1. Bálint Murai, HCSO National Accounts department Production Accounts section balint.murai@ksh.hu UNECE Group of Experts on National Accounts 6 - 9 May 2014. Geneva

3. Mexico Instituto Nacional de Estadística y Geografía

5.  The aim  estimate the performance of Informal economy and include in NA  give a proposal for a satellite account of Informal economy

6. Reference: Key Indicator of the Labour Market Database (KILM)

7.  The aim  estimate the performance of Informal economy and include in NA  give a proposal for a satellite account of Informal economy  ILO conceptual framework, SNA2008  Labour input are calculated separately:  informal sector and  informal employment outside the informal sector.

8.  Informal Economy, 2008: 25,5% of the GDP (8,7% Informal sector+16,8% Informal employment outside the informal sector)  The method applied here, however is not totally clear.

9. ENOE „Method of latent Variable” Hussmanns’ MATRIX ENAMIN GVA / Labour Input Method? FormalInformal Employment Sector Formal Informal

10. Calculation steps for the computation of data from ENOE and ENAMIN is not included. (Overview picture) GVA calculation scheme from ENAMIN is not totally clear (e.g. the use of IC/GVA ratios) Use of the Latent Variable method?

11. ENOE: asking the employees about the registration or status (formal/informal) of their employer. Reliable data for the employers? Different productivity in the formal and informal sector. Any correction while calculating the informal GVA from formal sector data?

12. Borderline between underground and informal On the informal activity there may be some underground activity (e.g. full time emloyment registered half-time, minimum wage, rest of the money is envelop payment.) In our experience enterprises tend to record the same data in the administrative records and in the survey. Even if we knew the informal employment the survey data could not be taken directly for calculating the informal production. Any correction for the Underground activity?

13. Canada Statistics Canada

15.  Summary of an exhaustive study, lot of information  Long tradition of estimating UE (Almost 3 decades of experience)  Upper bound estimation  Volume measure  All of the 3 GDP Approaches, Expenditure side is dominant

16. Informal sector Boundaries between informal and underground activity. Small businesses with revenues less than $30.000 do not have to charge VAT type taxes and are excluded form BR. Any studies for examining those who are above this limit, but not registered?

17. Upper bound method Maximum potential amount (Throughout the study, except for alcohol, tobacco, tips and rents) What’s the idea behind using the upper bound method? Why don’t you include them in the official GDP?

18. Skimming Skimming occurs when legitimate businesses fail to declare part of their business income. The type of tax evasion can be different by size and type of enterprises even if we rule out the largest companies. Threshold for potential tax evaders. (Annual revenues less than 2 million)  How did you arrive to chose this threshold?  Is this sub-set of enterprises supposed to be homogenous, or do you investigate them further by the main important indicators of production? (e.g. number of employees; type of activity?) Skimming rate How is it validated that the skimming rate is twice as much for the unincorporated enterprise than for the incorporated?

19. Allocation of skimming estimates Final step in the Reassessment estimation of skimming rates is unfortunately not very clear. How do you use the Tax audit data in the reconciliation process? Is it used only for adjusting the industrial classification or it changes the level?

20. Over-reporting of cost There are two ways of hiding business income:  under-report revenue or  over-report cost Underreporting of revenues was discussed deeply. Over-reporting of cost?

21. Mongolia National Statistical Office Of Mongolia

23.  Considerable effort (several projects) for estimating NOE and incorporate it into NA  EUROSTAT Tabular Approach framework  Data sources:  LFS+Household unincorporated enterprises producing for the market (HUEMs) survey  Informal sector survey  Survey on expert opinion of intentional distortion of business accounting  Establishment census  Tax audit data  Police, Health organisation, neighboring countries data

24. EUROSTAT Tabular Approach NOE by industries, but by N1-N7 is not included Data for  N4 legal person not surveyed  N7 other statistical deficiencies? Information of the GVA compilation for  Informal sector production (N1, N5)  HH’s production for own final use (N3)

25. HUEM Generally, the results of LFS are not reliable at a lower aggregation level. (Relative small sample and ignorance of data providers.) 2007/2008 ~7000 HHs were interviewed, number of HUEMs ~ 2200. Did you take this problem into consideration when evaluating HUEM’s data?

26. IndustriesNOEGDP Total economy (NOE+ GDP) Share of NOE Total1 332 093,108 414 504,509 746 597,6013,7 Agriculture8 060,201 203 348,001 211 408,200,7 Mining and quarrying305 661,801 981 970,102 287 631,9013,4 Manufacturing84 089,50708 931,60793 021,1010,6 Electricity, gas, steam and air conditioning supply 1 454,20174 302,80175 757,000,8 Water supply; sewerage, waste management and remediation activities 2 230,2033 051,7035 281,906,3 Construction82 511,70147 178,00229 689,7035,9 Wholesale and retail trade; repair of motor vehicles and motorcycles 528 875,901 310 622,101 839 498,0028,8 Transportation and storage186 841,20659 297,70846 138,9022,1 Accommodation and food service activities 28 266,1054 553,4082 819,5034,1 Other services104 102,302 141 249,102 245 351,404,6

27. NOE by industry There are 2 areas when one would expect a higher portion of NOE: Agriculture: 14% of total GVA, NOE: 1% of the total NOE. Unregistered producers, (e.g. estimation of cattle?) Other services: largest share in GDP: 25%, NOE: 8% Usually direct connection to HH, easiest to avoid tax. Personal services, tips, gratuities, etc.

28. Models

29. The results of the models in the presentation are close in 2010, but the lines are divergent in the earlier periode. Were there any study to examine the causes of these differences in macro models? Characteristics of N1-N7 activities can be different. This breakdown allows the investigations for more detailled analysis. Are there any connection between the NOE categories and the results of the models?

30. Netherlands Statistics Netherlands

32.  Long tradition of doing research on the NOE going back to the 1980s  Very clear paper, logical structure  Production approach; labour input data  Gives an overall view on the calculations  However, the ideas behind the assumptions and the applied ratios are not always presented.

33. Presentation framework NOE problem areas instead of TAE?

34. Cost fraud Part of Underground Activity why do you deal it separatley? You calculate it for the small enterprises (less than 10 employees). How do you calculate the share of cost fraud for (the selected items of) IC?

35. Newspaper articles Based on our experience, data in the newspapers are not always reliable and not suitable for generalisation. How do you validate the data in the papers? (Or do you use them only for identifying the potential NOE areas picked up by the press?) Expert guesses, estimations, opinions Do you use expert estimations from outside CBS, (e.g. information from lobby groups, research institutions, accountants)? How do you chose the experts and in which form are you interviewing them?

36. Potential double counting For illegal activities: 0,1% of the previously estimated data. Besides SUT what data sources did you apply? Are there any other area where you have such estimations? Which are the typical activities?

37. PROCESS TABLE Basic for NA Figures Adjustments Final NA Estimate INPUTPROCESSOUTPUT

38. PROCESS TABLE GDP & GNI Components Surveys and Censures Administrative Records Combined Data Extrapolations and Models Data Validation Conceptual NOE Balancing Production Expenditure Income GNI

39. Question for the discussion Some NOE type of adjustments may be included somewhere else in the calculation, mainly in the green cells. Collect typical borderline cases where it is particularly difficult to identify the amount of NOE which had already been calculated earlier somewhere else in the calculation. An example is agriculture (cultivated area X average yields)

40. Bálint Murai, HCSO National Accounts department Production Accounts section balint.murai@ksh.hu