1 / 16

An editing strategy for annual VAT-turnover

An editing strategy for annual VAT-turnover. Montreal June 18-21, 2007 * Jeffrey Hoogland Grietje van Haren. Outline. Register-based business statistics Micro-editing of VAT-data for fiscal units Conversion of fiscal units to enterprises Macro-editing of VAT-turnover for enterprises

zandra
Télécharger la présentation

An editing strategy for annual VAT-turnover

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. An editing strategy for annual VAT-turnover Montreal June 18-21, 2007 * Jeffrey Hoogland Grietje van Haren

  2. Outline • Register-based business statistics • Micro-editing of VAT-data for fiscal units • Conversion of fiscal units to enterprises • Macro-editing of VAT-turnover for enterprises • Objectives

  3. Register-based business statistics • - Pressure from Dutch government and business community • Use available register information instead of questionnaires • - Decrease response burden for small and medium sized companies

  4. An editing strategy for annual VAT-turnover • micro-editing of VAT data for fiscal units • conversion of VAT-turnover for fiscal units to VAT-turnover for enterprises • macro-editing of VAT-turnover for enterprises

  5. Micro-editing of VAT-data for fiscal units • Fiscal units submit a VAT-declaration per month, quarter, or year • Those with large turnover tax or those that try to mislead the IRS have to report per month • For a fiscal unit i compute VAT-turnover for each time period t in year r and year r-1 • Detect outliers within a fiscal unit that (usually) report a substantial VAT-turnover

  6. Micro-editing of VAT-data for fiscal units • VAT-turnover of a fiscal unit substantial and possibly too large for a time period in year r if: • > d million euro and • > c× Median value of VAT-turnover across time periods of fiscal unit in year r and year r-1 Example: d=1; c=9; year 2006 2.516 out of 3.150.000 monthly declarations 535 out of 2.740.000 quarterly declarations

  7. VAT-turnover of a fiscal unit substantial and possibly too small for a time period in year r if: • Median value of VAT-turnover > d million euro and • VAT-turnover < Median value / c Example: d=1; c=9; year 2006 1.549 out of 3.150.000 monthly declarations 272 out of 2.740.000 quarterly declarations

  8. fiscal unit fiscal person fiscal person CBS person CBS person enterprise enterprise fiscal unit fiscal person CBS person enterprise Conversion of fiscal units to enterprises

  9. Selectivity in available VAT-turnover

  10. Figure 1. Box plots for raw and edited SBS-turnover (thousands of euros) for enterprises in building industry with 2-4 employees. There are two groups: SBS-records with VAT-turnover and SBS-records without VAT-turnover.

  11. Macro-editing of VAT-turnover • VAT-data incomplete • Weight VAT-turnover • Direct weighting if available VAT-data not selective • Reference aggregates • in design phase: VAT-, SBS-, and CT-turnover • in production phase: VAT-turnover of last year • Detect influential inconsistencies

  12. Direct weighting of VAT-turnover • - For a specific publication cell • - Stratify by enterprise size • - Detect outliers per stratum • - Using box plot criterium for i = log |yi-ymed| • - • - Direct weighting of outliers per stratum • - Direct weighting of non-outliers per stratum

  13. Table 3. Net turnover for 17 publication cells for builders with 1-99 employees.

  14. Detecting influential inconsistencies Score functions are used to detect influential inconsistencies Example of score function for A  B, e.g. PS VAT

  15. Objectives • Improve cooperation with tax authorities • Reduce differences in definitions and filling-in behaviour • Improve weighting and outlier detection for VAT-turnover • Use tax assessments and surveys to develop a treatment strategy for VAT-declarations • Reduce use of business surveys

More Related