1. Ph. Brion Insee Redesigning French structural business statistics: first methodological studies Bonn, september 2006

2. Page 2 Outlines  General principles of the future device  A « specific » variable : the breakdown of turnover  Questions raised by the use of multiple sources

3. Page 3 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

4. Page 4 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

5. Page 5 Survey Other administrative data Tax data 01/0131/12 First results Definitive results GENERAL PRINCIPLES - CALENDAR

6. Page 6 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)

7. Page 7

8. Page 8 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)

9. Page 9 Estimator of the turnover of the economic branch « cars trade »

10. Page 10 Estimator of the turnover of the economic branch « Food retail trade in specialized shops »

11. Page 11 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 : - aggregates concerning economic branches, as the turnover of the branch k :

12. Page 12 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(X i, w i, Y i ) where X i are administrative data, Y i survey data, w i weights  Questions raised by the calibration of estimators (consequences on the weights w i due to the use of the administrative data)