1. The use of VAT for monthly and quarterly turnover estimates A case study between NL and UK Pieter Vlag, Henk van de Velden Nino Mushkudiani all at: Statistics Netherlands Gareth James, Craig Orchard, Myrto Miltiadou all at: ONS

2. ESSnet Admin Data Workpackage : STS-estimates AIM: Describe best practices for estimation of STS-variables from adm. sources if due to the timeliness problem - the turnover variable is not yet (completely) available in the VAT registration. - the employment variables (wages, persons employed) are not yet (completely) available in the social security admin sources

3. ESSnet Admin Data Workpackage : STS-estimates OBSERVATION: Survey data: NSIs do have control about timeliness Admin data: NSIs don’t have (complete) control about timeliness -Practical implications: a.admin data for monthly and quarterly STS-estimates are (often) incomplete b.availability of admin data for STS-estimates differs per country CHALLENGE: Are recommendations possible, taking into account the ‘national’ differences ?

4. ESSnet Admin Data Workpackage : STS-estimates ACTIONS a.Case study between UK and NL (for details see paper) b.Contacts and visits to other countries (DE, EST, FI, IT, LT) to check whether experiences and solutions for NL-UK are recognizable. c.Development of a framework to be worked out in 2010-2011 by DE, EST, FI, LT, NL, UK

5. CASE STUDY NETHERLANDS until 2009: VAT reporter yearlyif VAT-remittance < € 1883,= year quarterly if VAT-remittance <= € 7000,= quarter monthly if VAT-remittamce > € 7000,= quarter + “special cases” 1.1.2009 threshold M -> Q increased to € 15000,= from 2009 – Q3 year if VAT-remittance < € 1883,= year Quarter general month voluntary + “special cases” ? TIMELINESS <= 30 days after reporting period

6. CASE STUDY NETHERLANDS Quarterly turnover estimates - benchmarking system (prototype producion) Monthly estimates – in research a.Survey largest enterprises + nowcasting (approach Stat. Finland) b.Survey largest enterprises + quarterly system (modified) c.Survey largest enterprises + small survey other ent., low aggregation levels after quarter (approach Stat. Sweden) VAT t-12VAT t datadata + est. MM MQ QM QQ Mx Qx xM xQ panels stopping starting

7. CASE STUDY UNITED KINGDOM -Monthly declarations (limited) + 3 three-month periods (“staggers”) -Timeliness: 40 days after declaration period

8. CASE STUDY UNITED KINGDOM - Research to be done (small enterprises) CONCLUSION: after splining the ‘staggers’ into monthly data -> similar methodological problems as in the Netherlands -If representative: approach Dutch benchmark methodology possible - If not: nowcasting or small survey

9. Framework to be worked out by DE, EST, IT, LT, NL, UK Inventory Legislation, availability NSI, Stability time-series Analyses Work Henk (NL), Craig (UK) adm. Data Example VAT 1 1 VAT can be replaced by empl VAT no complete coverage VAT Almost complete coverage transf to STS periods VAT only VAT < threshold without benchmarking with benchmarking Benchmarking for quality 1st res. Benchmarking for transf. Q -> M not representative or cannot be modelled representative or can be modelled no VAT possible Nowcasting (GREG-type) Est. Survey (t,t-x) (GREG-type) Est. VAT (t,t-x)

10. Example: The Netherlands 2010 - VAT Inventory Legislation, availability NSI, Stability time-series Analyses Like deliverable I - 2009 adm. Data Example VAT VAT no complete coverage VAT Almost complete coverage transf to STS periods VAT only VAT < threshold without benchmarking with benchmarking Benchmarking for quality 1st res. Benchmarking for transf. Q -> M not representative or cannot be modelled representative or can be modelled no VAT possible Nowcasting (GREG-type) Est. Survey (t,t-x) (GREG-type) Est. VAT (t,t-x) Quarter – deliverable II - 2009 Month

11. Challenge a.Establishing the link between availability admin data and STS- estimates b.When established, comparing practices to improve them c.Providing recommendations