Redesigning French structural business
statistics: first methodological studies
Bonn, september 2006
Ph. Brion
Insee
Outlines
General principles of the future device
A « specific » variable : the breakdown of turnover
Questions raised by the use of multiple sources
Page 2
General principles of the future device
The present system of structural business statistics
needs to be redesigned, for different reasons :
 in the current device, two « parallel » processes, one
statistical survey and another process using tax data
(annual income statements)
 administrative data (especially tax data) are available
earlier than before
 the concept of « enterprise group » needs to be used
in a more important way in business statistics
Page 3
General principles of the future device
INSEE has started a long-term project to take into
account these aspects
The idea is to use different kinds of administrative
data :
 annual income statements
 annual statements of payroll data
 external trade data
… and to keep a statistical survey for specific
variables
Page 4
GENERAL PRINCIPLES - CALENDAR
Survey
First results
01/01
Tax data
Other administrative data
Page 5
Definitive results
31/12
A « cornerstone » variable : the breakdown
of turnover
This variable is very important for business statistics :
 it is used for the national accounts
 an algorithm calculates the value of the APE code
(principal activity code, according to the NAF
nomenclature) depending on this breakdown
It is not available in tax data : necessity to get this
information in the statistical survey
Example : extract of the questionnaire of the annual
enterprise survey for the industrial sector (next slide)
Page 6
Page 7
Study of the efficiency of selective editing
for the variable « breakdown of turnover »
In fact, « n » variables
How to select units to be edited manually using a
score
Test of different types of «local» scores : using the
difference between raw data and data of previous
year, or the difference between raw data and an
average profile
Test of different ways of aggregating the «local» scores
to produce a global score
Two examples (next slides)
Page 8
Estimator of the turnover of the economic
branch « cars trade »
49800000
49700000
49600000
49500000
49400000
501-methodA1
49300000
501-methodA2
501-methodA3
49200000
501-methodA4
49100000
49000000
48900000
Page 9
14586
14157
13728
13299
12870
12441
12012
11583
11154
10725
10296
9867
9438
9009
8580
8151
7722
7293
6864
6435
6006
5577
5148
4719
4290
3861
3432
3003
2574
2145
1716
1287
858
429
0
48800000
Estimator of the turnover of the economic branch
« Food retail trade in specialized shops »
1800000
1780000
1760000
1740000
1720000
522-methodA1
1700000
522-methodA2
522-methodA3
522-methodA4
1680000
1660000
1640000
Page 10
14665
14246
13827
13408
12989
12570
12151
11732
11313
10894
10475
10056
9637
9218
8799
8380
7961
7542
7123
6704
6285
5866
5447
5028
4609
4190
3771
3352
2933
2514
2095
1676
1257
838
419
0
1620000
The variable « breakdown of turnover »
(continued)
For selective editing, we have to take into account the
fact that statistics using this variable are of two types :
- aggregates concerning economic sectors, as the
turnover of an economic sector k :

i
1APEk(i) * wi * Ti
- aggregates concerning economic branches, as the
turnover of the branch k :

i
Page 11
wi * Ti( APEk)
Some questions raised by the use of multiple
sources
Different flows of data arriving at different times
Is it possible to check data arriving first (from the
statistical survey) without administrative data ?
Especially, two « administrative » variables are important :
the turnover, the number of employees
Study of the possibility of using infra-annual data for these
two variables
Questions raised by the estimators used : F(Xi, wi, Yi)
where Xi are administrative data, Yi survey data, wi
weights
Questions raised by the calibration of estimators
(consequences on the weights wi due to the use of the
administrative data)
Page 12