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Author: Carol S. King Presenter: Ruth E. Detlefsen Service Sector Statistics Division

An Evaluation of Changes to the Universe Extraction for Current Business Surveys at the U.S. Census Bureau. Author: Carol S. King Presenter: Ruth E. Detlefsen Service Sector Statistics Division U. S. Census Bureau June 20, 2007. Business Sample Revision. Approximately once every five years

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Author: Carol S. King Presenter: Ruth E. Detlefsen Service Sector Statistics Division

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  1. An Evaluation of Changes to the Universe Extraction for Current Business Surveys at the U.S. Census Bureau Author: Carol S. King Presenter: Ruth E. Detlefsen Service Sector Statistics Division U. S. Census Bureau June 20, 2007

  2. Business Sample Revision • Approximately once every five years • For retail, wholesale, and services sectors

  3. Why a Business Sample Revision (BSR) • To ensure that samples remain representative of the retail, wholesale, and services universes • To redistribute burden for small and mid-size firms currently in the samples • To introduce changes such as new industry codes, coverage expansion, etc.

  4. Topics • Changes made to the edit process • Efforts to improve edit bounds • Introduction of the Edit Tracking System

  5. Business Register (BR) • Business Register (BR) - master business list of employer firms and establishments contains: • administrative record data • Economic Census data • current survey data

  6. Universe Extraction Process • Extract from the BR all retail, wholesale and services establishments • Assign a NAICS-derived sampling recode to each inscope establishment • Compute an estimate of each establishment’s annual sales or receipts, measure of size (MOS) • Edit, review and correct the extracted data

  7. Data Edits - Why Edit the Data? • To find systematic problems in the data or input files • To review data used to compute the establishment measure of size • To review establishments in industries that may have unique reporting or classification issues • To find data problems for individual cases that if not corrected would adversely effect sample sizes

  8. Editing of Data in Prior Universe Extractions • Thirteen edits done at the establishment level • Edits tested Census and administrative data • Edit failures assigned a priority for review • Approximately 132,000 edit failures in BSR-2K

  9. Editing for BSR-06 • Performed edits at both the establishment and sampling unit level • Reviewed establishment failures only if sampling unit failed • Provided an interactive correction system

  10. Sampling Unit Edits for BSR-06 • Identified noncertainty sampling units that increased the sample size by one or more units. This increase was called the effect. • Identified certainty units that had MOS / β * payroll out of line with other certainty units in the same sampling recode.

  11. Noncertainty Effect Edit Edit failures were grouped into three categories: • Highest priority – unit added 15 or more units to the sample size • Next highest priority – unit added 5 to 14 units to the sample size • Lowest priority – unit added 1 to 4 units to the sample size

  12. Maximum Effect for Selected Sampling Recodes

  13. Certainty Edit • Used an Hidiroglou-Berthelot (H-B) edit for certainty unit outliers • Delineated three regions away from the acceptance region • Failures in furthest region were given review priority • Failures in other regions were reviewed as time permitted

  14. BSR-06 Edit Failures • Total establishment failures – 126,000 (132,000 for BSR-2K) • Sampling unit failures - 3,769 • Noncertainty edit failures – 2,637 (0.07% of all noncertainty sampling units) • Certainty sampling units - 1,132 (5% of all certainty units)

  15. Review and Correction of Edit Failures • Establishments of sampling unit edit failures were reviewed based on the priority assigned from the establishment edits. • Corrections were made as needed. • If no correction was made, sampling unit was marked so it would not appear as a failure in subsequent edit runs. • Edits were rerun and effects recomputed.

  16. Sample Sizes Before and After Data Editing

  17. Ratio Edit Bounds in Previous BSR

  18. Review of Ratio Edit Bounds • For BSR-06, • Plain Vanilla (PV) was examined for determining ratio bounds • establishments were grouped by whether singleunit or multiunit establishment within the sampling recode

  19. Establishment Edit Bounds for BSR-06 • PV used for the ratios: • Census Receipts / β * Census Payroll • Census Inventory / Census Receipts • BSR-2K method used for the ratios: • Administrative Payroll / Census Payroll • MOS / Annualized Census Receipts

  20. Edit Tracking System • Which establishments were corrected • When corrections were made • Which variables were corrected • The magnitude of the corrections.

  21. Some Results from the Tracking System • Corrections made throughout the 7-week period • Fifteen correctable fields. Most corrections to six fields. • Number of establishments with at least one change as a percent of the total number of establishments was small. • Changes made impacted the sample sizes.

  22. Conclusions • Satisfied with the sampling units edits and resulting reduction in sample sizes. • Improved our edit bound determination process but would like to see if more improvements can be made. • Will use the output of the edit tracking system to determine what improvements can be made to the extraction process for the next sample revision.

  23. Contact Information Author: Carol S. King Carol.Steadman.King@census.gov Presenter: Ruth E. Detlefsen Ruth.E.Detlefsen@census.gov

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