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2 Census Scientifically or Politically Correct? Stephen E. Fienberg Department of Statistics Notes for Stat October, 2001

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4 October Census Bureau Decision March 1, 2001 not to use adjusted data for redistricting. New October 17 decision against adjustment for intercensal estimates

5 How Many People Were There in the U.S. on April 1, 2000? At march 1 decision here were the numbers: Raw Census Count:281.4 million Demographic Analysis: million ACE: million Which number should we trust and use? Should we count or should we estimate?

6 Demographic Analysis Population = births - deaths + immigration - emigration only available at national level, and for blacks and whites

7 Net Census Undercount-Mother Rule Undercount Year Black White Differential Net %5.1% 5.2%5.6% %3.8% 5.8%4.4% %2.7% 5.6%3.3% %2.2% 5.8%2.9% 1980* 5.9%0.7% 5.2%1.4% 1990** 7.4%1.0% 6.4%1.9%

8 Net Census Undercount-Father Rule* Undercount Year Black White Differential Net %5.0% 3.4%5.4% %3.8% 3.8%4.1% %2.7% 3.9%3.1% %2.2% 4.3%2.7% %0.8% 3.7%1.2% %1.3% 4.4%1.8% %

DA Census Undercount Estimates (Rev. October 2001) SourceCount%Undercount Census281.4 mil. DA(original) mil.-0.65% DA(Alt.March)282.3 mil.0.32% DA(Rev. Oct.)*281.8 mil.0.12% ACE284.7 mil.1.3% *Changes to births and immigration components

10 Demographic Analysis No reliable measures of uncertainty (variability). Incompatibilities with new Census race measures. Major biases for immigration and Hispanics. Otherwise DA and ACE were much closer than the Bureau admitted! (Passel, 2001)

11 Census Accuracy Myth 3. The ‘actual enumeration’ has been highly successful at counting the population: ‘‘The 1990 census accurately counted 98.4% of the population....” What is error in the census? –Omissions AND Erroneous Enumerations

12 From A Survey! Our information about omissions and erroneous enumerations comes from a survey, taken after the census and matched to census records -- the post enumeration survey(PES in 1990 or ACE in 2000).

PES Net Undercount Estimates GroupUndercount Differential Non-Black1.7 Black Hispanic Asian American Indian5.02.9

ACE Net Undercount Estimates GroupUndercount Differential Non-Black1.0 Black Hispanic TBA TBA Asian TBA TBA American Indian TBA TBA

15 Gross vs. Net Error Omissions Erroneous Enumerations Gross Error = Omissions + Err. Enumerations Net Error = Omissions - Err. Enumerations 1990 Gross error (~8-12%) vs. Net error (1.6%)

16 Gross v. Net Error (in millions) ___ 2000* erroneous enumerations omissions net undercount gross errors gross as % of population 7 % 10.4% 5.4% *(based on March, 2001 reports; excludes imputations, suspected duplicates, and group quarter errors)

17 October 17, 2001 Decision No adjustment for intercensal purposes because of suspected 3 mil. EEs missed by ACE. Need revised information on gross error but some estimates now put it at 1990 levels, i.e., in neighborhood of 25 million.

18 Sampling and Census 2000 The Census enumeration Process: –Short Form and Long Form. –Mail-out and mail-back (trying to count all). –Non-response Follow-up. –Institutions and the Homeless. Accuracy and Coverage Evaluation –Post-Enumeration Survey (314,000 HHs)

19 ACE & Dual Systems Estimation Survey approximately 314,000 HH in 11,000 blocks. Correct raw census counts using “capture- recapture” or dual systems methodology. Corrects for omissions AND erroneous enumerations.

20 Political Bias & Manipulation Myth 6. Census Sampling Would Favor Democrats. “ Statistical errors in the count, accidental or deliberate, could result in as many as 24 GOP seats being lost.” “The ability to ‘create’ or ‘eliminate’ millions of strategically placed citizens with the stroke of a pen introduces a potent and disturbing new political weapon.”

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22 Winners and Losers in 1990 and Adjustment winners: –California –Arizona 1990 Adjustment losers: –Wisconsin –Pennsylvania In 2000, had adjusted data been used for apportionment, Texas would have gained seat.

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24 Perfection of the Sample Myth 11. Persons found in the census but not in the sample are inferred to have been counted erroneously by the census. ‘Rehnquist-Stark’ fallacy, or “What is dual systems estimation all about?”

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26 Dual Systems Components

27 Dual Systems Estimation Dual Systems Estimation

28 Dual Systems Example Counting people in a census block. 150 people 1st time -- the census; and 200 2nd time -- the sample. Of 200 people in sample, 125 were among 150 people in the census Total no. people seen = ( ) = 225.

29 Example (cont.) In sample, proportion of people also in census is 125/200, or 5/8. Generalizing from sample to entire population, we conclude that only 5/8 of people in the block were captured in census: 150 = (5/8) Ñ Ñ = (8/5) (1500) = 240.

30 More Formal Version Ñ = n cen n pes /a ? 150 Ñ = 150  200/125 = 240

31 Dual Systems For Census 2000 To apply method in the context of ACE, we need to correct census count for EEs by subtracting them. Practical issues regarding implementation.

32 Dual Systems Assumptions Perfect matching Homogeneity Dependence between sample and census –correlation bias? Errorless assessment of erroneous enumerations –big issue for 2000 census