an editing strategy for annual vat-turnover
DESCRIPTION
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 - PowerPoint PPT PresentationTRANSCRIPT
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An editing strategy for annual VAT-turnover
Montreal
June 18-21, 2007
*
Jeffrey Hoogland
Grietje van Haren
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– 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
Outline
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- Pressure from Dutch government and business community
- Use available register information instead of questionnaires
- Decrease response burden for small and medium sized companies
Register-based business statistics
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1. micro-editing of VAT data for fiscal units
2. conversion of VAT-turnover for fiscal units to VAT-turnover for enterprises
3. macro-editing of VAT-turnover for enterprises
An editing strategy for annual VAT-turnover
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– 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
Micro-editing of VAT-data for fiscal units
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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
Micro-editing of VAT-data for fiscal units
Example: d=1; c=9; year 2006
2.516 out of 3.150.000 monthly declarations 535 out of 2.740.000 quarterly declarations
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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
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Conversion of fiscal units to enterprises
fiscal unit fiscal person CBS person enterprise
fiscal unit
fiscal person
fiscal person
CBS person
CBS person
enterprise
enterprise
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Selectivity in available VAT-turnover
Table 1. Average edited SBS turnover (thousands of euros), for groups of enterprises
with, or without converted VAT data.
Average SBS
turnover
# SBS
records
Average SBS
turnover
# SBS
records
Number of
employees
No VAT VAT
Significance
T-test
1 411 48 238 269 0,041
2-4 665 52 518 190 0,269
5-9 1170 92 1053 219 0,348
10-19 2251 271 1849 460 0,019
20-49 5003 423 4212 653 0,017
50-99 11745 227 10587 188 0,139
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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.
VAT availableNo VAT available
5.000
4.000
3.000
2.000
1.000
0
Edited SBS-turnoverRaw SBS-turnover
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Table 2. Average raw SBS turnover (thousands of euros), for groups of enterprises
with, or without converted VAT data.
Average SBS
turnover
# SBS
records
Average SBS
turnover
# SBS
records
Number of
employees
No VAT VAT
Significance
T-test
1 674 47 673 267 0,996
2-4 894 51 971 190 0,750
5-9 1192 91 1348 219 0,393
10-19 2074 271 1881 460 0,255
20-49 3534 422 3471 652 0,631
50-99 4547 227 4705 188 0,629
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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
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- 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
Direct weighting of VAT-turnover
s Oiis
Piis
sss
ss
ss
yyun
uA
5,1 with ),( 133 cmmcmBoundary
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Table 3. Net turnover for 17 publication cells for builders with 1-99 employees.
Publication cell
SBS-turnover
VAT-turnover
Percentual Difference
1 583 522 -10,3 2 1.026 1.078 5,0 3 15.355 13.972 -9,0 4 587 502 -14,5 5 884 794 -10,1 6 2.611 2.081 -20,3 7 247 229 -7,3 8 2.710 2.308 -14,8 9 2.901 2.691 -7,2
10 2.545 2.543 -0,1 11 1.694 1.660 -2,0 12 287 248 -13,8 13 609 501 -17,8 14 1.917 1.570 -18,1 15 1.436 1.198 -16,6 16 2.469 2.468 0,0 17 808 642 -20,6
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Detecting influential inconsistencies
When comparing registers and surveys three groups are distinguished:
,BA ,\ BA and AB \ , where A and B are two different sources.
n
ii
Bi
Biii
n
ii
Ai
Aiii
BAyw
wyx
xw
wyxSF
11
,3 ,max
Example of score function for A B, e.g. PS VAT
Score functions are used to detect influential inconsistencies
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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