What does race have to do with mobility? The words “race,” “black,” or “African American” don’t appear in David Leonhardt’s report on the new Chetty et al. paper on intergenerational mobility that hit the news yesterday. Or in Jim Tankersley’s report in the Washington Post, which is amazing, because it included this figure: That’s not exactly a map of Black America, which the Census Bureau has produced, but it’s not that far off:
But even if you don’t look at the map, what if you read the paper? Describing the series of maps of intergenerational mobility, the authors write:
Perhaps the most obvious pattern from the maps in Figure VI is that intergenerational mobility is lower in areas with larger African-American populations, such as the Southeast. … Figure IXa confirms that areas with larger African-American populations do in fact have substantially lower rates of upward mobility. The correlation between upward mobility and fraction black is -0.585. In areas that have small black populations, children born to parents at the 25th percentile can expect to reach the median of the national income distribution on average (y25;c = 50); in areas with
large African-American populations, y25;c is only 35.
Here is that Figure IXa, which plots Black population composition and mobility levels for groups of commuting zones: Yes, race is an important part of the story. In a nice part of the paper, the authors test whether Black population size is related to upward mobility for Whites (or, people in zip codes that are probably White, since race isn’t in their tax records), and find that it is. It’s not just Blacks driving the effect. I’m thinking about the historical patterns of industrial development, land ownership, the backwardness of racist elites in the South, and so on. But they’re not. For some reason, not explained at all, Chetty et al. offer this pivot:
The main lesson of the analysis in this section is that both blacks and whites living in areas with large African-American populations have lower rates of upward income mobility. One potential mechanism for this pattern is the historical legacy of greater segregation in areas with more blacks. Such segregation could potentially affect both low-income whites and blacks, as racial segregation is often associated with income segregation. We turn to the relationship between segregation and upward mobility in the next section.
And that’s it, they don’t discuss Black population size again, instead only focusing on racial segregation. They don’t pursue this “potential mechanism” in the analysis that follows. Instead, they drop percent Black for racial segregation. I have no idea why, especially considering this Table VII, which shows unadjusted (and normalized) correlations (more or less) between each variable and absolute upward mobility (the variable mapped above):
In these normalized correlations, fraction Black has a stronger relationship to mobility than racial segregation or economic segregation! In fact, it’s just about the strongest relationship on the whole long table (except for single mothers, with which it is of course highly correlated). So why do they not use it in their main models? Maybe someone else can explain this to me. (Full disclosure, my whole dissertation was about this variable.)
This is especially unfortunate because they do an analysis of the association between commuting zone family structure (using macro-level variables) and individual-level mobility, controlling for marital status — but not race — at the individual level. From this they conclude, “Children of married parents also have higher rates of upward mobility if they live in communities with fewer single parents.” I am quite suspicious that this effect is inflated by the omission of race at either level. So they write the following, which goes way beyond what they can find in the data:
Hence, family structure correlates with upward mobility not just at the individual level but also at the community level, perhaps because the stability of the social environment affects children’s outcomes more broadly.
Or maybe, race.
I explored the percent Black versus single mother question in a post a few weeks ago using the Chetty et al. data. I did two very simple OLS regression models using only the 100 largest commuting zones, weighted for population size, the first with just single motherhood, and then a model with proportion Black added: This shows that the association between single motherhood rates and immobility is reduced by two-thirds, and is no longer significant at conventional levels, when percent Black is added to the model. That is: Percent Black statistically explains the relationship between single motherhood and intergenerational immobility across U.S. labor markets. That’s not an analysis, it’s just an argument for keeping percent Black in the more complex models. Substantively, the level of racial segregation is just one part of the complex race story — it measures one kind of inequality in a local area, but not the amount of Black, which matters a lot (I won’t go into it all, but here are three old papers: one, two, three.
The burgeoning elite conversation about economic mobility, poverty, and inequality is good news. It’s avoidance of race is not.
23 thoughts on “Where is race in the Chetty et al. mobility paper?”
Nice follow up to the cited paper and newspaper column. Seems the authors were blind to the fact you raise about “the historical patterns of industrial development, land ownership, the backwardness of racist elites in the South.” We address the critical issues of SEGREGATION and lack of mobility for Blacks in two papers:
Angela Hattery and Earl Smith, E. (2007). “Social Stratification in the New/Old South: The Influences of Racial Segregation on Social Class in the Deep South.” Journal of Poverty Research 11(1), 55-81.
Earl Smith and Angela J. Hattery. (2010). “Cultural Contradictions in the South.” Mississippi Quarterly Vol 63 (2): 145-166.
Since social mobility is closely related to educational attainment it is no surprise it is lower for African-Americans.
The topic of this blog is a favorite of mine, decomposing results based on segregated populations, and I am glad you addressed this. I have two comments:
1.Upward mobility, Y25, is a complex number. It is the median percentile, in the national income distribution, of a child whose family, at birth, stood at 25th percentile of income distribution See http://www.equality-of-opportunity.org/index.php/faq-s, and details: http://www.equality-of-opportunity.org/files/mobility_trends.pdf
This data is specific to poor parents. The y-axis numbers, typically in the 35-50% range, actually show a pretty decent social mobility across the board – it looks like more than half of these born-poor kids achieve middle class income no matter the place they lived. So, many of the conclusions made by the authors, have to be understood with this caveat, i.e., 35-50 is not improvement to one percenter territory, but it is not the same as getting worse. The way the curve is plotted, I cannot predict waht happens when the percentage black is > 50, buu I guess Y25 is < 35, but I dont know how much.
2. What is rich is Dr.Cohen chastising Chetty for not looking at percentage black, but with 1964 glasses on, he skips over the larger minority. The biggest minority in the US is Hispanic with 17% of the population, but 22-25% of the children. The impact of segregation on Hispanic mobility can be easily identified by a trip to South texas, East LA, or locally to Takoma Park. What I am saying is that we need to decompose these results to at least three populations, and plot against percentage of each group. And that is the crux of the weakness of most soci-economic analyses showen here; the lack of details by population.
You’re right about Latinos but miss the point for this analysis: the problem with not having Black in there at the individual or community level is that it is so strongly correlated with single-parent families. So, in my view, I suspect that racial inequality (lots of mechanisms) causes single-parent families, which affects social mobility. And when you leave race out you inflate the effect of single-parent families.
I think you are taking my criticism too much to your heart. I am only supporting what you are saying by mentioning that if you add Latino percentages and unmarried latino mothers to your analysis, you will reduce the association between single motherhood rates and immobility even further.
https://familyinequality.wordpress.com/2013/12/30/inequality-mobility-single-mothers-race/ was an important contribution; i could not do the same because I could not find the race percentages by “Commuting zone” (What the hell is that? How did he get results by commuting Zone). However, noting that the birth to latino mothers has attained 53% in the 2000s, and that more Latino children (911,000 vs 583000 black children) your analysis will be strengthened.
No way is that correlation in Figure IXAa as low as -.585. Something’s wrong there…
Ya, that’s odd. Maybe the bins look more correlated, but they calculated the correlation off the full data, which is messier? Still.
It’s Galton 101: The black income mean in lower than the white income mean, so blacks in the bottom quintile regress toward a lower mean than whites in the bottom quintile.
Basic regression toward the mean explains why this map looks like a college football recruiting map of where the best high school cornerbacks are found.
Here’s a lengthy critique of Chetty citing Dr. Cohen’s insight: