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2010 Census Coverage Measurement Discussion by Kirk Wolter May 22, - PowerPoint PPT Presentation

2010 Census Coverage Measurement Discussion by Kirk Wolter May 22, 2012 Outline of My Remarks 1. Coverage measurement results 2. Methods used to produce the CCM results 3. Census costs 4. Implications for 2020 2 1. Coverage Measurement


  1. 2010 Census Coverage Measurement Discussion by Kirk Wolter May 22, 2012

  2. Outline of My Remarks 1. Coverage measurement results 2. Methods used to produce the CCM results 3. Census costs 4. Implications for 2020 2

  3. 1. Coverage Measurement Results Net Undercount Rate: National Level, 2010 • CCM = -0.01% (or overcount of 36,000 people) • DA = -0.09% (or overcount of 270,538 people) • Seems amazingly good 3

  4. How Does 2010 Compare to Recent Censuses? Census Year Net Undercount (in %)* 1990 1.61 2000 ‐ 0.49 2010 ‐ 0.01 *Results based on the PES method 4

  5. Differential Undercount • Race • Ethnicity • Sex • Age • Type of enumeration area • Housing tenure • Mover status • Urban/rural • State 5

  6. How Does 2010 Compare to Recent Censuses? Differential Undercount v. Census Year: National Level 7.0 6.0 Difference in Percent Net Undercount 5.0 4.0 3.0 2.0 1.0 0.0 1940 1950 1960 1970 1980 1990 2000 2010 Census Year DA Difference by Sex (Male ‐ Female) DA Difference by Race (Black ‐ Nonblack) PES Difference by Race (NonHispanic Black ‐ NonHispanic White) 6

  7. Differential Undercount by Age: Males in 1980, Demographic Analysis Estimates DA Estimated Percent Net Undercount by Age: Males 5 4 3 Net Undercount (in %) 2 1 0 0 to 4 5 to 9 10 to 14 15 to 19 20 to 24 25 to 29 30 to 34 35 to 39 40 to 44 45 to 49 50 to 54 55 to 59 60 to 64 65 to 69 70 to 74 >= 75 ‐ 1 Age Groups 7

  8. Differential Undercount by Age: Males in 1990, 2000, and 2010, PES Estimates PES Estimated Percent Net Undercount by Age: Males 5 4 3 Net Undercount (in %) 2 1 0 0 to 4 5 to 9 10 to 17 18 to 29 30 to 49 50+ ‐ 1 ‐ 2 Age Groups 2010 2000 1990 8

  9. Differential Undercount by State: 2010, CCM Estimates • Top three states • DC = 2.23% • VT = 1.29% • TX = 0.97% • Bottom three states • AK = -0.85% • OK = -1.08% • WV = -1.43% 9

  10. 2010 was Accurate Overall because of Well Targeted Additions CCM Estimate Census Estimate Correct Correct Enumerations 284,668 Enumerations 284,668 Omissions 15,999 EE+II 16,035 Total Population 300,667 Total Population 300,703 10

  11. Additions at the State Level EE+II v. Omissions at the State Level: 2010 10 9 8 7 6 EE+II (in %) 5 4 3 2 1 0 0 1 2 3 4 5 6 7 8 9 10 Omissions (in %) 11

  12. Additions at the County Level EE+II v. Omissions at the County Level: 2010 20.0 15.0 EE+II (in %) 10.0 5.0 0.0 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 18.0 Omissions (in %) 12

  13. Additions at the County Level EE+II v. Omissions at the County Level: 2010 20.0 } Net Undercount 15.0 EE+II (in %) 10.0 5.0 0.0 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 18.0 Omissions (in %) 13

  14. Duplicates are a Major Part of the Census Additions Duplicates 5993 Other EE 8521 1520 II 14

  15. But Do They Distort Relationships? Net Key Variables CE Duplicates Other EE II Undercount Omissions Persons White 95.2 2.7 0.4 1.7 ‐ 0.5 4.3 Black 92.6 3.6 0.7 3.1 2.1 9.3 Owner 95.7 2.4 0.4 1.5 ‐ 0.6 3.7 Renter 92.5 3.7 0.7 3.0 1.1 8.5 Mailout/Mailback 94.8 2.7 0.5 2.0 0.0 5.2 Update/Leave 92.7 4.7 0.5 2.2 ‐ 1.4 6.1 Update/Enumerate 91.1 3.0 0.5 5.3 7.9 16.0 OK 92.6 5.0 0.7 1.4 ‐ 1.1 6.4 TX 94.0 2.7 0.6 2.6 1.0 6.9 Housing Units Owner 98.6 0.6 0.8 0.2 1.6 Renter 97.2 1.3 1.5 ‐ 0.3 2.5 15

  16. 16 Type of Enumeration Areas

  17. Quality Declines with Time Components of Census by Mail Return Date 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 2/25 ‐ 3/17 3/18 ‐ 3/24 3/25 ‐ 3/31 4/1 ‐ 4/7 4/8 ‐ 4/15 4/15 ‐ 4/30 5/1 ‐ 9/30 No Valid Return Not in Mail Return Universe CE Duplicates Other EE II 17

  18. Quality Declines with Time - continued Components of Census by NRFU Domain and Month of Enumeration 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% April May June July and Unknown In VDC and in In VDC but not Not in NRFU or Not in any August Month NRFU NRFU VDC but in NRFU Universe NRFU Reinterview or Residual CE Duplicates Other EE II 18

  19. Wish List • Analysis by mover status • Ethnographic studies • Analysis of omissions • Within household • Whole household 19

  20. Analysis of Omissions Omissions of Persons v. Omissions of HUs: State Level, 2010 10 9 8 Omisions of Persons (in %) 7 6 5 4 3 2 1 0 0 1 2 3 4 5 6 7 8 9 10 Omissions of HUs (in %) 20

  21. 2. Methods Used to Produce the CCM Results • Basic Method • Problems? • Not enough information for matching • Innovations • Assessment of undercount by stage of operations • Persons and HUs • Logistic regression • Correction for correlation bias 21

  22. 22 2. Methods - continued • Great work!

  23. 3. Census Costs Costs in 2009 Real Dollars per HU v. Census Year $140 $120 $100 $80 Dollars $60 $40 $20 $0 1950 1960 1970 1980 1990 2000 2010 2020 Census Years 23

  24. Approximate Distribution of Total Costs in 2010 $2,266 $4,147 Communications and technology $436 Printing and postage Office space and staff Fingerprinting National processing center ops Headquarters staff $2,129 Field ops $148 $364 $2,986 24

  25. Approximate Distribution of Field Ops Costs in 2010 $386 $450 $118 $108 Address canvassing NRFU $341 VDC Update/enumerate Update/leave Other field ops $2,744 25

  26. 4. Implications for 2020 • Simulate cost and quality of alternative census scenarios • Address canvassing • NRFU • VDC • CFU • Update/leave • Update/enumerate • Ascertain key reasons why people and HUs are being missed 26

  27. 2020 - continued • Duplicates, other EE, and II • Ascertain key reasons for EE+II • Ascertain how well they balance omissions within blocks, tracts, and counties • Are they a cost-effective, worthwhile, and acceptable compensation for the omissions • Internet census • Any new problems of EE, II, or omissions? • Any new problems of coverage measurement? • Administrative records census • Any new problems of EE, II, or omissions? • Any new problems of coverage measurement? 27

  28. Thank You!

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