1 an evaluation of changes to the universe extraction for current business surveys at the u.s....
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An Evaluation of Changes to the Universe Extraction for Current Business Surveys at the U.S.
Census Bureau
Author: Carol S. KingPresenter: Ruth E. Detlefsen
Service Sector Statistics DivisionU. S. Census Bureau
June 20, 2007
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Business Sample Revision
• Approximately once every five years
• For retail, wholesale, and services sectors
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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.
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Topics
• Changes made to the edit process
• Efforts to improve edit bounds
• Introduction of the Edit Tracking System
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Business Register (BR)
Business Register (BR) - master business list of employer firms and establishments contains:
• administrative record data
• Economic Census data
• current survey data
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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
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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
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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
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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
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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.
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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
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Maximum Effect for Selected Sampling Recodes
Trade Sampling Recode Initial Week 4 Week 7
Services 621490 – Other Individual and
Family Services
640 640 4
Services 523920 – Portfolio Management 639 127 32
Services 561510 – Travel Agencies 316 1 0
Retail 444130 – Hardware Stores 634 633 18
Retail 722410 – Drinking Places 106 106 106
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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
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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)
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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.
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Sample Sizes Before and After Data Editing
Survey
Sample Size Before Data Editing
Sample Size After Data Editing
Percent Change in Sample Size
MRTS 13,460 12,384 -8.0%
MWTS 6,834 6,556 -4.4%
SAS 70,710 61,177 -13.5%
90,554 80,117 -12.0%
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Ratio Edit Bounds in Previous BSR
Ratio BSR-2K Upper
Bound
BSR-2K Lower
Bound
Administrative Payroll/ Census
Payroll 99th percentile 1/99th percentile
Census Receipts/ β * Census
payroll 99th percentile 1/99th percentile
Census Inventory/Census
Receipts
10 0.005
MOS/Census Receipts 10 1/10
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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
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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
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Edit Tracking System
• Which establishments were corrected
• When corrections were made
• Which variables were corrected
• The magnitude of the corrections.
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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.
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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.
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Contact Information
Author: Carol S. King [email protected]
Presenter: Ruth E. Detlefsen [email protected]