essnet admindata methods of estimation for business statistics variables that cannot be obtained...
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ESSnet AdminData
Methods of estimation for business statistics variables that cannot be obtained from administrative data sources (WP3)
Duncan Elliott (UK), Danny van Elswijk (NL), Orietta Luzi (IT), Giampiero Siesto (IT), Brigitta Redling (DE), Daliute Kavaliauskiene (LT)
Aim of work package three
• Estimation for business statistics variables that cannot be obtained from administrative data sourcesNo similar variables and definitional differences
Admin data from a public authority
Focus on SBS and STS variables
• Objective: reduce burden for business
Planned work 2009 – 2010
• Literature Review • Identification of variables• Organising partnerships• Development of estimation methods• Testing• Review
Some terminology
• Admin data: administrative and accounts data• Register
Administrative: for administrative purposes
Statistical: processed for statistical purposes
• SurveySample: use of sample returns
Register based: direct use of administrative and derived variables
Business statistics variables
• Selection of Structural Business Statistics and Short Term Statistics
• WP3 members researched availability of admin data
• Variables selected for initial researchPayments for agency workersChanges in stocks of goods and servicesTotal purchases of goods and servicesNumber of employees in FTE New Orders
SBS
STS
Quality and regulatory requirements
• SBS (selected variables)Timeliness: 18 months from reference period
Period: annual
Details: class level and region by division
Quality information
Definition of each variable
• STS (new orders)Timeliness: one month and 20 or one month and 35
days from reference period
Details: reduced NACE code or division
Reducing burden
• Reduce number of enterprises sampled• Reduce number of questions• Reduce periodicity
units sampled or questions asked
Estimation methods
• Reducing burden from a more extensive use of admin data to reduce sampling fractionsPotential for only a small reduction
• Larger reductions of burdenDesign: ‘take none’ and/or ‘ask some strata
Estimation: Direct and Synthetic
Modelling at aggregate and/or unit level
Example
take some
take none
sample
• Derive model from sample• Apply model to ‘take none’ stratum or all non-sampled units
Quality of estimation
• AccuracyBias
Developing a decent model
• Assessing quality of estimates• Relevance for other Member States
• Testing using past data• Other quality issues addressed by other WPs
Future work and challenges (1)
• ‘Changes in stocks’ and ‘Purchases’Applying models to ‘take none’ stratum
Problems: modelling highly skewed data and data with high frequency of zeros, bias
• ‘New Orders’Applying models to ‘take none’ stratum
Problems: bias, timeliness of admin data
Future work and challenges (2)
• ‘Payments for agency workers’Sample employment agencies
Estimation using VAT
Problems: definitional issues for industrial and regional details
• ‘Number of employees in FTE’Combination of admin and sample survey sources
Problems: definitional issues, timeliness and periodicity
Beyond 2010
• Review of 2009 – 2010 work• Selection and analysis of further variables• Report on recommendations and best
practice
Thank you for listening …