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ACS PUMS – How to Aggregate Sample

This document details methods for aggregating sample data from the American Community Survey (ACS) Public Use Microdata Sample (PUMS). It outlines the differences between 2005 and 2006 PUMS data concerning housing units, households, and group quarters populations. Two aggregation approaches are discussed: one focusing on adjusting estimates at the end while the other adjusts weights initially. Key procedures include adjusting dollar amounts for inflation, creating counts, means, medians, and estimating ratios for more precise demographic data analysis.

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ACS PUMS – How to Aggregate Sample

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  1. ACS PUMS – How to Aggregate Sample Anthony Tersine US Census Bureau Census Information Center Meeting October 10, 2007

  2. ACS PUMS - Sampling • 2005 PUMS is limited to housing units and household population • 2006 PUMS includes housing units, household population and the group quarters population

  3. Multiyear PUMS Files • Two approaches – both combine single year files • Adjust estimates at the end • Adjust weights at the beginning

  4. Method 1 • Concatenate single year files • Adjust dollar amounts for inflation • Express prior year dollars in terms of latest year dollars

  5. Adjust Dollar Amounts – 1 • First apply “ADJUST” variable within year • Apply the CPI-U-RS adjustment factors from BLS • http://www.bls.gov/cpi/cpiurs1978_2006.pdf

  6. Adjust Dollar Amounts – 2 • Express year 2005 dollars in terms of 2006 dollars • Values from the CPI-U-RS table for 2005 (286.7) and 2006 (296.1) • Multiply the 2005 dollars by 296.1/286.7 = 1.03279

  7. Adjust Dollar Amounts – Example • 2005-2006 person income in 2006 $ • 2005 person record PINC * (ADJUST / 1000000) * 1.03279 • 2006 person record PINC * (ADJUST / 1000000) • ADJUST – different values

  8. Method 1 –Tabulations • Use combined file as a single-year file • Adjust estimates based on number of years (M) combining • Create counts, means, medians, etc. • Create separate estimates for HU and GQ persons • Standard Errors • Replicate weights • Generalized variances

  9. Method 1 – Counts / Aggregates • All years have GQs or only interested in HU or household pop

  10. Method 1 – Counts / Aggregates • Counts or aggregates - replicates • Counts only - generalized

  11. Method 1 – Counts / Aggregates • Some (but not all) years have GQs • M is total number of years • N is the number of years with GQ data

  12. Method 1 – Counts / Aggregates • Counts or aggregates – replicates • Counts – generalized

  13. Method 1 – Counts Example State of Delaware

  14. Method 1 – Ratios • All years have GQs or only interested in HU or household pop

  15. Method 1 – Ratios • Replicates • Proportion/percents only - generalized

  16. Method 1 – Ratios • Some (but not all) years have GQs • M is total number of years • N is the number of years with GQ data

  17. Method 1 – Ratios • Replicates • Proportion/percents only - generalized

  18. Method 1 – Medians • All years have GQs or only interested in HU or household pop • Normal median (X) on the combined data • Categorical median (Interpolated)

  19. Method 1 – Medians • Replicates • Generalized – Can be done

  20. Method 1 – Medians • Some (but not all) years have GQs • Use method 2

  21. Method 2 • Concatenate single year files • Adjust weights • Adjust dollar amounts for inflation • Same approach as method 1

  22. Adjust Weights • Adjustment factor is the number of years being combined • Divide by the factor

  23. Adjust Weights – Example 1 • 2005-2006 Estimate (PWGTP) • 2005 HU person - weight 50 becomes 25 • 2006 HU person - weight 75 becomes 37.5 • 2006 GQ person - weight 60 will stay 60

  24. Adjust Weights – Example 2 • 2005-2007 Estimate (PWGTP) • 2005 HU person - weight 67 becomes 22.333333 • 2006 HU person - weight 50 becomes 16.666667 • 2007 HU person - weight 75 becomes 25 • 2006 GQ person - weight 60 becomes 30 • 2007 GQ person - weight 55 becomes 27.5

  25. Contact Information Anthony.G.Tersine.Jr@census.gov Alfredo.Navarro@census.gov

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