By Steve Sailer
02/03/2016
Economist Raj Chetty, now at Stanford, has a new paper out based on his giant data trove of IRS 1040 returns. The IRS gave him anonymized access to track the life histories of a whole bunch of kids born in 1980-82 via their parents’ tax returns in 1996-2000 and their own tax returns in 2011-2012.
I’ve been keeping up a running commentary on the strengths and weakness of his analyses of this amazing data source since 2013. Last year, in a Taki’s Magazine article (“Moneyball for Real Estate“) focusing on county-level results, I noted gender gaps hurting boys in some counties. I wrote:
A close reading of the new 2015 paper by Chetty and Nathaniel Hendren, “The Impacts of Neighborhoods on Intergenerational Mobility: Childhood Exposure Effects and County-Level Estimates,” reveals much that is plausible. For example, the effect of local culture, such as gangs, can be different on boys and girls. Chetty and Hendren write:This suggests that there are pockets of places across the U.S., like Baltimore MD, Pima AZ [Tucson], Wayne County (Detroit) MI, Fresno CA, Hillsborough FL [Tampa], and New Haven CT, which seem to produce especially poor outcomes for boys.
New Haven County is a fine place to live if you have daughters and you are a Tiger Mother professor at Yale Law School, but it’s a terrible place to move to if you have poor black sons. Chetty has no data on what percentage of boys who were moved to Baltimore, Detroit, or New Haven weren’t earning much in 2011-12 because they were in jail, but it’s obviously a considerable risk.
In contrast, Tucson, Fresno, and Tampa were all home construction boomtowns that got wiped out by the bursting of the Housing Bubble in 2008, a memorable cataclysm whose effects on his data Chetty doesn’t seem to have pondered.
Conversely, girls whose parents moved them when they were teens in the 1990s to now booming and low crime Manhattan are likely to pay a penalty in terms of lower family income in 2011-2012 because they are less likely to be married than if they had been moved to Salt Lake City.
Chetty has now followed up with a new paper looking at some of these gender gaps:
CHILDHOOD ENVIRONMENT AND GENDER GAPS IN ADULTHOODRaj Chetty
Nathaniel Hendren
Frina Lin
Jeremy Majerovitz
Benjamin Scuderi
Working Paper 21936
https://www.nber.org/papers/w21936
January 2016
ABSTRACT
We show that differences in childhood environments play an important role in shaping gender gaps in adulthood by documenting three facts using population tax records for children born in the 1980s. First, gender gaps in employment rates, earnings, and college attendance vary substantially across the parental income distribution. Notably, the traditional gender gap in employment rates is reversed for children growing up in poor families: boys in families in the bottom quintile of the income distribution are less likely to work than girls. Second, these gender gaps vary substantially across counties and commuting zones in which children grow up. The degree of variation in outcomes across places is largest for boys growing up in poor, single-parent families. Third, the spatial variation in gender gaps is highly correlated with proxies for neighborhood disadvantage. Low-income boys who grow up in high-poverty, high-minority areas work significantly less than girls. These areas also have higher rates of crime, suggesting that boys growing up in concentrated poverty substitute from formal employment to crime. Together, these findings demonstrate that gender gaps in adulthood have roots in childhood, perhaps because childhood disadvantage is especially harmful for boys.
Among children of the poorest families of the 1990s, girls are more likely to grow up to be employed at age 30 than are boys.
Here are the top ten and bottom ten “commuting zones” for more 30ish men than 30ish women working:
Salt Lake City metro has lots of white people with 1950s social values where dad works and mom stays home raising the three kids. The next metros tend to be ones with Hispanics and conservative whites. The bottom ten metros, where more women than men work, all have high black percentages.
As usual, Chetty’s latest map turns out to be another one of Where the Blacks Are:
When looking at the concentrations of red on the map, it’s hard not to say the word “Baltimore.” Just as JFK said D.C. combines northern charm and southern efficiency, Baltimore combines northern welfare and southern lackadaisicalness.
Chetty doesn’t have individual family-level data on race, so he has to guesstimate the effects of race from the percentage of the geographical area that is black.
And even with that blunt instrument, it turns out the percent black in the locale is the dominant factor in this reverse gender gap of working women and idle men:
The single factor that is off by itself in terms of correlation with this Reverse Gender Gap is “Frac. Black Population.”
This shouldn’t be a surprise: after all, in black Africa, feminist organizations do the opposite of what feminist organizations do in the rest of the world: complain that men let women do too much of the work.
Chetty’s data is downloadable here.
Here’s a 538 article with some nice graphs of Chetty’s latest data.
I can be brusque with Chetty in analyzing his analyses, but that’s because he has been handed an unprecedented data set of your tax returns. So we all owe it to ourselves to publicly discuss what he’s doing right (which is considerable) and what he should do to improve his work in the future.
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