1 Demographic Analysis of the 2010 Census Jason Devine U.S. Census Bureau 2010 SDC Steering Committee Meeting February 23, 2010 This presentation is released to inform interested parties of research and to encourage discussion. Any views expressed on statistical, methodological, technical, or operational issues are those of the authors and not necessarily those of the U.S. Census Bureau.

2 Census 2010 Timeline December Apportionment data will be released December 2010 – DA population estimates by single years of age, sex, and Black, non- Black will be finalized Survey-Based estimates of coverage will be released

3 What is Demographic Analysis (DA)? DA is one of two methods used by the Census Bureau to assess coverage of the decennial census. DA starts with the development of population estimates from historical vital statistics, estimates of international migration, and other data sources that are essentially independent of the census. These estimates are then compared to census counts to arrive at estimates of census coverage by age, sex, and limited race groups.

4 DA Progress and Plans for 2010 Presented our plans to a range of audiences and external experts Working closely with members of the FSCPE - formed an FSCPE/DA working group Held an expert workshop on January 8 Working to establish and benefit from collaborations with external experts Upcoming panels at PAA (April) and ASA (Aug) End of 2010 and early 2011 – release of range of DA estimates of census coverage

5 Demographic Analysis for 2010 DA population estimates will be developed by single years of age, sex, and race (Black, non- Black) Difference between the DA estimate and the census count will represent an estimate of census coverage Additional effort directed towards assessing uncertainty in the DA estimates Deliver sex ratios for use in the survey-based estimates of coverage

6 Two DA Estimation Subgroups Ages under 65 are based on historical components of change for cohorts beginning with 1945 (births, deaths, immigration, emigration) P = B – D + I – E Ages 65 and over are based on aggregate Medicare enrollments, adjusted for under- enrollment Estimates for the population will also be developed from the components of change for evaluation purposes

7 DA Expert Workshop Attendees/Format Asked for input on all aspects of DA 22 external participants Ken Darga represented the FSCPE NCHS, SSA, CMS, DHS, Statistics Canada, PEW Hispanic Center, COPAFS, INEGI, FSU, UMich, UPenn, UT Presented four papers provided three weeks in advance, three discussants Will make minutes and papers available Described in the Director’s blog

8 DA Expert Workshop A great conference at Census Bureau headquarters a few days ago gathered experts to give advice about how the 2010 demographic analysis results should be presented. Bertrand Russell, in commenting on how science progresses, once noted that the more scientists know, the more they also know what they don’t know. By giving the country multiple estimates, we’ll be reflecting this higher state of understanding the difficulties of demographic analysis. From the Director’s blog:

9 DA Components in 2000 ComponentEstimate (in thousands) Total Population281,760 Population Under Age 65 in Births starting with ,860 - Deaths to persons born since ,767 + Immigration of persons born since ,564 - Emigration of persons born since 19355,485 Population Ages 65 and Over in Medicare-based population33,245 + Estimated number not enrolled1, ,172 34,587

10 Census 2000 and DA Estimates by Age

11 Race Classification of Births Achieving consistency in the race classification of births with the reporting of race in the census is a challenge Race of the child is not on the birth certificate; it is assigned based on the race of the parents The race classification in DA largely reflect the race assigned in the administrative records (e.g., births, deaths, enrollment in Medicare) The DA estimates are biased to the extent that people who are classified as Black in DA reported a different race in the census

12 Race in the Vital Statistics DA relies on birth records to categorize the native- born population under 65 as Black or non-Black and death records to account for deaths to the resident population by Black or non-Black The birth records include a race for each parent and may be recorded by proxy or imputed The majority of birth and death records only included the option to report a single race Race can be assigned to each birth based on the recorded race of the mother and/or father

13 Race in the Census Reporting of race in the census is based on self- identification May be reported by someone else or imputed Includes the instruction to ‘Mark one or more boxes’ Includes the option to report ‘Some Other Race’ Census results can be tabulated by single race responses ‘Alone,’ multiple race responses ‘In Combination,’ and by responses ‘Alone or In Combination’

14 What Does This Mean For DA? We can try to minimize the conceptual differences between the DA estimates and the census count by Black and non-Black, but can not eliminate them This will have a minimal impact on the DA estimates of the total population by age and sex and the DA sex ratios by Black and non- Black

15 Uncertainty in the DA Estimates DA estimates of coverage contain uncertainty from errors in the data (sampling and non- sampling), the assumptions used to construct the DA estimates, and the inconsistencies between the DA and census race categories “Uncertainty” measures have been developed for assessing the accuracy of previous DA estimates, but there has been a lack of consensus about the validity of the models used and assumptions about the range of each component

16 Uncertainty in the DA Estimates For 2010 DA, we will develop a series of “illustrative” estimates to demonstrate the impact of varying assumptions in each of the components used in the DA estimates Uncertainty will vary across each single year of age, sex, and race (Black, non-Black) DA estimate and demographic measure DA Sex Ratios –many DA errors affect males and females equally (e.g., birth registration completeness factors) –inconsistency in race classification has about the same affect for males and females

17 Jason Devine (Vital Statistics) (301) Renuka Bhaskar (Immigration) (301) Kirsten West (Medicare) (301) Contacts