Presentation on theme: "Why collect the same data twice?: Exploring the possibilities of using VAT data in the estimation of the Danish IIP Søren Kristensen Statistics Denmark."— Presentation transcript:
Why collect the same data twice?: Exploring the possibilities of using VAT data in the estimation of the Danish IIP Søren Kristensen Statistics Denmark
Data sources for three turnover indexes and the IIP Is it really the same data?
Differences between VAT and IIP – what are the issues? Is it really the same data?
Reasons for using VAT data instead of survey data Reduce burden on businesses Political focus on reducing burden Increase efficiency Produce more for less We already use VAT data Increase quality of the indicator Better coverage Imputation and grossing up
1. Replacement of sample data with VAT 2. Partial replacement of sample data with VAT data 3. Use of VAT data for imputation 4. Use of VAT for grossing up How to use VAT data in the estimation of the IIP – exploring the alternatives
Partial replacement of sample data with VAT Production index = turnover + change in inventories 2 questions: Is VAT a good replacement for sample turnover? How can inventories be measured and combined with administrative data?
VAT as replacement for survey data Taking account of difference in definitions – subtracting sale of traded goods
VAT as replacement for survey data Taking the difference in units into account Percentage of Sample Percentage of difference 1 KAU> 85 pct.15 pct > 1 KAU all in Sections B, C, D < 5 pct.15 pct > 1 KAU, at least one outside sections B,C,D < 7 pct70 pct Only 20 large units that really make a difference => Reasonably good prospects for the turnover variable
Measuring inventories - No administrative data available Collect data from the sample Problem of data consolidation Estimate change in inventory at a more aggregate level Collect data from a smaller sample,
Three models for using VAT data in the IIP TurnoverInventories Model 1: matched data VAT data Ca. 1200 units Sample data Ca 1200 units Model 2: aggregate estimates VAT data All units Sample data Less than 1200 Model 3: aggregate estimates + focus on significant units VAT data All units Sample Most significant units Sample data Less than 1200