1979–82 into 50 rather than 100 bins and plot the mean child rank( versus the mean) parent rank within 50 each bin. The rank-rank relationship is almost perfectly linear. Its slope can be interpreted as 71–74 Slope 0.299 = 0.009 40 ( ) the difference in the mean percentile rank of 75–78 Slope 0.291 = 0.007 ( ) children from the richest families versus chil- 79–82 Slope 0.313 = Mean child income rank 0.008 ( ) dren from the poorest families. The rank-rank 30 0 20 40 60 80 100 slopes for the three sets of cohorts in Figure 1 Parent income rank estimated using OLS on the binned data are all( approximately 0.30, with standard errors) Figure 1. Child Income Rank versus Parent Income less than 0.01. In the working paper version, we Rank by Birth Cohort show that these rank-rank slope estimates are Notes: The figure plots the mean percentile income rank robust to measuring parent and child income at of children at ages 29–30 y-axis versus the percentile different ages and using multiple years to mea- rank of their parents x-axis( for three) groups of cohorts ( ) sure income, indicating that the estimates do not 1971–1974, 1975–1978, and 1979–1982 in the SOI sam- suffer from significant life cycle or attenuation ple.( The figure is constructed by binning) parent rank into 2-percentile point bins so that there are 50 equal-width bias.
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