1. The use of Linked Employer-Employee Data in Maintaining the Statistics New Zealand Business Frame and in producing Business Demographic Statistics Geoff Mead

2. Over view of Business Frame (BF)
BF has 440,000 enterprise units
BF is maintained primarily from administrative data.
Frame update surveys for larger / complex enterprises.
Statistical unit model.
Enterprise
Legal Unit
Kind of activity unit
Local Unit

3. New source of administrative tax data
Employer monthly schedule (EMS)
All employers must complete an EMS tax return,
Monthly
150,000 employers in NZ
EMS data records about 1.9 mill filled jobs
Strict privacy, security, and confidentiality policies are applied in the use of the data by Statistics NZ
Encryption of employee tax data numbers
Removal of employee names
Tight access control
Use only for statistical purposes

4. EMS return identifies:
Name and tax number of the employer
Name and tax number of each employee
Taxable earnings during the month for each employee
Tax deductions for each employee
Start & end dates for each employee

6. Integration with BF
BF enterprise unit holds tax number of tax legal unit
Dataset is referred to as LEED
Linked Employer Employee Data
Updated monthly
BF Enterprise Unit
Tax Employer Unit
Employee 1
Employee 2
Employee 3
Employee …..

7. Uses of LEED data Quarterly labour market statistics Maintain the BF
Maintain the BF
Improved business demographic statistics
This talk focuses on the last 2 items

8. EMS BF size measure BF Enterprise unit employment size measures
Aggregated counts of employees
Employee count
Rolling mean employee , 12 month rolling mean of employee count
Updated monthly

9. Identification of continuing local units
Traditionally the BF has primarily identified changes of ownership for continuing local units by surveying enterprises
LEED allows the tracking of employee clusters that move between employers
Potentially indicates changes of local unit ownership if the original employer (enterprise) ceases to be an employer
Cluster of employees over a minimum number
Information not useful in seasonal industries

10. Example of employee cluster tracking
Month T
Month T + 1
Employer A
Employees 1 2 3 4 5
Employer B
(“Birth”)
Zero employees
All employees of employer A have moved to employer B.
Employer A has a single local unit.
Employer B is a new employer.
Indicates that employer B has taken ownership of the local unit where the 5 employees work.

11. Employee cluster tracking
Automatic BF updates for small and medium sized enterprises with simple structures (single local unit)
Other updates for larger / complex enterprises are referred to an operator
Employee cluster tracking historically has identified an extra 20% of local unit ownership changes

12. Identification of potentially ceased enterprises
LEED data allows the identification of employers that stop employing and the employees have not moved in a cluster to another employer
Employees have dispersed
Potentially indicates that an enterprise and local unit(s) have ceased?
To date used to supplement other tax data (VAT) that is the prime source for identifying enterprise unit ceases.

13. Identification of potentially missing local units
LEED data includes sufficient detail to classify each employee to a region
Allows regional distribution of LEED employees to be confronted with the BF local unit structure for an employer (enterprise)
Does the employer have a significant number of employees in a region where there is no BF local unit?

14. Using LEED data to identify potentially missing local units
Employer
Region X
100 employees
Region Y
50 employees
Region Z
80 employees
BF Structure
Enterprise Unit
Local Unit Region X
Local Unit Region Y ?

15. Improved Business Demography Statistics
Currently being implemented, new series backdated to 2000
Employee cluster tracking to help identify continuing local units
Probabilistic record matching to help identify continuing local units
Inclusion of agriculture industry
Eurostat / OECD standards for defining continuing local units & enterprises

16. Significant improvements in the quality of the Business Demographic Statistics More continuing local units and enterprises are being identified Enterprise birth rates
Year
2001
2002
2003
2004
2005
Enterprise Birth Rate
Old Series
17%
18%
21%
Enhanced Series
12%
13%

17. Enterprise death rates
Year
2001
2002
2003
2004
2005
Enterprise Death Rate
Old Series
18%
15%
14%
12%
Enhanced Series
10%

18. Conclusion
Use of LEED data to maintain the BF is still at the “bedding in” stage
LEED data has significant potential to help maintain the BF
Improved quality in BF and the derived Business Demographic Statistics
Further reductions in the requirements for BF update surveys