QUALITY REPORT ON STRUCTURE OF EARNINGS SURVEY 2010 IN SLOVENIA

QUALITY REPORT ON STRUCTURE OF EARNINGS SURVEY 2010 IN SLOVENIA Prepared by: Miran Žavbi, Rudi Seljak Litostrojska 54, 1000 Ljubljana Tel. +386 1 234 08 10, +386 1 234 02 94 Fax. +386 1 241 53 44 E-mail: miran.zavbi@gov.si, rudi.seljak@gov.si December 2012

TABLE OF CONTENTS 1. Relevance... 4 2. Accuracy... 5 2.1. Sampling errors... 6 2.2. Non-sampling errors... 10 2.2.1. Coverage errors..10 2.2.2. Measurement errors 11 2.2.3. Non response errors.14 2.2.4. Model assumption errors 16 3. Punctuality and timeliness... 17 3.1. Punctuality... 17 3.2. Timeliness... 18 4. Accessibility and clarity... 19 4.1. Accessibility... 19 4.2. Clarity... 19 5. Comparability... 20 5.1. Geographical comparability... 20 5.2. Comparability over time... 20 6. Coherence... 21 ANNEX 1 SES 2010 QUESTIONNAIRE... 23 2

List of abbreviations: AJPES NR PRS SES SRDAP SURS ZAP/M Agency of the Republic of Slovenia for Public Legal Records and Related Services National Accounts Business Register Structure of Earnings Survey Statistical Register of Employment Statistical Office if the Republic of Slovenia Monthly Report on Paid Earnings by Legal Persons; national official data on earnings 3

1. Relevance The main users of Structure of Earnings Survey 2010 (SES 2010) results are the Institute of Macroeconomic Analyses and Development, Office for Equal Opportunities, the Bank of Slovenia, the Ministry of Labour, Family and Social Affairs, the Ministry of Finance, the Chamber of Commerce and Industry, the Employers' Association of Slovenia and trade unions. Important users are also units within the Statistical Office of the Republic of Slovenia (SURS). Other users of survey results are various research institutes, domestic and foreign companies, students and the media. Data published in the First Release are also sent to all users of data collected with the statistical survey Monthly Report on Earnings Paid by Legal Persons 1. The most important national users are the Ministry of Labour, Family and Social Affairs (The International Cooperation and European Affairs Service), the Institute of Macroeconomic Analyses and Development and the Employers' Association of Slovenia. Major foreign users of survey data are Eurostat, the European Central Bank, the International Monetary Fund and the International Labour Organisation. SES data also represent basis for many researchers dealing with earnings statistics. Structural data on earnings, including most wanted Gender Pay Gap, are one of the top data on earnings which are interesting not just for experts but also for general public. In general users are satisfied with data offered but as in 2006 also in 2010 two main weaknesses were mentioned; information on structure of earnings should be available more often than every four years (problem is solved by annual estimations, especially with annual Gender Pay Gap) and data availability which is almost one and half year after the reference period (for domestic users) or almost two years (for international comparison). 1 Official data on earnings in Slovenia. 4

2. Accuracy For SES 2010 the data collection stage was done by the Agency of the Republic of Slovenia for Public Legal Records and Related Services (AJPES), which collected the data with a special electronic questionnaire. Changed sampling plan in 2006 (to randomly select only business entities (or their units) and observe all employees in these business entities) was performed also for SES 2010. Sampling frame As a basis for creating the sampling frame, data from SRDAP and PRS were used to which data from two statistical surveys Monthly Report on Earnings Paid by Legal Persons and Monthly Report on Earnings Paid by Registered Natural Persons and statuses from other statistical surveys were added. In this case data from the above mentioned surveys were used only as auxiliary data in determining large units that will be sampled with certainty. In the final sampling frame 74,124 units were included. Size classes were determined on the basis of the data on the number of employees (source: SRDAP) as well as data on labour costs (source: final accounts estimated at the level of local units). Large business entities were those with 250 and more employees or with labour costs exceeding EUR 450,000. Other business entities were divided into three size classes: medium-sized (from 50 to 249 employees), small (from 10 to 49 employees) and micro (with fewer than 10 employees). As the second and third stratification variables activity (by the Standard Classification of Activities 2008 (NACE Rev. 2)) and cohesion regions were used. Sample The final sample size for the SES 2010 was 3,086 business entities or their units. Reporting units had to report data for all employees in the business entity or unit selected in the sample. In the distribution of sample units by strata, optimum allocation by the number of employees was used, while in those strata where the calculation by optimum allocation yielded fewer than 8 units 8 units were sampled, i.e. if there were fewer than 8 units in the stratum, all units were sampled. Systematic sample selection was applied, sorting the units within each stratum by five-digit Standard Classification of Activities 2008 (NACE Rev. 2) codes and thus ensuring implicit stratification at the lowest level of activity. Because in the case of the selected sampling plan it cannot be controlled for how many employees the unit will report data, it was decided to include control in the software application for reporting. If the business entities reported data for too low number of employees (according to data from SRDAP), the person reporting the data was warned. 5

Table 1: Number of units in the frame and in the sample by sections of activities and size classes 2 Sample frame Sample Share Activities m S M L Total m S M L Total m S M L Total A 486 97 16 0 599 16 16 14 0 46 0,03 0,16 0,88 0,08 B 59 24 5 2 90 16 16 5 2 39 0,27 0,67 1,00 1,00 0,43 C 7549 1493 569 105 9716 236 237 255 105 833 0,03 0,16 0,45 1,00 0,09 D 156 52 18 10 236 16 16 16 10 58 0,10 0,31 0,89 1,00 0,25 E 210 85 53 4 352 16 16 20 4 56 0,08 0,19 0,38 1,00 0,16 F 9554 981 143 16 10694 135 73 48 16 272 0,01 0,07 0,34 1,00 0,03 G 14082 1952 217 10 16261 207 141 72 10 430 0,01 0,07 0,33 1,00 0,03 H 4182 677 109 15 4983 62 54 40 15 171 0,01 0,08 0,37 1,00 0,03 I 4726 427 52 8 5213 66 28 17 8 119 0,01 0,07 0,33 1,00 0,02 J 2121 274 47 9 2451 30 23 21 9 83 0,01 0,08 0,45 1,00 0,03 K 1087 296 60 18 1461 17 20 26 18 81 0,02 0,07 0,43 1,00 0,06 L 842 64 9 0 915 16 16 9 0 41 0,02 0,25 1,00 0,04 M 8834 574 65 8 9481 112 40 26 8 186 0,01 0,07 0,40 1,00 0,02 N 1549 194 71 14 1828 22 16 25 14 77 0,01 0,08 0,35 1,00 0,04 O 389 457 214 25 1085 16 37 72 25 150 0,04 0,08 0,34 1,00 0,14 P 1118 535 505 9 2167 19 50 121 9 199 0,02 0,09 0,24 1,00 0,09 Q 1963 188 187 34 2372 24 17 61 34 136 0,01 0,09 0,33 1,00 0,06 R 1027 190 31 7 1255 16 16 15 7 54 0,02 0,08 0,48 1,00 0,04 S 2848 105 12 0 2965 31 16 8 0 55 0,01 0,15 0,67 0,02 Total 62782 8665 2383 294 74124 1073 848 871 294 3086 0,02 0,10 0,37 1,00 0,04 Table 2: Number of employees in the frame and in the sample by sections of activities and size classes 2 Sample frame Sample Share Activities m S M L Total m S M L Total m S M L Total A 1249 2435 1357 0 5041 34 400 1213 0 1647 0,03 0,16 0,89 0,33 B 184 503 481 1752 2920 46 363 481 1752 2642 0,25 0,72 1,00 1,00 0,90 C 20042 31475 62008 69222 182747 588 4928 28440 69222 103178 0,03 0,16 0,46 1,00 0,56 D 441 1212 1684 4260 7597 33 376 1506 4260 6175 0,07 0,31 0,89 1,00 0,81 E 669 2086 5065 1487 9307 50 367 1830 1487 3734 0,07 0,18 0,36 1,00 0,40 F 22891 18583 13739 6034 61247 307 1638 4316 6034 12295 0,01 0,09 0,31 1,00 0,20 G 36781 38402 20806 5996 101985 575 3083 7123 5996 16777 0,02 0,08 0,34 1,00 0,16 H 10923 14621 11007 7459 44010 151 1257 4030 7459 12897 0,01 0,09 0,37 1,00 0,29 I 11640 7502 4931 3244 27317 169 482 1756 3244 5651 0,01 0,06 0,36 1,00 0,21 J 5001 5450 5020 5298 20769 91 486 2002 5298 7877 0,02 0,09 0,40 1,00 0,38 K 3147 5657 5798 9027 23629 45 355 2468 9027 11895 0,01 0,06 0,43 1,00 0,50 L 1809 1178 902 0 3889 42 254 902 0 1198 0,02 0,22 1,00 0,31 M 19031 10714 6011 2824 38580 235 749 2345 2824 6153 0,01 0,07 0,39 1,00 0,16 N 3568 4119 7548 8933 24168 50 289 2500 8933 11772 0,01 0,07 0,33 1,00 0,49 O 1623 11838 20718 17949 52128 62 923 7472 17949 26406 0,04 0,08 0,36 1,00 0,51 P 3549 14779 41583 3463 63374 74 1287 10189 3463 15013 0,02 0,09 0,25 1,00 0,24 Q 4064 4685 18819 23878 51446 69 446 5969 23878 30362 0,02 0,10 0,32 1,00 0,59 R 2132 3818 2957 2249 11156 36 382 1328 2249 3995 0,02 0,10 0,45 1,00 0,36 S 5423 1856 1120 0 8399 53 232 693 0 978 0,01 0,13 0,62 0,12 Total 154167 180913 231554 173075 739709 2710 18297 86563 173075 280645 0,02 0,10 0,37 1,00 0,38 2.1. Sampling errors In the tables 3 to 12 coefficients of variations are shown in percentage for variables 4.2 (Gross earnings in the reference month) and 4.3 (Average gross hourly earnings in the reference month) for different individual breakdowns. In the tables from 3 to 7 coefficients of variations are calculated for business entities with 1 and more employees while in the tables from 8 to 12 for business entities with 10 and more employees. In all tables from 3 to 12 data are for all activities A-S. 2 m micro units (less than 10 employees) S small units (from 10 to 50 employees) M medium units (from 51 to 250 employees) L large units (251 and more employees) 6

Table 3: Coefficients of variations for variable 4.2 Gross earnings in the reference month and variable 4.3 Average gross hourly earnings in the reference month by full time and part time employees and by gender for business entities with 1 and more employees Monthly earnings (4.2) Full time employees Part time employees Hourly earnings (4.3) Slovenia 0.7% 0.7% Men 0.8% 0.8% Women 0.8% 0.8% Total 0.7% 0.7% Men 0.8% 0.8% Women 0.8% 0.8% Total 3.2% 2.2% Men 6.2% 5.1% Women 2.3% 2.0% Table 4: Coefficients of variations for variable 4.2 Gross earnings in the reference month and variable 4.3 Average gross hourly earnings in the reference month by sections of activities for business entities with 1 and more employees Monthly earnings (4.2) Hourly earnings (4.3) Slovenia 0.7% 0.7% A Agriculture, forestry and fishing 5,0% 4,9% B Mining and quarrying 0,7% 0,7% C Manufacturing 0,9% 0,9% D Electricity,gas,steam,air cond.supply 1,9% 1,8% E Water suppl;sewer.,wst.manag.,remed.act 2,6% 2,6% F Construction 2,7% 2,5% G Wholesale,retail;repair of mot.vehicles 2,5% 2,5% H Transportation and storage 2,5% 2,4% I Accommodation and food ser.activities 2,5% 2,2% J Information and communication 3,3% 3,4% K Financial and insurance activities 2,2% 2,1% L Real estate activities 11,9% 11,2% M Professional,scientific,technical act. 4,2% 4,0% N Administrative and support service act. 4,7% 4,9% O Public admin.defence;compulsory soc.sec. 1,0% 1,0% P Education 1,8% 1,7% Q Human health and social work activities 1,4% 1,4% R Arts,entertainment and recreation 3,2% 3,2% S Other service activities 14,0% 13,8% Table 5: Coefficients of variations for variable 4.2 Gross earnings in the reference month and variable 4.3 Average gross hourly earnings in the reference month by occupation for business entities with 1 and more employees Monthly earnings (4.2) Hourly earnings (4.3) Slovenia 0.7% 0.7% 0 Armed forces occupations 0,0% 0,0% 1 Managers 2,0% 2,0% 2 Professionals 0,8% 0,8% 3 Technicians and associate professionals 0,8% 0,8% 4 Clerical support workers 0,8% 0,7% 5 Service and sales workers 1,1% 1,1% 6 Skilled agricultural, forestry and fishery workers 3,0% 3,1% 7 Craft and related trades workers 0,9% 0,8% 8 Plant and machine operators, and assemblers 1,0% 1,0% 9 Elementary occupations 1,0% 0,9% 7

Table 6: Coefficients of variations for variable 4.2 Gross earnings in the reference month and variable 4.3 Average gross hourly earnings in the reference month by age bands for business entities with 1 and more employees Monthly earnings (4.2) Hourly earnings (4.3) Slovenia 0.7% 0.7% 1 Under 20 years 1,3% 0,7% 2 20 to 29 years 0,8% 0,8% 3 30 to 39 years 0,9% 0,9% 4 40 to 49 years 0,8% 0,8% 5 50 to 59 years 1,0% 1,0% 6 60 years and over 1,7% 1,7% Table 7: Coefficients of variations for variable 4.2 Gross earnings in the reference month and variable 4.3 Average gross hourly earnings in the reference month by size class for business entities with 1 and more employees Monthly earnings (4.2) Hourly earnings (4.3) Slovenia 0.7% 0.7% 1 Less than 10 employees 2,9% 2,8% 2 10 to 49 employees 1,7% 1,7% 3 50 to 249 employees 1,0% 1,0% 4 250 to 499 employees 1,1% 1,0% 5 500 to 999 employees 0,8% 0,8% 6 1000 and more employees 0,6% 0,7% Table 8: Coefficients of variations for variable 4.2 Gross earnings in the reference month and variable 4.3 Average gross hourly earnings in the reference month by full time and part time employees and by gender for business entities with 10 and more employees Monthly earnings (4.2) Full time employees Part time employees Hourly earnings (4.3) Slovenia 0,6% 0,6% Men 0,7% 0,7% Women 0,7% 0,7% Total 0,6% 0,6% Men 0,7% 0,7% Women 0,7% 0,7% Total 3,5% 2,7% Men 11,3% 9,3% Women 2,0% 1,7% 8

Table 9: Coefficients of variations for variable 4.2 Gross earnings in the reference month and variable 4.3 Average gross hourly earnings in the reference month by sections of activities for business entities with 10 and more employees Monthly earnings (4.2) Hourly earnings (4.3) Slovenia 0.6% 0.6% A Agriculture, forestry and fishing 5,5% 5,4% B Mining and quarrying 0,7% 0,7% C Manufacturing 0,8% 0,8% D Electricity,gas,steam,air cond.supply 1,8% 1,7% E Water suppl;sewer.,wst.manag.,remed.act 2,6% 2,6% F Construction 3,1% 2,9% G Wholesale,retail;repair of mot.vehicles 2,7% 2,7% H Transportation and storage 2,3% 2,2% I Accommodation and food ser.activities 2,1% 2,1% J Information and communication 2,8% 2,8% K Financial and insurance activities 2,1% 2,1% L Real estate activities 4,5% 4,4% M Professional,scientific,technical act. 4,6% 4,6% N Administrative and support service act. 2,4% 1,9% O Public admin.defence;compulsory soc.sec. 1,0% 1,0% P Education 1,3% 1,3% Q Human health and social work activities 1,3% 1,2% R Arts,entertainment and recreation 3,0% 3,0% S Other service activities 14,7% 14,8% Table 10: Coefficients of variations for variable 4.2 Gross earnings in the reference month and variable 4.3 Average gross hourly earnings in the reference month by occupation for business entities with 10 and more employees Monthly earnings (4.2) Hourly earnings (4.3) Slovenia 0.6% 0.6% 0 Armed forces occupations 0,0% 0,0% 1 Managers 1,4% 1,3% 2 Professionals 0,7% 0,7% 3 Technicians and associate professionals 0,7% 0,7% 4 Clerical support workers 0,7% 0,7% 5 Service and sales workers 1,1% 1,1% 6 Skilled agricultural, forestry and fishery workers 3,7% 3,8% 7 Craft and related trades workers 0,9% 0,8% 8 Plant and machine operators, and assemblers 1,1% 1,0% 9 Elementary occupations 0,9% 0,8% Table 11: Coefficients of variations for variable 4.2 Gross earnings in the reference month and variable 4.3 Average gross hourly earnings in the reference month by age bands for business entities with 10 and more employees Monthly earnings (4.2) Hourly earnings (4.3) Slovenia 0.6% 0.6% 1 Under 20 years 1,3% 0,7% 2 20 to 29 years 0,7% 0,6% 3 30 to 39 years 0,7% 0,7% 4 40 to 49 years 0,7% 0,7% 5 50 to 59 years 0,8% 0,8% 6 60 years and over 1,5% 1,5% 9

Table 12: Coefficients of variations for variable 4.2 Gross earnings in the reference month and variable 4.3 Average gross hourly earnings in the reference month by size classes for business entities with 10 and more employees Monthly earnings (4.2) Hourly earnings (4.3) Slovenia 0.6% 0.6% 1 Less than 10 employees / / 2 10 to 49 employees 1,7% 1,7% 3 50 to 249 employees 1,0% 1,0% 4 250 to 499 employees 1,1% 1,0% 5 500 to 999 employees 0,8% 0,8% 6 1000 and more employees 0,6% 0,7% 2.2. Non-sampling errors 2.2.1. Coverage errors There are no difference between the reference and the study population. For national purposes for business entities and employees in activities A and S data were also collected and published. Moreover also data for business entities with less than 10 employees were included. On total there was 5.5% of over-coverage among business entities and 1.9% among employees (see table 13). Higher over-coverage is because of the increased number of business entities without paid wages mainly because of the crises. There were some responses from units which were not in the sample but they were in the frame. Undercoverage was not detected. Table 13: Over-coverage rates by sections of activities Over-coverage rates by business entities by employees Slovenia 5.5% 1.9% A 4.6% 2.4% B 0.0% 0.0% C 5.1% 1.1% D 3.1% 6.9% E 0.0% 0.0% F 2.7% 0.7% G 6.8% 2.3% H 1.5% 1.8% I 4.1% 3.4% J 3.4% 1.8% K 4.6% 4.4% L 19.1% 9.7% M 5.2% 3.3% N 11.9% 4.0% O 4.7% 1.3% P 8.2% 0.5% Q 7.6% 1.9% R 8.7% 3.1% S 9.4% 7.9% 10

Table 14: Over-coverage rates by size classes Over-coverage rates by business entities by employees Slovenia 5.5% 1.9% Less than 10 employees 6.1% 4.1% 10 to 49 employees 3.0% 1.2% 50 to 249 employees 4.5% 1.3% 250 to 499 employees 6.8% 2.5% 500 to 999 employees 0.2% 1.6% 1000 and more employees 1.3% 1.1% 2.2.2. Measurement errors Collection of the data was combination of existing sources, mainly from SRDAP, and questionnaire (Annex1). The source for each variable is described in table 15. Table 15: Sources for the SES 2010 variables Variable number in Variable name the EU Regulation 1. Information about the local unit to which the sampled employees are attached 1.1. Geographical location of the local unit (NUTS-1) How was the information collected For national purposes data collected on NUTS-3 level - PRS 1.2. Size of the business entity to which the PRS, SRDAP local unit belongs 1.3. Principal economic activity of the local PRS unit (NACE Rev. 2) 1.4. Form of economic and financial control PRS 1.5. Collective pay agreement ZAP/M 1.6. Total number of employees in the local unit in the reference month (optional) 1.7. Affiliation of the local unit to a group of business entities (optional) SRDAP Data were not collected Question number in the survey questionnaire or formula 2. Information on individual characteristics of each employee in the sample relating to the reference month 2.1. Sex SRDAP 2.2. Age SRDAP 2.3. Occupation (ISCO-08) SRDAP 2.4. Management or supervisory position (optional) 2.5. Highest successfully completed level of education and training (ISCED 97) Data were not collected 11 SRDAP 2.6. Length of service in the business entity Included in the questionnaire 2 2.7. Contractual working time (full-time or SRDAP part-time) 2.7.1. Share of a full-timer s normal hours SRDAP

Table 15: Sources for the SES 2010 variables (continued) 2.8. Type of employment contract SRDAP 2.9. Citizenship (optional) Data were not collected 3. Information on working periods for each employee in the sample 3.1. Number of weeks in the reference year to which the gross annual earnings relate 3.2. Number of hours paid during the reference month 3.2.1. Number of overtime hours paid in the reference month Included in the questionnaire 13 Included in the questionnaire and calculated 7, 9 Included in the questionnaire 8 3.3. Annual days of holiday leave Included in the questionnaire 16 3.4. Other annual days of paid absence Data were not collected (optional) 4. Information on earnings for each employee in the sample 4.1. Gross annual earnings in the reference year 4.1.1. Annual bonuses and allowances not paid in each pay period Included in the questionnaire and calculated Included in the questionnaire and calculated 10, 12, 15, 17, 18, 19 11, 15 4.1.2. Annual payments in kind (optional) Data were not collected 17, 18, 19 4.2. Gross earnings in the reference month Included in the questionnaire and calculated 4.2.1. Earnings related to overtime Included in the questionnaire 4 4.2.2. Special payments for shift work Included in the questionnaire 5 4.2.3. Compulsory social contributions and Data were not collected taxes paid by the employer on behalf of the employee (optional) 4.2.3.1. Compulsory social-security Data were not collected contributions (optional) 4.2.3.2. Taxes (optional) Data were not collected 4.3. Average gross hourly earnings in the reference month Included in the questionnaire and calculated Calculated from 3, 6, 7, 9 3, 6 5. Grossing-up factors 5.1. Grossing-up factor for the local unit 5.2. Grossing-up factor for the employees Data were collected electronically by AJPES. Every question in the questionnaire contains the definition of what must be included in and excluded from the data. Methodology and definitions were published in Official Journal as well as on SORS and AJPES internet sites. First logic control was built in application of data collection where mistakes were hard or soft (colored in red or yellow). Data could not be transferred with hard mistakes. Mistakes are described in table 16. In case of unit non-response reporting units were notified to send the data. 12

Table 16: Set of logic test for SES 2010 questionnaire and number of mistakes for each variable from the questionnaire Mistake Type 3 4 Number of Description mistakes Absolute Relative Total 278,511 100.0% N1 H PIN module 542 0.2% N2 H Date of birth less than 1 January 1925 11 0.0% N3 H SN002>1 January 2011 868 0.3% N4 H SN004>0 AND SN003=0 OR SN005>0 AND SN003=0 OR SN006>0 AND SN003=0 423 0.2% N5 H SN004>SN003 OR SN005>SN003 OR SN006>SN003 1,282 0.5% N6 S SN003>20000 51 0.0% N7 S SN004>SN003*0.5 585 0.2% N8 S SN005>SN003*0.5 934 0.3% N9 S SN006>SN003*0.7 4,602 1.7% N10 H SN003>0 AND SN007=0 OR SN007>0 AND SN003=0 3,033 1.1% N11 H SN004>0 AND SN008=0 OR SN008>0 AND SN004=0 621 0.2% N12 H SN006>0 AND SN009=0 OR SN009>0 AND SN006=0 462 0.2% N13 H SN008>0 AND SN007=0 73 0.0% N14 H SN009>0 AND SN007=0 183 0.1% N15 H SN008>SN007 75 0.0% N16 H SN009>SN007 382 0.1% N17 S SN008=0 AND SN007>200 1,398 0.5% N18 S SN008>0 AND SN007>300 341 0.1% N19 S SN008>30 5,419 1.9% N20 H SN003>0 AND SN010=0 2,191 0.8% N21 H SN010<SN003 2,335 0.8% N22 H SN011>0 AND SN010=0 241 0.1% N23 H SN012>0 AND SN010=0 340 0.1% N24 H SN011>SN010 1,296 0.5% N25 H SN012>SN010 923 0.3% N26 S SN011>SN010*0.6 1,537 0.6% N27 S SN012>SN010*0.7 2,361 0.8% N28 H SN010>0 AND SN013=0 OR SN013>0 AND SN010=0 1,334 0.5% N29 H SN014>0 AND SN013=0 336 0.1% N30 H SN014>SN013 993 0.4% N31 S SN014=0 AND SN013>2400 (200 per month) 872 0.3% N32 S SN014>0 AND SN013>3600 (300 per month) 385 0.1% N33 S SN014>300 (25 per month) 5,057 1.8% N34 S SN015>1500 16,710 6.0% N35 S SN016>60 3,152 1.1% N36 S SN017>SN010*0.4 1,631 0.6% N37 S SN018>SN010*0.7 1,418 0.5% N38 S SN019>SN010*0.6 2,538 0.9% N39 H SN010=0 2,958 1.1% N40 H SN002<Date in SN001 + 15 years 113 0.0% N41 H SN014<SN008 595 0.2% N42 H SN013<SN007 3,470 1.2% N43 H SN012<SN006 480 0.2% N44 H SN003>50000 23 0.0% N45 H SN008>200 21 0.0% N46 H SN008=0 AND SN007>300 508 0.2% N47 H SN008>0 AND SN007>400 282 0.1% 3 H hard mistake S soft mistake 4 SN serial number of the question from the questionnaire 13

Table 16: Set of logic test for SES 2010 questionnaire and number of mistakes for each variable from the questionnaire (continued) Number of Mistake Type Description mistakes N48 H SN016>100 2,969 1.1% N49 S SN018=0 58,899 21.1% N50 S SN019=0 59,917 21.5% N51 S SN015=0 35,374 12.7% N52 H SN003/SN007<0.5 1,713 0.6% N53 H SN010/SN013<0.5 677 0.2% N54 H SN004/SN008<0.5 278 0.1% N55 H SN005>0 AND SN016=0 16,780 6.0% N56 S SN016>0 AND SN015=0 26,519 9.5% The highest share of mistakes was in N49 (payments for meals) and N50 (payments for travel between home and work) where most of the employees are entitled for these payments but not all while logic controls was set as obligatory for all employees. Therefore both logic controls were set as soft error, where confirmation of correct data from reporting person was necessary. Also high share of mistakes (21.6 %) was in N51 because of holiday bonus where there is limit set by law. For payments below or equal to the limit just income taxes are paid but above the limit also social security contributions must be paid. Logic control was set on the limit set by law but many companies paid above the limit. All hard mistakes detected through the system of logical controls were corrected by the companies themselves. Where a lot of soft mistakes occurred (e.g. N34) companies were contacted and data were double checked. Variables from existing sources were not controlled, they have their own checking. Data from existing sources were put through code list to check possible miscoding. 2.2.3. Non response errors - UNIT RESPONSE RATE The overall unit response rate was 72.6%. Response rate concerning employees was 79.8%. Response rates by activities are in the table 17. 14

Table 17: Response rates by section of activities Unit response rate Response rate by employees Slovenia 72,6% 79,8% A 61,9% 71,3% B 69,4% 91,7% C 72,0% 80,6% D 87,0% 92,3% E 83,0% 91,9% F 48,5% 54,7% G 77,3% 80,3% H 57,9% 65,1% I 59,5% 69,0% J 82,7% 86,7% K 83,1% 86,6% L 76,3% 82,2% M 71,8% 77,2% N 68,5% 82,2% O 95,1% 98,2% P 83,1% 84,8% Q 88,6% 92,8% R 88,0% 88,9% S 51,0% 54,4% In the sample key-responders were selected which represent units from which respond is necessary to obtain the sample quality. In case of unit non-response re-weighting was used. - ITEM RESPONSE RATE For most mandatory variables, including Gross earnings in the reference month (4.2), data were expected while filling in the electronic questionnaire. This variable was not included in the logic control as hard mistake, because it is possible for employee not to have been paid in October. Missing data were checked at the business entities and corrected if necessary. No imputation was performed in case of item non-response. - OVERALL IMPUTATION RATE Most of the mandatory variables (those collected with the questionnaire) were included in the logic control and mostly of them were treated as hard mistakes in case of item non-response. Also the questionnaire could not be delivered if these variables were not filled in correctly. For those variables no imputation were performed, just statistical editing. Overall imputation rate was 0.9%, and including editing 4.8%. 15

Table 18: Statistical imputation rate including editing for mandatory variables Variable number in the EU Regulation Rate of statistical editing 1.1 0.0% 1.2. 0.0% 1.3. 0.0% 1.4. 0.0% 1.5. 1.8% 2.1. 1.3% 2.2. 0.0% 2.3. 1.4% 2.5. 4.4% 2.6. 0.8% 2.7. 0.2% 2.7.1. 0.2% 2.8. 1.3% 3.1. 9.2% 3.2. 9.7% 3.2.1. 9.5% 3.3. 0.7% 4.1. 7.3% 4.1.1. 0.0% 4.2. 7.3% 4.2.1. 9.4% 4.2.2. 9.5% 2.2.4. Model assumption errors No models were used. 16

3. Punctuality and timeliness 3.1. Punctuality The responding units were notified with a circular letter about being included in the sample, which was sent to them by mail or by post where mail was unknown. The circular letter contained the general information about the survey and obligation by Law of Statistics to fill the questionnaire and for which variables data are already collected from the existing sources. The guidelines and definitions were published on internet sites of SURS and AJPES. The questionnaire was open for filling it in on 1 March 2011. The deadline for filling in the questionnaire was set to 31 march 2011, but the final deadline was then change to 3 May 2011. After the deadline non responded business entities were notified by mail. In July and August just non-responded key-responders were contacted to send the data. The data collection ended in October 2011. Data delivery is shown in Graph 1. Graph 1: SES 2010 data delivery by weeks (in %) 5 100% 90% 80% 70% 60% 50% 40% 30% number of business entitites number of employees 20% 10% 0% 9 11 13 15 17 19 21 23 25 27 31 33 40 42 week numbers in 2011 From end of October 2011 to February 2012 data were analysed and some double checking with responding units were done. In March 2012 the data were weighted and basic tables were made. Through period from April until June 2012 other tables were produced and checked. First Release was sent out on 29 June 2012 as a provisional data 6. First release contained data on hourly, monthly and annual earnings per employee by activities, sex, main occupational and 5 week 9 starts from 28 February 2011 and week 42 ends with 23 October 2011 6 http://www.stat.si/eng/novica_prikazi.aspx?id=4820 17

educational groups, age and size classes, including short methodological explanations. On the same day data were put in Eurostat's standard scheme and sent to Eurostat via Edamis. 3.2. Timeliness Data were published on 29 June 2012 which is 18 months after the reference period as it is stated in the EU regulation. Data were published in Slovenia and sent to Eurostat on the same day. 18

4. Accessibility and clarity 4.1. Accessibility According to the SURS publishing policy, data were first published in First Release (in June 2012) as provisional data, including explanations and short methodology. More detailed results are planned to be published in 2013 in Rapid Reports (in electronic version) with tables, graphs, methodological explanations and definitions. First release (and later Rapid Reports) is sending to all our users of ZAP/M statistical survey. To the reporting units no results will be sent, only on their explicit request. Individual data are also available in the safe room at SURS. 4.2. Clarity Subscribed users on ZAP/M statistical survey received an e-mail notification of First release of provisional SES data. Publication with final data will be also sent to all ZAP/M statistical survey. Only electronic version will be available on SURS internet sites, free of charge. After the publication of final data in first quarter 2013, it is planned to publish detailed methodological explanations. 19

5. Comparability 5.1. Geographical comparability SES 2010 data were collected in accordance with EU regulations with some exceptions listed below: - Also business entities with less than 10 employees were included because of national purposes. In Slovenia there are many small business entities; by SES 2010 sample frame 84.7% of all business entities, which represents 20.8% employees. - Apprentices were excluded due to negligible phenomena and because units would face a problem filling the data. - By the regulation payments paid by employer at a reduced rate are to be excluded. In Slovenia there are a lot of payments at a reduced rate because all sickness leave which is paid by employer (up to 30 days) is paid at a reduced rate (except in case of injuries at work). Therefore data on monthly and annual earnings were collected separately for total and payments at a reduced rate. For EU purposes payments at a reduced rate were deduct from total payments (the same procedure was applied for paid hours and paid hours at a reduced rate). - Holiday bonus in Slovenia is not treated as wage component. In tables for Eurostat holiday bonus was included but for national purposes holiday bonus was excluded from annual earnings data and shown separately. - Wages in kind in Slovenia is not treated as wage component though wages in kind in Slovenia represent high share in total costs because of payments for travel between home and work. In Slovenia most of employees are entitled to receive payments for travel between home and work by different ways (e.g. as cash payments, bus or train tickets). In tables for Eurostat payments in kind were included but for national purposes payments in kind were excluded from annual earnings data and were shown separately. 5.2. Comparability over time In comparison with SES 2006, in SES 2010 almost all methods were the same. There were small changes in data collection (wages in kind were added in the questionnaire). 20

6. Coherence Table 19: Coherence between gross annual earnings per employee from SES 2010 and wages and salaries per employee from National Accounts SES NA SES / NA Slovenia 20188 20787 97,1 A Agriculture, forestry and fishing 16770 14471 115,9 B Mining and quarrying 26743 26586 100,6 C Manufacturing 18109 18652 97,1 D Electricity,gas,steam,air cond.supply 29277 31101 94,1 E Water suppl;sewer.,wst.manag.,remed.act 19968 20255 98,6 F Construction 15909 16371 97,2 G Wholesale,retail;repair of mot.vehicles 18959 20081 94,4 H Transportation and storage 18826 19998 94,1 I Accommodation and food ser.activities 14057 14986 93,8 J Information and communication 28271 29343 96,3 K Financial and insurance activities 29638 30308 97,8 L Real estate activities 20756 23500 88,3 M Professional,scientific,technical act. 24069 27409 87,8 N Administrative and support service act. 14017 15773 88,9 O Public admin.defence;compulsory soc.sec. 24222 24307 99,6 P Education 22708 22797 99,6 Q Human health and social work activities 23122 22748 101,6 R Arts,entertainment and recreation 23729 24500 96,9 S Other service activities 16520 18745 88,1 Table 20: Coherence between number of employees from SES 2010 and from National Accounts SES NA SES / NA Slovenia 720457 783700 91,9 A Agriculture, forestry and fishing 4719 7000 67,4 B Mining and quarrying 3075 2900 106,0 C Manufacturing 175938 184700 95,3 D Electricity,gas,steam,air cond.supply 7970 7900 100,9 E Water suppl;sewer.,wst.manag.,remed.act 8571 9400 91,2 F Construction 60083 69000 87,1 G Wholesale,retail;repair of mot.vehicles 100738 106700 94,4 H Transportation and storage 41986 44900 93,5 I Accommodation and food ser.activities 27530 28400 96,9 J Information and communication 20760 21600 96,1 K Financial and insurance activities 23192 24000 96,6 L Real estate activities 3804 4800 79,3 M Professional,scientific,technical act. 38297 41100 93,2 N Administrative and support service act. 24428 42300 57,7 O Public admin.defence;compulsory soc.sec. 51018 53400 95,5 P Education 60949 63200 96,4 Q Human health and social work activities 49546 51600 96,0 R Arts,entertainment and recreation 10017 11400 87,9 S Other service activities 7836 9400 83,4 21

Almost in all activities there are lower average annual wages and salaries per employee in SES compared to NA data because in Slovenia in wages and salaries per employee in NA data also some payments are included which are not parts of wage system (e.g. retirement bonus, jubilee rewards) 7. There reasons for the major differences between both surveys in activities are some groups of business entities or employees included in NR but not in SES; unpaid family members in activity A, business entities without employees in activity L and students in activity N 8. In other activities with larger difference no special reason were found except in activity S where there was low unit response rate (see Table 17). 7 Data on holiday bonus and payments in kind are also not part of wage system in Slovenia but were collected and included in SES 2010 Eurostat tables but excluded for national purposes. In table 19 holiday bonus and payments in kind are included in SES data. 8 See also table 20. 22

ANNEX 1 SES 2010 QUESTIONNAIRE ZAP-SP/4L 0 7 0 6 STRUCTURE OF EARNING SURVEY 2010 National Statistics Act (OJ RS, No. 45/95 and 9/2001) Annual Programme of Statistical Surveys (OJ RS, No. 93/2010) Data delivery is obligatory BUSINESS ENTITIY ID number Name UNIT OF BUSINESS ENTITY ID number Name Status of unit of business entity (descriptive) Responsible person: Telephone of responsible person: Serial number Description Variable number A. GENERAL DATA ON PERSON IN PAID EMPLOYMENT xxx x x x x x x x x x x x x x 1. PIN 001 2. ENTRY DATE IN THIS BUSINESS ENTITY (DDMMYYYY) 002 x x x x x B. MONTHLY DATA FOR OCTOBER 2010 xxx x x x x x x x x x x x x x 3. GROSS EARNINGS 003 x x x x x 4. (included in 3) EARNINGS RELATED TO OVERTIME 004 x x x x x x 5. (included in 3) SPECIAL PAYMENTS FOR SHIFT WORK 005 x x x x x x 6. (included in 3) PAYMENTS FOR LESS THEN 100% PAYED ABSENCE 006 x x x x x x 7. NUMBER OF HOURS PAID 007 x x x x x x x x x x 8. (included in 7) NUMBER OF OVERTIME HOURS PAID 008 x x x x x x x x x x 9. (included in 7) NUMBER OF HOURS PAID FOR LESS THEN 100% PAYED ABSENCE 009 x x x x x x x x x x C. ANNUAL DATA FOR YEAR 2010 xxx x x x x x x x x x x x x x 10. GROSS EARNINGS 010 x x x 11. (included in 10) BONUSES AND ALLOWANCES NOT PAID IN EACH PAID PERIOD 011 x x x x 12. (included in 10) PAYMENTS FOR LESS THEN 100% PAYED ABSENCE 012 x x x x 13. NUMBER OF HOURS PAID 013 x x x x x x x x x 14. (included in 13) NUMBER OF OVERTIME HOURS PAID 014 x x x x x x x x x 15. HOLIDAY BONUS 015 x x x x 16. NUMBER OF DAYS OF HOLIDAY LEAVE 016 x x x x x x x x x x 17. PAYMENTS IN KIND 017 x x x x 18. PAYMENTS FOR MEALS 018 x x x x 19. PAYMENTS FOR TRAVEL FROM / TO WORK 019 x x x x 23