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| Darker colors indicate lower income mobility while lighter colors indicate higher mobility. |
An article at the NY Times about the study provides some information on factors that correlate with income mobility (and a really fascinating interactive map.
The team of researchers initially analyzed an enormous database of earnings records to study tax policy, hypothesizing that different local and state tax breaks might affect intergenerational mobility.As you can see from the map, some of the areas with the highest income mobility are rural areas. Using the interactive map, I think I've identified income mobility paradise. Move yourself up to Bismark, North Dakota where someone around 30, whose parents in the 1990s were at the bottom 1% of the income distribution, now have a 19% chance of being in the bottom quintile, a 21% chance of being in the 2nd quintile, a 21% chance of being in the 3rd, 19% chance of the 4th, and a 20% chance of being in the top 20% of incomes.
What they found surprised them, said Raj Chetty, one of the authors and the most recent winner of the John Bates Clark Medal, which the American Economic Association awards to the country’s best academic economist under the age of 40. The researchers concluded that larger tax credits for the poor and higher taxes on the affluent seemed to improve income mobility only slightly. The economists also found only modest or no correlation between mobility and the number of local colleges and their tuition rates or between mobility and the amount of extreme wealth in a region.
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All else being equal, upward mobility tended to be higher in metropolitan areas where poor families were more dispersed among mixed-income neighborhoods.
Income mobility was also higher in areas with more two-parent households, better elementary schools and high schools, and more civic engagement, including membership in religious and community groups.
Regions with larger black populations had lower upward-mobility rates. But the researchers’ analysis suggested that this was not primarily because of their race. Both white and black residents of Atlanta have low upward mobility, for instance.
The authors emphasize that their data allowed them to identify only correlation, not causation. Other economists said that future studies will be important for sorting through the patterns in this new data.
Now, to be fair, before you buy a parka and move north, I kind of wonder if this may be thrown off a bit by out-migration from the area. Via google it looks like Bismark has been growing more slowly than the US as a whole, so it could be that people who are doing very poorly tend to leave. However, one could also imagine that the sorts of factors listed above by the researchers apply pretty heavily in the northern plains.
4 comments:
The way the article is written (which might be wrong; journalists often screw up meta-analysis) seems to imply that out-migration would not matter for these conclusions. They reported it as if they followed individual children in order to measure their income mobility, not averages over areas. The map location you are associated with appears to be the place you lived with your parents at your early-life income, not necessarily the same place you wound up living as an adult.
You would have to go to the original article to see if the map location associated with an individual was a single snapshot at a particular age or moment of time, with no exclusion of individuals who moved in or out of the area at other times, or if they only looked at people who spent a significant part of their childhood in one place.
The methodology is explained more clearly on the project website:
"We constructed measures of relative and absolute mobility for 741 “commuting zones” (CZ’s) in the United States. Commuting zones, constructed by Tolbert and Sizer (1996) based on Census data, are geographical aggregations of counties based on commuting patterns that are similar to metro areas but also cover rural areas. Children are assigned to the CZ based on their location at age 16 (no matter where they live today), so that the location can be interpreted as where a child grew up. When analyzing local area variation, we continue to rank both children and parents based on their positions in the national income distribution. Hence, our statistics measure how well children do relative to those in the nation as a whole rather than those in their own particular community."
http://obs.rc.fas.harvard.edu/chetty/website/IGE/Executive%20Summary.pdf
So, if your family was doing badly, and they left before you were 16, you wouldn't count for the region. If your family was poor, and you grew up, left, and did better somewhere else, you would count for the area.
Still, that seems rigorous enough that it suggests there's something about these central, rural areas that is different from the rest of the county. Nor is it only in the north. Pecos TX and Woodward OK as similar, as are a lot of areas moving up through Kansas and Nebraska. Rural Georgia, Mississippi and South Carolina, by contrast, seem to have a good deal less mobility.
None of the correlated factors that the article identified seemed surprising to me. Two-parent households, good schools, social connections all mattered; taxation-based redistribution of wealth, not so much.
The thing that was most interesting to me (though it makes sense if you think about it) is that integration of the upper and lower middle class matters much more than the 1% kind of inequality.
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