Linked EmployerEmployee Data

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Linked Employer-Employee Data

• Seventh Management Seminar for heads of NSOs
• Shanghai, October 2008
• Cathryn Ashley-Jones
• Deputy Government Statistician

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Linked Employer-Employee Data (LEED)

• Description
• Objectives and benefits
• Critical success factors and lessons learnt
• Future direction

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Description - LEED

• Data integration project
• Linked employer-employee data
• Longitudinal (April 1999June 2006)
• Measures labour market dynamics at both the
  national and regional level
• Collaborative project with other agencies
• Follows other successful initiatives (US, France,
  Sweden, Germany)

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Data Sources

• Tax Department
• Employer Schedules
• Monthly data from employers
• Employees / earnings /
• deductions
• Employers employees
• uniquely identified

• Business Frame
• List of businesses
• By enterprise geographic
• unit
• Uses standard industrial
• classification

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The Linking
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Objectives

• Provides new insights into the dynamics of the
  labour market - labour market outcomes for New
  Zealanders, and the operations of businesses
• Enable monitoring of impacts of labour market
  programmes
• Assists with the management of respondent load in
  the long run

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Published statistics

• Quarterly data releases (job level)
• Focus is on jobs (a unique employer-employee
  pair)
• Measures include
• Total, mean and median earnings for full-quarter
  jobs,
• Total, mean and median earnings for continuing
  jobs, and new hires
• Total filled jobs
• Worker accessions and separations
• Job destruction and creation
• Worker turnover rates
• Published 12 months after reference quarter
• Detailed tables on-line

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Published statistics

• Annual data releases (person-level)
• Sources of income
• earnings, benefit, pension, accident
  compensation, student allowance, and paid
  parental leave
• counts and median annual earnings
• Income transitions
• flows between income sources and deciles
• Spells of employment (person level)
• length of spells by income and age group
• Multiple job holding
• counts and monthly median earnings
• Self-employed
• by firm size and by industry

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Benefits
Research programme
New statistics
Knowledge of data quality issues
Building good relationships
Data integration skills
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Critical success factors

• Well funded and planned programme
• International expertise used
• Highly skilled team throughout development phase
• Strong collaboration between agencies
• Data users group kept fully involved
• Staged approach
• Privacy and confidentiality carefully addressed

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Lessons learnt

• Encourage discussion of fit-for-purpose (quality
  vs cost)
• Have a healthy disrespect for disk space
• Document processes throughout
• Ensure plenty of resource its resource
  intensive
• Encourage shared understanding of issues and
  problems
• Work towards continuous improvement
• Start small (few variables) and expand later
• Communicate the findings in an accessible way

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Future Directions

• Adding new administrative data (benefit to work
  transitions, tertiary education data)
• Enhancement or replacement of existing surveys
  (e.g. wages data from an employment survey)
• Expand research programme