1. ESSnet on Consistency of Concepts and applied Methods of Business and Trade-related Statistics: Statistical Units D. Filipponi – Istat (Italy) ________________________________________________________ ESSnet on consistency – Statistical Units Workshop Riga, 19 – 20 June 2012 Results of the quantitative part of the Inquiry on identification of inconsistencies between Member States

2. Content Why a quantitative part in the questionnaire The Statistical Unit Enterprise: questionnaire The Statistical Unit Enterprise: main results The Statistical Unit KAU: questionnaire The Statistical Unit KAU: main results Discussion

3. The quantitative part of questionnaire The aim: to give a quantitative information – measure- on the inconsistency - if any - of the statistical units among MS The approach: to evaluate the impact of the actions carried out by each country for the identification of the statistical unit as defined by the Regulation N.696/93 The considered statistical unit: Enterprise and KAU

4. The Statistical Unit Enterprise – The Questionnaire

5. The Statistical Unit Enterprise – Inquiry Results  The respondent countries have been divided into 3 groups according to their application of the enterprise definition (treatment)  The analysis has been carried out using three measures : units, employed, turnover GroupLabel in graphsDescription of treatment 1Part1 NO Part3 NONo treatment of LeUs 2Part1 YES Part3 NOThresholds or other methods to identify the productive units 3Part1 YES Part2 YES Both combination of LeUs and methods to identify the productive units Analysis of the impact of the applied treatment to identify Enterprises from the administrative LeUs.

6. The Statistical Unit Enterprise – Inquiry Results Percentual variation between LeUs and Enterprises ( units, employed and turnover) by type of treatment and country

7. The Statistical Unit Enterprise – Inquiry Results LeU and Enterprise (number) by NACE and country

8. The Statistical Unit Enterprise – Inquiry Results How much does the distribution “before and after” the treatment vary? And in which NACE codes?

9. The Statistical Unit Enterprise – Inquiry Results

10. Index of dissimilarity (of units, employed and turnover) by type of treatment and country

11. The Statistical Unit Enterprise – Inquiry Results Index of dissimilarity (of units, employed and turnover) by type of treatment and country

12. The Statistical Unit Enterprise – Inquiry Results We tried to explicate the index of dissimilarity of the distributions by NACE before and after the treatment as a function of the applied treatment of units and in relation with the countries who performed it. Used tool: Correspondence analysis

13. The Statistical Unit Enterprise – Inquiry Results Index of dissimilarity and treatment In terms of units

14. The Statistical Unit Enterprise – Inquiry Results Index of dissimilarity and treatment In terms of employed

15. The Statistical Unit Enterprise – Inquiry Results Index of dissimilarity and treatment In terms of turnover

16. The Statistical Unit Enterprise – Inquiry Results If we consider, where are defined as before, it is possible to analyze the differences between the two distributions for each NACE code (i) The differences have been grouped in classes: <-1 (-1,-0.5] [-0.5,0) 0 (0,0.5] (0.5,1] >1

17. The Statistical Unit Enterprise – Inquiry Results In terms of units

18. The Statistical Unit Enterprise – The Questionnaire Table 3 – Legal units by main economic activity code (only NACE codes that could be considered as "ancillary"

19. The Statistical Unit Enterprise – Inquiry Results Estimated number of legal units combined with other legal units by nace code and country via Generalized Linear Mixed Model. A generalized mixed model is a statistical model containing both fixed effects and random effects.fixed effects random effects These models are useful where repeated measurements are made on the same statistical units, or where measurements are made on clusters of related statistical units.statistical units ~N(0,G) g is a link function y is a vector of observations units is a vector of fixed effects The general matrix formulation is: and X and Z are matrices of regressors relating the observations Y to

20. The Statistical Unit Enterprise – Inquiry Results Here, and This model allows to take into account the correlation among units belonging to the same group (NACE SECTOR), with the matrix G1, G2 and G3, and the correlation among number employed and turnover, with the matrix G12 G13 and G23 The parameters have been estimated using the value of the respondent countries: ES, SE, LT, NO The Leu, employed and turnover have been estimated for the othercountries

21. The Statistical Unit Enterprise – Inquiry Results %Legal units combined with other legal units to create the enterprise by country

22. The Statistical Unit Enterprise – Inquiry Results Cluster of EU/EFTA country (respondent) using the distribution of the unit by NACE code, before and after the treatment.....

23. The Statistical Unit Enterprise – Inquiry Results

25. The Statistical Unit Enterprise – Conclusion 1.The application of the PART 1 of the definition of Ent (identification of “productive activity” – threshold-) brings: big variation between LeUs and Ents in terms of unit small variation in terms of employment and turnover 2.The application of the PART 3 of the definition of Ent (“combination of units”) brings; variations in terms of employment and turnover

26. The Statistical Unit Enterprise – Conclusion 3.The distribution of LeU with respect to the distribution of Ent (in Units): decrease the incidence of NACE “L” and “S” (<-1); high increase of “G”, “M” and “F” (>+1); medium increase of “C”, “H” and “Q” (+0.5 to +1); all the others are stable variation

27. The Statistical Unit KAU – The Questionnaire

30. The Statistical Unit KAU – Inquiry Results Number of enterprises, economic activities and KAU by country and domain

31. The Statistical Unit KAU – Inquiry Results Number of enterprises, economic activities and KAU by country

32. The Statistical Unit KAU – Inquiry Results KAU and Enterprise (number) by NACE and country

33. The Statistical Unit KAU – Inquiry Results KAU and Enterprise (employed) by NACE and country

34. The Statistical Unit KAU – Inquiry Results KAU and Enterprise (turnover) by NACE and country

35. The Statistical Unit KAU – Inquiry Results Index of dissimilarity of Number, Employed and Turnover by country

36. The Statistical Unit KAU – Inquiry Results Estimated KAU and KAU’ employed by NACE sector via Linear Mixed Model. A mixed model is a statistical model containing both fixed effects and random effects.fixed effectsrandom effects These models are useful where repeated measurements are made on the same statistical units, or where measurements are made on clusters of related statistical units.statistical units ~N(0,G) y is a vector of observations units is a vector of fixed effects The general matrix formulation is: andX and Z are matrices of regressors relating the observations Y to

37. The Statistical Unit KAU – Inquiry Results Here, and This model allows to take into account the correlation among units belonging to the same group (NACE SECTOR), with the matrix G1 and G2, and the correlation among number and employed, with the matrix G12 The parameters have been estimated using the value of the respondent countries: AT, ES, LT, PT, SE, SK, DK, EE, HU, IT, LV, and SI The KAU and the related employed have been estimated for the following countries BE, BG, CH, CY, CZ, DE, EL, FI, IE, LU, MT, NO, PL and RO

38. The Statistical Unit KAU – Inquiry Results

39. KAU and Estimated KAU by NACE for the respondent countries.

40. The Statistical Unit KAU – Inquiry Results KAU and Estimated KAU employed by NACE for the respondent countries.

41. The Statistical Unit KAU – Inquiry Results KAU and Enterprise by NACE for the EU/EFTA

42. The Statistical Unit KAU – Inquiry Results KAU and Enterprise employed by NACE for the EU/EFTA

43. The Statistical Unit KAU – Conclusion The results of the KAU analysis it is partial because of missing data for most of the biggest countries There are not evident differences between the Enterprise NACE distribution and KAU NACE distribution, even if the analysis carried out at section level could be partial

44. 44 Thanks for your attention!