Unified Enterprise Survey Unified Enterprise Survey New HorizonsNew Horizons

International Conference on Establishment Surveys

Daniela Ravindra and Marie Brodeur

Montreal, June 2007

Statistics CanadaStatistique Canada

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Outline1. Background2. Principles3. Survey Characteristics4. Sampling and Use of Tax Data5. Processing6. Analysis and Dissemination7. Achievements

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Background to the Integrated Approach

Established in 1997 Goal to integrate all annual business surveys Objectives:

– Improve coherence– Improve breath and depth of data–Not increase response burden

Created one central area for processing (ESD)

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Integrated Approach Principles

Use of a single unduplicated frame -- the BR

Common sample design methodology

Questionnaire

–harmonized concepts / variables

–Generic portion

Centralized Data Collection

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Integrated Approach Principles (continued)

Integrated metadata system

Common generic processing systems and methods (all residing in ESD)

Centralized data warehouse

Head Office Survey

Maximum use of tax data

Coherence analysis for large enterprises

Regular profiling of large enterprises

Holistic approach to response management

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Survey Characteristics All annual surveys Establishment Surveys Currently 64 surveys but plans to add more Smallest businesses estimated through tax

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Sampling Stratified Random Sample

– Industry – Province– Size

1 Take-all stratum 2 Take-some strata (50% of units

replaced by tax) Take-none strata

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Sampling ProcessSampling ProcessSurvey Universe File

(2M businesses)

Sample Control File(2M businesses)

Survey Interface File38K CEs / Questionnaires

Tax Est’d (1.4M)

UES Sample (70K businesses)

Tax Replacements17K CEs

55K CEs

BR(2.3M businesses)

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UES : Use of Tax Data in Sampling

T1 T2 and other

T1TN:

Sample of T1

T2 TN:

Census of T2

THRESHOLDS

Main sample to be surveyed(sample size of about 47k, from which 4k are T1)

Take-none : Weighted Sample of T1 and Census of T2

Sample substitution (TRP) for pre-identified T1 (unincorporated) and T2 (Incorporated) units.

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Centralized CollectionCentralized Collection

Mailout

Pre-Contact

Edit / Verification(BLAISE)

Receipt(75% target)

Delinquent Follow-UpCapture / Imaging

“Clean” Records

Score Function

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Centralized Processing Systems and Databases

Develop centralized systems– Single point of access for security– Move away from stand-alone– Increase efficiency of resource use

Integrated Questionnaire Metadata System Edit and imputation

– Use generalized system Allocation

– Developed for complex units– In the process of standardizing the approach

Estimation

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Post-Collection Post-Collection ProcessingProcessing

Pre-Grooming

Allocation / Estimation

Edit & Imputation

“Clean” Records

Central Data Store

Subject Matter Review & Correction

Tool

Tax Data

USTART

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UES: Use of Tax Data in Post-Collection

Validation (comparison)– Verify dubious collected data against it’s

equivalent tax data record Imputation

– One of the methods used for non-response Estimation

– Weighted TRP units, T2 take-none, weighted T1 take-none, T1 adjustments for units not on the business register

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UES: Use of Tax Data in Post-Collection (continued)

Not always a direct correspondence between tax and survey variables: differences in concepts and definitions

Developed a common mapping to bring them together

–Standard income statement called Chart of Accounts

–Map survey and tax data to it

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Analysis and Dissemination

Analysis conducted by subject-matter specialists

Use of common analytical tools Estimates released no later than 15

months after reference date Previous year’s data is revised when

working on current year

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Achievements

Timeliness improved Efficient, streamlined systems Common database Response burden reduced More coherent data More efficient use of resources