Skip Header

We are hiring thousands of people for the 2020 Census. Click to learn more and apply.

Measuring Quality in a Census, Part 4

Mon Aug 23 2010
Robert Groves
Component ID: #ti1179293286

The point of the first three posts on census quality was to note that there is no known “truth” with regard to the population of the United States. We have different tools, each of which gives us a different look at the population at different points in time, but each of which has some weakness.

Component ID: #ti941165634

This post is a short description of the method of “demographic analysis.” It provides estimates of population counts at the national level only. It provides separate estimates by single years of age, separately for males and females, separately for two race groups (Black and nonblack).

Component ID: #ti1777922189

It does not provide separate estimates for each state (and thus is not helpful in providing a different set of reapportionment figures); it does not provide estimates for the 8 million different census blocks (and thus does not permit different redistricting estimates).

Component ID: #ti1777922188

Just like the census, demographic analysis has a simple ideal. If, for every year, we could count all the births in the country, subtract all the deaths, add all immigrants to the country, subtract all emigrants, then we could have a perfect accounting of the total population and how it has changed across time, and from one census to the next.

Component ID: #ti1777922187

If we could know the gender of births, and the age and gender of deaths, immigrants, and emigrants, we could produce counts by males and females separately by age. If we could do the same for race groups, we could produce counts by different race groups.
This is essentially what we try to do, but, as with the census, we can’t achieve the ideal. Each of the major components of demographic analysis has some problem in practice and need a fix:

Component ID: #ti1777922186

1) Because of the quality of the historical data on births, for the age groups 65 years and older, we use counts from Medicare enrollment by age, gender, and race.

Component ID: #ti1777922185

a. Problem: not all those 65 and older are enrolled in Medicare. Fix: use survey data on medical insurance coverage to estimate the number not enrolled.

Component ID: #ti1777922184

b. Problem: Medicare uses different race measurement than Census. Fix: Supplement the Medicare data with data from other sources and in some cases assume race measurement is equivalent.

Component ID: #ti1777922183

2) For those under 65 years of age:

Component ID: #ti1777922182

a. Problem: underegistration of births in older age groups (e.g., 6% of Black births in 1950). Fix: use estimates of the completeness of birth registration from birth registration research, combined with professional judgment, to adjust birth counts

Component ID: #ti1777922181

b. Problem: different race measurement on birth and death records than on Census. Fix: examine patterns of racial identification in the last census and use professional judgment to assign groups only to “black” and “nonblack” race categories.

Component ID: #ti1777922180

c. Problem: no direct count of components of international migration. Fix: use a combination of survey and other data sources and professional judgment to estimate international migration

Component ID: #ti718987068

Every component that involves some professional judgment is subject to professional debate. Some of the debates concern very small categories, which do not individually affect the national figures too much.

Component ID: #ti718987069

Increasingly, the component generating the most controversy is the count of international migrants by race, age, and gender groups. There is little consensus among demographers about how large those groups are.

Component ID: #ti718987070

Most professionals believe that the strongest features of demographic analysis come from its consistency over different age by gender groups. When the estimates of these group sizes systematically vary from the counts based on a census, many believe that is evidence of weaknesses in the census, not in the demographic analysis. Few professionals would attempt to adjust the census counts based on these comparisons, however, given the problems reviewed above.

Component ID: #ti718987071

To be transparent with the American public, in early December 2010, we will release a preliminary range of estimates by age, gender, and race, developed using the demographic methods above. This range of estimates can be compared to the total population count we release in late December from the 2010 Census.

Component ID: #ti718987072

Later, in the Spring of 2011, the range of estimates by age, race, and gender can be compared to the 2010 Census counts. Then, we may be able to improve our assumptions about components to the demographic analysis estimates, and then release an improved set of demographic analysis numbers sometime in 2011.

Component ID: #ti718987073

I expect in late December, when we release the 2010 Census counts and compare them to the demographic analysis range of estimates, journalists will ask which one is correct. As you can see from the description above, I won’t be able to answer that question. Each method has strengths and weaknesses for the various statistics of interest.

Component ID: #ti718987074

Please submit any questions pertaining to this post to ask.census.gov

X
  Is this page helpful?
Thumbs Up Image Yes    Thumbs Down Image No
X
Comments or suggestions?
No, thanks
255 characters remaining
X
Thank you for your feedback.
Comments or suggestions?
Back to Header