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Outline

Improvements in stratification in the UK's Office for National Statistics Pete Brodie, Martina Portanti & Emily Carless UK Office for National Statistics. Outline. Context The B usiness R egister and E mployment S urvey Stratification Variables Employment Size Measure

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Outline

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  1. Improvements in stratification in the UK's Office for National Statistics Pete Brodie, Martina Portanti & Emily CarlessUK Office for National Statistics

  2. Outline • Context • The Business Register and Employment Survey • Stratification Variables • Employment Size Measure • Complexity of Enterprise • Sample Design and Estimation • Conclusion

  3. BRES (1/2) Why design a new survey (BRES)? • The Allsopp Review of Statistics for Economic Policy Making • Utilise administrative data and improve regional statistics • The Integration of survey systems to improve efficiency. • Integrate ABI/1 (employment estimates) • and the BRS (register updating)

  4. BRES (2/2) Annual Business Inquiry (ABI) Business Register Survey (BRS) Part 1 Part 2 Updates the business register Employment Estimates Financial Estimates Annual Business Inquiry (ABI/2) Financial Estimates Current Business Register and Employment Proposed Survey (BRES) Employment Estimates

  5. Stratification Variables • Register Employment (size banded) with Industrial Classification (SIC is the UK’s NACE) • For new survey • Considered the use of Full Time Equivalent (FTE) instead • Considered the use of a marker for complex businesses

  6. Employment Size Measure (1/6) • Problems caused by using Headcount (HC) for stratification • Some businesses that employ many part time workers appear unduly large • For certain industries the correlation between this measure and returned employment is not particularly good

  7. Employment Size Measure (2/6) • A more sensible measure may be the FTE but how to define it? • Tried two different definitions: • FTE1 = Full Time + 0.5 Part Time • FTE2 = Full Time + industry specific fraction for PT (using data from ASHE) • As well as HC = FT + PT

  8. Employment Size Measure (3/6) • Firstly we examined the effect of these three measures on burden on business • Each FTE measure reduces business size compared to HC • Fewer businesses sampled (Osmotherly Rule) • Little difference between FTE1 and FTE2

  9. Employment Size Measure (4/6) • Secondly we examined the effect of the measures on correlation with returned variables • The table below shows the correlation between returned values from the Annual Business Inquiry and the three employment measures for the whole economy.

  10. Employment Size Measure (5/6) • Lastly we looked at the effect of the stratification variable on cv’s of estimates

  11. Employment Size Measure (6/6) • FTE is a much better stratification variable • Reduces burden without unduly reducing quality • Markedly reduces cv’s for some variables without unduly reducing quality of others • No gain from using the complex definition so we will use simple FTE1 (=FT + 0.5 PT)

  12. Complexity of Enterprise (1/7) EU Regulation: “structure of units on the Register must be updated at least every four years” ONS: “structure of multiple Local Units (LUs) enterprises must be updated at least every four years” With: Number of LUs LU variables (SIC, geography, employment)

  13. Complexity of Enterprise (2/7) • Would satisfy register updating requirements if there was good coverage of employment CURRENT REGISTER has: Single LU enterprises Multi LU enterprises 2,138,000 LUs 63,000 enterprises 547,000 LUs

  14. Complexity of Enterprise (3/7) 100% 90% 80% 70% 60% 50% Multi 40% Single 30% 20% 10% 0% Enterprises Employment

  15. Complexity of Enterprise (4/7) • But 40,000 of these multi LU enterprises have all LUs in the same region with the same SIC • Most employment is covered by defining complex enterprises: • LUs in more than one region • OR LUs classified to more than one SIC-2 industry • The smaller (less than 20 employment) businesses had very few LUs (all small also) so we did not consider these as complex

  16. Complexity of Enterprise (5/7) • The second main aim of BRES was to satisfy the Allsopp requirements: • to improve regional estimates • To retain fine industrial breakdowns • Use detailed LU data in estimation • Discrepancy between parent enterprise region and local unit region causes large differences in regional employment estimates

  17. Complexity of Enterprise (6/7)

  18. Complexity of Enterprise (7/7) • Complex enterprises are the ones with most likely discrepancy • Making complex enterprises take-all should improve regional estimation • Similarly improvements will be made in estimation at 2-digit SIC as Allsopp recommended

  19. Sample Design and Estimation (1/4) • Tested three different designs with stratum cut-offs set to optimise register updating or estimation requirements • Tested whether stratification within size bands by geography or industry was best • Tested the use of a fully enumerated stratum for “unusual” enterprises.

  20. Sample Design and Estimation (2/4) • Conventional Industry combined with Geographical stratification would spread sample too thinly • Tested a two partition solution • Calibrated to a geography partition and simultaneously to an Industry partition • Tested the auxiliary and variance model to be used in calibration

  21. Sample Design and Estimation (3/4) • Created a LU level Pseudo Population from the current IDBR RU data • Returned values were created using a ratio model within strata to create residuals about the model • Imputed LU level variables for Industry and region (probabilistically) • Added outliers (0.1%) • Repeated sampling to test coverage and estimation properties of different options

  22. Sample Design and Estimation (4/4) Best design: • Gave best coverage of employment so best for updating • Gave smallest MSEs for most outputs

  23. Conclusions • We can improve both register updating and employment estimation by replacing two surveys with one more efficient survey • Uses the concept of a complex business to increase coverage of “important” businesses • Reduces burden on businesses by measuring size using FTEs • Increase efficiency of estimation by calibrating in two partitions

  24. Register Updating • Talk by Daniel Lewis of the ONS • Evaluating the effect of business register updates on monthly survey estimates • Tomorrow afternoon (Wednesday) Session 39: Updating of Business Registers

  25. Any questions? Contact details: Pete.Brodie@ons.gsi.gov.uk

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