How Economists Tally Unemployment-and Its Affect on
the Black Jobless Rate
by Shani O. Hilton, Hatty Lee
Thursday, February 23 2012
When the black unemployment numbers dropped so steeply
in January-from 15.7 to 12.7 percent-a lot of analysts
were scratching their heads to figure out why. One told
us that it was "quite surprising," but there would be no
way to know what the numbers meant or whether they were
accurate until we saw if the trend continued in later
months. But why is that? Aren't these numbers hard and
fast facts? We dug a little deeper into the process of
tracking joblessness to find out. Put on your data nerd
hat and follow along.
We learned two important things. First, it's confusing.
Second, it's difficult to know each month if the latest
numbers bandied about on newscasts are as accurate as we
think they are. When unemployment numbers fall, like
they did so dramatically with black workers last month,
any one of three factors could be driving that change-
and it's difficult to know which one is really making
the difference. Colorlines.com graphic designer Hatty
Lee has mapped out the three factors visually below, but
here's the detailed explanation of each option.
[moderator: please use the link above to view
Hatty Lee's graphic depiction of the factors
which influence the study of Black unemployment]
1) An actual reduction in unemployment. This is the
ideal, but since it's unlikely that unemployment would
fall by three points for the black population in a
single month, real employment is not likely the only
thing that it explains it.
2) Month-to-month variability for smaller populations.
Unemployment for blacks has hovered around double the
rate of whites for decades. But the numbers tend to
fluctuate a bit more for black workers, because of the
way joblessness is tallied. To get the nation's
unemployment data, researchers select 60,000 households
representing 350 million people. Of that 60,000, the
proportional sample of black households is about 7,500.
That's a fairly small number within the larger sample,
and the smaller the sample, the more likely it is to
2) The impact of new weights. This is where it gets
complicated. Each household is sampled for four months,
then ignored for eight months, then sampled for four
more months, and then released from the sample. And each
household is given a different formula weight, depending
on a wide range of factors, including the identity of
the household and the larger socio-economic picture.
So, think of each household like a car. These weights
stay the same for a year, and then at the end of the
year, the households are reweighted to reflect the more
current economic climate. If each household is like a
car, then over the course of a year, every month the
numbers get slightly further out of alignment-because
the weights stay the same from January to December even
as the broader economic picture changes. By the end of
the year, the car needs a tune-up, which is when the
Bureau of Labor Statistics re-weights the household.
This means that the decline in unemployment from January
2011 to December 2011 is most likely to be a misreading,
because the households sampled in December are using the
same weights as the January households-even though the
weights in December are now far out of alignment with
the larger economic picture.
Secondarily, at the end of each 10 year Census, the BLS
does another re-weighting. If the January numbers were
calculated under new weights, and the December numbers
were calculated under the old weights, then calculating
the December numbers under the new weights could show a
less steep drop in unemployment.
Most importantly, however, what we've learned is that
there's really no way to tell what's going on until a
few more months have passed.
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