Prepared by Giorgos Ntouros, Ioannis Nikolalidis, Ilias Lagos, Maria Chaliadaki

GENERAL SECRETARIAT OF THE NATIONAL STATISTICAL SERVICE OF GREECE GENERAL DIRECTORATE OF STATISTICAL SURVEYS DIVISION OF POPULATION AND LABOUR MARKET STATISTICS HOUSEHOLD S SURVEYS UNIT SSTATIISSTIICSS ON IINCOME AND LIIVIING CONDIITIIONSS ((EU--SSIILC)) STUDY OF THE IIMPACT ON COMPARABIILIITY OF NATIIONAL IIMPLEMENTATIIONS Prepared by Giorgos Ntouros, Ioannis Nikolalidis, Ilias Lagos, Maria Chaliadaki PIRAEUS, JULY 2008 1

EU SILC: Study of the impact on comparability of national implementation 2

INTRODUCTION 5 A. INTRODUCTION ON CONDITIONS UNDER WHICH DATA FROM TWO DIFFERENT SOURCES OF STATISTICAL INFORMATION ARE COMPARABLE 8 1. EU SILC 2003 AND SES 2002 8 2. EU SILC 2004 AND LCS 2004 13 B. DEPICTION IN THE SURFACE OF THE WAGE STRUCTURE BY SECTION, SEX AND AGE GROUPS APPLYING MULTIVATE ANALYSIS (FACTOR ANALYSIS, MULTIPLE LINER REGRESSION, GENERALIZED LINER REGRESSION ETC.) USING DATA FROM EU SILC 2003, STRUCTURAL STATISTICS ON EARNING IN ENTERPRISES SURVEY 18 1. AVERAGE EMPLOYEE INCOME BY ECONOMIC ACTIVITY 18 2. AVERAGE EMPLOYEE INCOME BY GENDER 19 3. AVERAGE EMPLOYEE INCOME BY AGE GROUPS 19 4. AVERAGE EMPLOYEE INCOME BY EDUCATION LEVEL 20 5. AVERAGE EMPLOYEE INCOME BY OCCUPATION 21 6. NUMBER OF EMPLOYEES BY INCOME CLASSES AND GENDER 22 7. NUMBER OF EMPLOYEES BY INCOME CLASSES AND ECONOMIC ACTIVITY 23 8. FACTOR LEVEL: CORRELATION OF NACE AND INCOME CLASSES 25 9. FACTOR LEVEL: CORRELATION OF GENDER, AGE AND INCOME CLASSES 27 10. NUMBER OF EMPLOYEES BY INCOME CATEGORIES, AGE GROUPS AND GENDER 29 11. NUMBER OF EMPLOYEES BY ECONOMIC ACTIVITY 32 12. NUMBER OF EMPLOYEES BY GENDER 33 13. NUMBER OF EMPLOYEES BY AGE GROUPS 33 14. NUMBER OF EMPLOYEES BY EDUCATION LEVEL 34 15. NUMBER OF EMPLOYEES BY OCCUPATION 35 16. FACTOR LEVEL: RELATIONSHIP BETWEEN PROFESSIONS (ONE DIGIT ISCO CODES) AND INCOME CLASSES 38 C. COMPARISONS OF WAGE AND SALARIES FROM EU SILC 2004 WITH THE CORRESPONDING DATA FROM THE LABOUR COST SURVEY APLLYING T-TESTS 40 D. COMPARISON OF THE INCOME TREND AND THE CONSUMPTION OF HOUSEHOLDS USING DATA OF EU-SILC AND THE ANNUAL INDEX OF TURNOVER IN THE RETAIL TRADE FOR VALIDATING THE ACCURACY OF THE COLLECTED INCOME IN THE EU-SILC 42 E. COMPARISON OF SOCIAL FAMILY ALLOWANCES WITH ADMINISTRATIVE DATA 42 1. FAMILY ALLOWANCES: EU SILC 2003/ ADMINISTRATIVE DATA 42 2. FAMILY ALLOWANCES: EU SILC 2004/ ADMINISTRATIVE DATA 45 F. CONCLUDING REMARKS 46 REFERENCES 49 ANNEX 1: VARIABLES USED 51 EU SILC: Study of the impact on comparability of national implementation 3

STUDY OF THE IMPACT ON COMPARABILITY OF NATIONAL IMPLEMENTATIONS Abstract This study provides systematic cross/comparisons/validations of Statistics on Income and living conditions (EU-SILC) data with other data sources (Structural statistics on earning in enterprises Survey, Labour Cost Survey, Annual index of turnover in the retail trade and Social family allowances. EU SILC: Study of the impact on comparability of national implementation 4

INTRODUCTION With the Amsterdam Treaty the program of social action in all member states for the years 1998-2000 was defined as well as the legal frame ruling the production of Social Statistics. The fields of poverty and social exclusion were of high priority in the political agenda of the European Council in Lisbon, in March 2000 as well as in the proposal of Commission for a communal program for encouraging co-operation among the member states against social exclusion. During the European Council of Lisbon (March 2000) several requests were submitted concerning the quality improvement of statistical data and among other things were discussed the effacement of absolute poverty, the cooperation program among member states against social exclusion as well as the constitution of structural indicators, such as indicators of unequal income distribution, poverty percentages before and after social transfers, intergenerational poverty, etc. In December 2000, at the European Council that took place in Nice, France, the leaders of all member states confirmed the decision of Lisbon, that the battle against poverty and social exclusion is won using open methods of co-ordination and co-operation. Basic elements of this rapprochement are the determination of commonly accepted targets for the European Union and the elaboration of proper national action plans for the achievement of these targets, as well as the regular report and recording of the progress being made. The Greek Survey on Income and Living Conditions is part of the European Statistical Program and has replaced since 2003 the European Community Household Survey. Basic aim of the survey is the study, both at European and national level of households living conditions in relation to their income. The survey is the reference for comparative statistics on income distribution and social exclusion in the European Union. With the survey examined are specific socio-economic magnitudes affecting population s living conditions. With collected information our country calculates the structural indicators for social cohesion and produces systematic statistics on income inequalities, inequalities on households living conditions, poverty and social exclusion. More specifically from the survey are calculated 8 of overarching indicators,13 of social Inclusion indicators and 9 of pension adequacy indicators, concerning poverty and social inequality. These indicators, among other things, contribute in the configuration and practice of social politics in our country. For the pre-mentioned reasons information is gathered, for the households as well as for their members, concerning: - Income from any source (work, property, social benefits, etc.) - Occupation - Living conditions (dwelling s quality, amenities, etc.) - Educational level - Health status for all members of the household According to the methodology for measuring poverty, the poverty line is calculated with its relative concept and it is defined at 60% of the median total equivalized disposable income of the household, using modified OECD equivalized scale. Equivalent size refers to the OECD modified scale which gives a weight of 1.0 to the first adult, 0.5 to other persons aged 14 or over who are living in the household and 0.3 to each child aged under 14. EU SILC: Study of the impact on comparability of national implementation 5

As total equivalized disposable income of the household is considered total net income (that is income after deducting taxes and social contributions) received from all household members. More specifically the income components included in the survey are: Income from work Income from property Social transfers and pensions Monetary transfers from other households and Imputed income from the use of company car Income components, such as imputed rent from ownership-occupancy, indirect social transfers, income in kind and loan interest can possibly influence significantly the results and will be included in the survey from the year 2007, onwards. The survey is being conducted upon the decision of the Ministry of Economy and Finance, and according to the contract having been signed between Commission and the National Statistical Service of Greece, in the framework of Regulation (EC) No 1177/2003 of the European Parliament and of the Council concerning Community Statistics on Income and Living Conditions (EU-SILC). The survey consists of two components the cross-sectional and the longitudinal. The first one referring to a specific time period, while the second to the changes occurring in three or four years time. As referred in the technical description of the action, comparability is a critical aspect of EU-SILC. Several provisions for the study of comparability are made in EU-SILC framework regulation. Comparability of data between Member States shall be a fundamental objective and shall be pursued through the development of methodological studies from the outset of EU-SILC data collection, carried out in close cooperation between the Member States and Eurostat (Article 1). The Commission (Eurostat) shall produce by 30 June N+3 a comparative final quality report that covers both crosssectional and longitudinal components in relation to the year of the survey N. By way of exception, the 2004 report (for those Member States starting data collection in 2004) and the 2005 report (for those Member States starting data collection in 2005) shall cover only the cross-sectional component (Article 16). Preliminary assessment and studies on comparability are currently carried out at EU level, by Eurostat in the framework of the Eurostat Task Force on methodological issues. In this context National Statistical Service of Greece carried out a study of the impact on comparability of national implementations. This document provides systematic cross/comparisons/validations of EU-SILC results with other data sources: Structural statistics on earning in enterprises Survey, 2002 Labour Cost Survey, 2004 Annual index of turnover in the retail trade, 2002 and 2003 Social family allowances (administrative data), 2002 and 2003 EU SILC: Study of the impact on comparability of national implementation 6

It is structured following the description of the action. The report is divided in five chapters: A. Introduction on conditions under which data from two different sources of statistical information are comparable B. Depiction in the surface of the wage structure by section, sex and age groups applying multivate analysis (t test, correspondence factor analysis etc.) using data from EU-SILC 2003, Structural statistics on earning in enterprises Survey. C. Comparisons of wage and salaries from EU-SILC 2004 with the corresponding data from the labour cost survey applying t-tests D. Comparison of the income trend and the consumption of households using data of EU-SILC and the annual index of turnover in the retail trade for validating the accuracy of the collected income in the EU-SILC E. Comparison of social family benefits with administrative data (social budget) F. Concluding remarks EU SILC: Study of the impact on comparability of national implementation 7

A. INTRODUCTION ON CONDITIONS UNDER WHICH DATA FROM TWO DIFFERENT SOURCES OF STATISTICAL INFORMATION ARE COMPARABLE This chapter provides the conditions under which data from different data sources of statistical information are comparable. The sources are the Structural statistics on earning in enterprises Survey (SES), 2002 and the Labour Cost Survey (LCS), 2004. Mainly, it contains information on basic concepts and definitions as described in the regulations of European Parliament and Council between two sources, the EU-SILC 2003 and SES 2002 and the EU-SILC 2004 and LCS 2004, and the differences of the concepts and definitions used, as well as an assessment of the consequences of the differences. The variables used in each source are listed in ANNEX 1. 1. EU SILC 2003 AND SES 2002 1.1. Statistical Unit EU SILC 2003 SES 2002 It is based on private household: means a person living alone or a group of people who live together in the same private dwelling and share expenditures, including the joint provision of the essentials of living and provide information on employees in enterprises independently of its size Provide information on employees in enterprises with 10 or more employees classified by size and principal activity. Besides the fact that the statistical units between the two surveys are totally different (household, enterprise), the consequences seem not to affect the comparability and the differences are not worth noticing. EU SILC: Study of the impact on comparability of national implementation 8

1.2. Classification economic activities EU SILC 2003 SES 2002 The region in which the local unit is located was classified according to NACE rev.1.1: Statistical classification of economic activities in the European Community, Rev. 1.1. All classification economic activities The region in which the local unit is located was classified according to NACE rev.1.1: Statistical classification of economic activities in the European Community, Rev. 1.1. covers all sectors in economic activities classified to Sections C to K and M to O of NACE Rev. 1.1 in enterprises with at least 10 employees. C. Mining and quarrying (10-14) D. Manufacturing industry (15-37) E. Electricity, gas and water supply (40,41) F. Construction (45) G. Wholesale and retail trade (50,51,52) H. Hotels and restaurants 55 I. Transport, storage and communication (60-64) J. Financial intermediation (65-67). K. Real estate (70-74) In both surveys EU-SILC and SES, NACE rev.1 (two digits) is used. EU SILC all sectors of economic activities are included, while SES covers all sectors of economic activities classified to Sections C to K of NACE Rev. 1.1 and moreover in enterprises with at least 10 employees (see in the table above). Also, in EU-SILC no distinction is being made among public and private sector, while in SES this distinction exists. The comparison has been made, thus, only in the common sections of economic activities and in public and private sector as a whole. 1.3. Size of the enterprise to which the local unit belongs The size of the enterprise in terms of the number of employees was assigned to one of the following bands: EU SILC 2003 SES 2002 1 10 (exact number if between 1 10 to 49, and 10) 50 to 249, 11 if between 11 to 19 persons 250 to 499, 12 if between 20 to 49 persons 500 to 999, and 13 if 50 persons or more 1 000 or more employees. 14 don't know but fewer than 11 persons 15 don't know but more than 10 persons It is noted that the first band of EU-SILC (1 9 employees) has not been excluded. EU SILC: Study of the impact on comparability of national implementation 9

1.4. Employees EU SILC covers all employees living in private dwellings and Structural Statistics on Earnings provide information on employees in enterprises with 10 or more employees classified by size and principal activity. EU SILC 2003 SES 2002 Employees are defined as persons who work for a public or private employer and who receive compensation in the form of wages, salaries, fees, gratuities; non-conscripted members of the armed forces are also included. Employees are all persons, irrespective of their nationality or the length of their working time in the country, who have a direct employment contract with the enterprise or local unit (whether the agreement is formal or informal) and receive remuneration, irrespective of the type of work performed, the number of hours worked (full-time or part-time) and the duration of the contract (fixed or indefinite). The remuneration of employees can take the form of wages and salaries including bonuses, pay for piecework and shift work, allowances, fees, tips and gratuities, commission and remuneration in kind. The employees to be included in the sample are those who actually received remuneration during the reference month. The definition of employees covers manual and non-manual workers and management personnel in the private and public sectors in economic activities classified to Sections C to K of NACE Rev. 1.1 in enterprises with at least 10 employees EU SILC: Study of the impact on comparability of national implementation 10

1.5. Sex 1.6. Age EU SILC 2003 SES 2002 1. Male 2. Female 1. Male 2. Female EU SILC 2003 SES 2002 The age is calculated as the difference between the reference year of the survey and the year of birth The age is calculated as the difference between the reference year of the survey and the year of birth 1.7. Occupation in the reference month (ISCO-88 (COM)) EU SILC 2003 SES 2002 ISCO 88 (COM): International standard classification of occupations (for European purposes), 1988 version at the two-digit level. The occupation is to be coded according to the International Standard Classification of Occupations, 1988 version (ISCO-88 (COM)) at the two-digit level. 1.8. Highest successfully completed level of education and training (ISCED 97) EU SILC 2003 SES 2002 International Standard Classification of Education, 1997 version (ISCED 97). International Standard Classification of Education, 1997 version (ISCED 97). Although EU-SILC provides more detailed information for the comparison the classification used in SES has been used, that is ISCED levels 0 and 1 together and ISCED levels 5 and 6 together. EU SILC: Study of the impact on comparability of national implementations 11

1.9. Contractual working time (full-time or part-time) EU SILC 2003 SES 2002 The distinction between full-time and part-time work should be made on the basis of a spontaneous answer given by the respondent. It is impossible to establish a more exact distinction between part-time and full-time work, due to variations in working hours between Member States and also between branches of industry. By checking the answer with the number of hours usually worked, it should be possible to detect and even to correct implausible answers, since part-time work will hardly ever exceed 35 hours, while full-time work will usually start at about 30 hours. Full-time employees are those whose normal working hours are the same as the collectively agreed or customary hours worked in the local unit under consideration, even if their contract is for less than one year. Information on part time employees was considered as not being reliable and has not been included. After all in 2002/2003 part time work was at very low percentages (<5%) in Greece. 1.10. Income reference period EU SILC 2003 SES 2002 Previous calendar year Current calendar year Income reference period is 2002. 1.11. Net cash or near cash employee income EU SILC 2003 SES 2002 Employee income is defined as the total renumaration in cash payable income by an employer to an employee income in return for work done by the latter during the income reference period. Compensation of employees is defined as the total remuneration, in cash or in kind, payable by an employer to an employee in return for work done by the latter during the reference period. EU-SILC collects information only on monetary income (and not income in kind) so we only used and compared it. EU SILC: Study of the impact on comparability of national implementations 12

1.12.Taxes/ Compulsory social contributions EU SILC 2003 SES 2002 Tax refers to the amount of all taxes on the employee s earnings withheld by the employer for the reference month and paid by the employer to the tax authorities on behalf of the employee. Tax refers to the amount of all taxes on the employee s earnings withheld by the employer for the reference month and paid by the employer to the tax authorities on behalf of the employee. Employers' contributions are defined as payments made, during the income reference period, by employers for the benefits of their employees to insurers (social security funds and private funded schemes) covering statutory, conventional or contractual contributions in respect of insurance against social risks. Employers' contributions refer to the total amount of compulsory social contributions paid by the employer on behalf of the employee to insurance schemes authorities during the reference year. EU-SILC collects information both on net income and taxes and social contributions, however taxes and social contributions information is being considered unreliable. SES collects information only on gross income. Taxes and social contributions were optional, thus only a few enterprises provided this information. Applying a simple mathematical model in SES data, based on taxation system and on compulsory social insurance system, gross income was converted to net. 2. EU SILC 2004 AND LCS 2004 2.1. Statistical Unit EU SILC 2004 LCS 2004 It is based on private household: means a person living alone or a group of people who live together in the same private dwelling and share expenditures, including the joint provision of the essentials of living and provide information on employees in all enterprises. Provide information on employees in enterprises with 10 or more employees classified by size and principal activity. Besides the fact that the statistical units among the two surveys are totally different (household, enterprise), the consequences seem not to affect the comparability and the differences are not worth noticing. EU SILC: Study of the impact on comparability of national implementations 13

2.2. Classification economic activities EU SILC 2004 LCS 2004 The region in which the local unit is located was classified according to NACE rev.1.1: Statistical classification of economic activities in the European Community, Rev. 1.1. - All classification economic activities The region in which the local unit is located was classified according to NACE rev.1.1: Statistical classification of economic activities in the European Community, Rev. 1.1. covers all sectors in economic activities classified to Sections C to K and M to O of NACE Rev. 1.1 in enterprises with at least 10 employees (1). C. Mining and quarrying (10-14) D. Manufacturing industry (15-37) E. Electricity, gas and water supply (40,41) F. Construction (45) G. Wholesale and retail trade (50,51,52) H. Hotels and restaurants 55 I. Transport, storage and communication (60-64) J. Financial intermediation (65-67). K. Real estate (70-74) M. Education N. Health, social protection O. Other activities In both surveys EU SILC and SES, NACE rev.1 (two digits) is used. EU SILC all sectors of economic activities are included, while SES covers all sectors of economic activities classified to Sections C to K and M to O of NACE Rev. 1.1 and moreover in enterprises with at least 10 employees (see in the table above). Also, in EU-SILC no distinction is being made among public and private sector, while in SES this distinction exists. The comparison has been made, thus, only in the common sections of economic activities and in public and private sector as a whole. EU SILC: Study of the impact on comparability of national implementations 14

2.3. Size of the enterprise to which the local unit belongs The size of the enterprise in terms of the number of employees was assigned to one of the following bands: EU SILC 2004 LCS 2004 1 10 (exact number if between 1 10 to 49, and 10) 50 to 249, 11 if between 11 to 19 persons 250 to 499, 12 if between 20 to 49 persons 500 to 999, and 13 if 50 persons or more 1 000 or more employees. 14 don't know but fewer than 11 persons 15 don't know but more than 10 persons It is noted that the first band of EU-SILC (1 9 employees) has not been excluded. 2.4. Employees EU SILC covers all employees who live who live in the private dwellings while Labour Cost survey covers the total expenditure borne by employers in order to employ EU SILC 2004 LCS 2004 Employees are defined as persons who work for a public or private employer and who receive compensation in the form of wages, salaries, fees, gratuities; non-conscripted members of the armed forces are also included. Employees are all persons, irrespective of their nationality or the length of their working time in the country, who have a direct employment contract with the enterprise or local unit (whether the agreement is formal or informal) and receive remuneration, irrespective of the type of work performed, the number of hours worked (full-time or part-time) and the duration of the contract (fixed or indefinite). The remuneration of employees can take the form of wages and salaries including bonuses, pay for piecework and shift work, allowances, fees, tips and gratuities, commission and remuneration in kind. The employees to be included in the sample are those who actually received remuneration during the reference month. The definition of employees covers manual and non-manual workers and management personnel in the private and public sectors in economic activities classified to Sections C to K and M to O of NACE Rev. 1.1 in enterprises with at least 10 employees EU SILC: Study of the impact on comparability of national implementations 15

2.5. Occupation in the reference month (ISCO-88 (COM)) EU SILC 2004 LCS 2004 ISCO 88 (COM): International standard classification of occupations (for European purposes), 1988 version at the two-digit level.. 2.6.Contractual working time (full-time or part-time) The occupation is to be coded according to the International Standard Classification of Occupations, 1988 version (ISCO-88 (COM)) at the two-digit level. EU SILC 2004 LCS 2004 The distinction between full-time and parttime work should be made on the basis of a spontaneous answer given by the respondent. It is impossible to establish a more exact distinction between part-time and full-time work, due to variations in working hours between Member States and also between branches of industry. By checking the answer with the number of hours usually worked, it should be possible to detect and even to correct implausible answers, since part-time work will hardly ever exceed 35 hours, while full-time work will usually start at about 30 hours. Full-time employees are those whose normal working hours are the same as the collectively agreed or customary hours worked in the local unit under consideration, even if their contract is for less than one year. Part-time employees are those who work fewer hours than the normal working hours of full-time employees 2.7. Income reference period EU SILC 2004 LCS 2004 Previous calendar year Previous calendar year Income reference period: 2003 2.8. Net cash or near cash employee income EU SILC 2004 LCS 2004 Employee income is defined as the total renumaration in cash payable income by an employer to an employee income in return for work done by the latter during the income reverence period, Compensation of employees is defined as the total remuneration, in cash, payable by an employer to an employee in return for work done by the latter during the reference period. EU-SILC collects information only on monetary income (and not income in kind) so we only used and compared it. EU SILC: Study of the impact on comparability of national implementations 16

2.9.Taxes /Compulsory social contributions EU SILC 2004 LCS 2004 Tax refers to the amount of all taxes on the employee s earnings withheld by the employer for the reference month and paid by the employer to the tax authorities on behalf of the employee. Tax refers to the amount of all taxes on the employee s earnings withheld by the employer for the reference month and paid by the employer to the tax authorities on behalf of the employee. Employers' contributions are defined as payments made, during the income reference period, by employers for the benefits of their employees to insurers (social security funds and private funded schemes) covering statutory, conventional or contractual contributions in respect of insurance against social risks. Employers' contributions refers to the total amount of compulsory social contributions paid by the employer on behalf of the employee to insurance schemes authorities during the reference year. EU-SILC collects information both on net income and taxes and social contributions, however taxes and social contributions information is being considered unreliable. SES collects information only on gross income. Taxes and social contributions were optional, thus only a few enterprises provided this information. Applying a simple mathematical model in SES data, based on taxation system and on compulsory social insurance system, gross income was converted to net. EU SILC: Study of the impact on comparability of national implementations 17

B. DEPICTION IN THE SURFACE OF THE WAGE STRUCTURE BY SECTION, SEX AND AGE GROUPS APPLYING MULTIVATE ANALYSIS (FACTOR ANALYSIS, MULTIPLE LINER REGRESSION, GENERALIZED LINER REGRESSION ETC.) USING DATA FROM EU SILC 2003, STRUCTURAL STATISTICS ON EARNING IN ENTERPRISES SURVEY 1. AVERAGE EMPLOYEE INCOME BY ECONOMIC ACTIVITY After checking the hypothesis that average net employee s income per economic activity does not present statistically significant difference among the two surveys (EU-SILC and SES), see table 1, we conclude that : a) We do accept the hypothesis (since T 0,05 =1,96) for most of the economic activities, where A<1,96, that is in economic activities C, D, G, H, I, J and K. b) On the contrary, keeping the same level of significance (=0,05) we conclude that for economic activities E. Electricity, gas and water supply and F. Construction average yearly net employee s income presents statistically significant difference among the two surveys. Table 1. Average employee income by economic activity Economic activity EU-SILC SES Α<1,96 C. Mining and quarrying 11.393,46 12.433,18 0,47 D. Manufacturing industry 11.196,95 11.671,47 0,87 E. Electricity, gas and water supply 16.661,30 22.704,86 2,42 F. Construction 9.164,31 11.603,20 6,17 G. Wholesale and retail trade 9.938,92 10.426,61 0,99 H. Hotels and restaurants 8.007,43 8.575,63 0,89 I. Transport, storage and communication 14.822,53 14.598,51 0,23 J. Financial intermediation 18.441,36 17.127,12 0,63 K. Real estate 13.337,23 11.610,38 1,20 EU SILC: Study of the impact on comparability of national implementation 14

2. AVERAGE EMPLOYEE INCOME BY GENDER After checking the hypothesis that average net employee s income per gender does not present statistically significant difference among the two surveys (EU-SILC and SES), see table 2, we conclude that : a) As far as men are concerned we can accept the hypothesis. b) As far as women are concerned total average net income presents statistically significant difference among the two surveys. Table 2. Average employee income by gender Gender EU-SILC SES Α<1,96 Male 12.997,27 13.326,81 1,05 Female 11.112,90 10.308,97 2,47 3. AVERAGE EMPLOYEE INCOME BY AGE GROUPS After checking the hypothesis that average net employee s income per age group does not present statistically significant difference among the two surveys (EU-SILC and SES), see table 3, we conclude that we do accept the hypothesis for all age groups. Table 3. Average employee income by age groups Age groups EU-SILC SES Α<1,96 16-24 6.823,48 6.849,44 0,07 25-34 10.515,31 10.020,99 1,51 35-44 13.423,58 12.970,67 1,02 45-54 14.818,03 15.570,20 1,23 55-74 15.072,60 16.355,95 1,12 EU SILC: Study of the impact on comparability of national implementations 19

4. AVERAGE EMPLOYEE INCOME BY EDUCATION LEVEL After checking the hypothesis that average net employee s income, as far as the educational level having been completed by the employee is concerned, does not present statistically significant difference among the two surveys (EU-SILC and SES), see table 4, we conclude that : a). We can accept the hypothesis for persons having completed Primary education Upper secondary education and First or second stage of tertiary education b). On the contrary, average net income presents statistically significant difference among the two surveys for persons having completed Lower secondary education and Post secondary non tertiary education Table 4. Average employee income by education level Education level EU-SILC SES Α<1,96 Never attended any level of education - Primary education 10.024,87 10.389,43 0,67 Lower secondary education 11.036,52 10.067,56 3,53 Upper secondary education 10.416,37 11.189,38 1,05 Post secondary non tertiary education 16.155,16 11.777,95 8,80 First and second stage of tertiary education 26.069,06 17.346,96 1,56 EU SILC: Study of the impact on comparability of national implementations 20

5. AVERAGE EMPLOYEE INCOME BY OCCUPATION After checking the hypothesis that average net employee s income, as far as occupation is concerned, does not present statistically significant difference among the two surveys (EU- SILC and SES) and with significance level a=0,05 we conclude that we can accept the hypothesis for all occupations except for Extraction and building trades workers, other craft and related trades workers. Metal machinery and related trades workers. Precision, handicraft, printing and related trades workers for which average net income, among the two surveys, see table 5, presents statistically significant difference. Table 5. Average employee income by occupation Occupation EU-SILC SES Α<1,96 1. Legislators and senior officials-corporate managers 2. Physical, mathematical, engineering science and other professionals 3. Physical, engineering science associate professionals and other associate professionals 4. Office clerks and customer services clerks 5. Personal and protective services workers, models, salespersons and demonstrators miscellaneous 24.608,76 22.061,14 0,76 16.925,42 17.977,94 1,38 13.815,13 14.369,75 0,73 12.218,16 11.577,96 1,28 9.654,90 8.944,06 1,64 6. Skilled agricultural and fishery workers 7.834,72 7.974,09 0,13 7. Extraction and building trades workers, other craft and related trades workers. Metal machinery and related trades workers. Precision, handicraft, printing and related trades workers 8. Stationary-plant and related operators, drivers and mobile plant operators, machine operators and assemblers 9. Sales and services elementary occupations, agricultural, fishery and related labourers in mining, construction, manufacturing and transport 10.229,80 11.914,54 4,17 10.872,06 11.901,71 1,66 8.092,91 8.516,41 0,84 EU SILC: Study of the impact on comparability of national implementations 21

6. NUMBER OF EMPLOYEES BY INCOME CLASSES AND GENDER Applying X 2 ν distribution tables with (κ-1).(λ-1) = (5-1).(2-1) = ν = 4 degrees of freedom and probability 95%, that is a=0,05, for both variables (gender / income category), in both surveys (EU-SILC and SES), see table6 and 7, it arises that income category significantly depends on gender. The dependence degree in the SES is larger, that is 22,84% in relation to that of EU-SILC being 12,80%. Table 6. Number of employees by income classes and gender, EU- SILC Income classes Gender Male Female Total 0-4.999 99.825 96.461 196.286 5.000-9.999 452.841 340.859 793.700 10.000-19.999 745.569 439.985 1.185.554 20.000-29.999 112.198 36.656 148.854 30.000+ 48.546 10.401 58.947 Total 1.458.979 924.362 2.383.341 Table 7. Number of employees by income categories and gender, SES Income classes Gender Male Female Total 0-4.999 39.192 33.567 72.759 5.000-9.999 170.769 162.852 333.621 10.000-19.999 296.984 133.463 430.447 20.000-29.999 64.592 10.955 75.547 30.000+ 15.617 1.710 17.327 Total 587.154 342.547 929.701 EU SILC: Study of the impact on comparability of national implementations 22

7. NUMBER OF EMPLOYEES BY INCOME CLASSES AND ECONOMIC ACTIVITY Applying X 2 ν distribution tables with (κ-1).(λ-1) = (9-1).(5-1) = ν = 32 degrees of freedom and probability 95%, that is a=0,05, for both variables (income category/economic activity), in both surveys (EU-SILC and SES), see tables 8 and 9, it arises that income category depends on economic activity. The dependence degree of the two variables is strong for both surveys, 37,89% for EU- SILC and 44,25% for SES. What s left to be studied is if in both surveys, the same economic activities depend on the same income categories. This will be done using corresponded factor analysis and Hierarchical cluster analysis and the results will be presented at factor level. Table 8. Number of employees by income classes and economic activity, EU-SILC Income classes Economic activity 0-5.000-10.000-20.000-30.000 4.999 9.999 19.999 29.999 + Total C. Mining and quarrying 1.158 5.699 11.112 468 0 18.437 D. Manufacturing industry 23.731 176.945 158.082 16.103 10.967 385.828 E. Electricity, gas and water supply 0 2.834 22.853 7.077 1.111 33.875 F. Construction 22.976 98.559 72.983 1.758 755 197.031 G. Wholesale and retail trade H. Hotels and restaurants I. Transport, storage and communication J. Financial intermediation 27.968 177.125 109.719 13.422 3.478 331.712 37.350 66.237 34.981 671 942 140.181 6.600 49.258 103.344 24.881 9.714 193.797 3.412 12.278 37.964 12.104 8.514 74.272 K. Real estate 11.682 43.127 39.246 10.344 7.191 111.590 Total 134.877 632.062 590.284 86.828 42.672 1.486.723 EU SILC: Study of the impact on comparability of national implementations 23

Table 9. Number of employees by income classes and economic activity, SES Economic activity 0-4.999 C. Mining and quarrying D. Manufacturing industry E. Electricity, gas and water supply 5.000-9.999 Income classes 10.000-19.999 20.000-29.999 30.000 + Total 298 1.873 3.838 386 60 6.455 18.902 110.271 143.000 17.287 3.497 292.957 83 282 15.273 15.485 5.155 36.278 F. Construction 4.687 18.364 23.586 3.686 440 50.763 G. Wholesale and retail trade H. Hotels and restaurants I. Transport, storage and communication J. Financial intermediation 18.517 105.063 81.844 7.204 2.039 214.667 15.811 50.545 23.104 1.104 280 90.844 5.146 15.567 72.410 11.307 1.567 105.997 1.183 4.853 40.839 13.982 2.542 63.399 K. Real estate 8.132 26.802 26.552 5.106 1.747 68.339 Total 72.759 333.620 430.446 75.547 17.327 929.699 EU SILC: Study of the impact on comparability of national implementations 24

8. FACTOR LEVEL: CORRELATION OF NACE AND INCOME CLASSES Income has been split in five classes, as following: a) The first class includes persons having yearly net income from 0 to 4.999 euros. b) The second persons having yearly net income from 5.000 to 9.999 euros. c) The third persons having yearly net income from 10.000 to 19.999 euros. d) The fourth persons having yearly net income from 20.000 to 29.999 euros and e) The fifth persons having yearly net income more than 30.000 euros. The horizontal axe confronts employees having low income with employees having high income. Moving from left to right employees income increases. The vertical axe confronts Mining and quarrying Manufacturing Industry (D and C) and Construction (F) plus Wholesale and retail trade (G) with the rest of economic activities (E, H, I, J, K). As far as the EU-SILC survey is concerned, according to their income and their economic activity employees have been split into four clusters (see graph 1), as following: a) The first cluster consists of branch H with the employees reaching income of the first income class b) The second cluster includes branches F and G with employees reaching income of the second income class c) The third cluster includes branches D, C and K with the majority of employees reaching income of the third income class and d) The fourth cluster includes branches I, E and J with employees with high income. Branch J is mostly correlated to income class 5, though. As far as the SES survey is concerned, according to their income and their economic activity employees have been split into four clusters(see graph 2),, as following: a) The first cluster consists of branch H with the employees reaching income of the first income class b) The second cluster includes branches K and G -and not F and G like the EU-SILC- with employees reaching income of the second income class c) The third cluster includes branches F, D and C and not K included in the EU-SILC- with the majority of employees reaching income of the third income class and finally d) The fourth cluster includes branches I, E and J with employees with high income. However, it should be noted that branches I and J of EU-SILC correspond to definitely higher incomes in relation to those of the SES. Additionally, it should also be noted that in the EU-SILC branch J is strongly correlated to income class 5, while in the SES branch E is strongly correlated to income class 5. EU SILC: Study of the impact on comparability of national implementations 25

EU SILC: Study of the impact on comparability of national implementations 26 Graph 1. EU-SILC: NACE X Income classes 1 H K 5 J 4 I E 3 F C G 2 D Graph 2. SES: NACE X Income classes 5 E 4 J I C 3 F D K G 2 1 H

9. FACTOR LEVEL: CORRELATION OF GENDER, AGE AND INCOME CLASSES Income has been split in five classes, as following: a) The first class includes persons having yearly net income from 0 to 4.999 euros. b) The second persons having yearly net income from 5.000 to 9.999 euros. c) The third persons having yearly net income from 10.000 to 19.999 euros. d) The fourth persons having yearly net income from 20.000 to 29.999 euros and e) The fifth persons having yearly net income more than 30.000 euros. The horizontal axe confronts employees having low income with employees having high income. Moving from left to right employees income increases. The vertical axe confronts age group 25-44 with the rest age groups for men and women. As far as the EU-SILC survey is concerned, according to their income four groups of persons are presented (see graph 3),, as following: a) The first group includes employees men and women- aged 16-24 reaching income of the first income class b) The second group includes employees men and women- aged 25-34 reaching income of the second income class c) The third cluster includes only women- aged 35-74 mostly reaching income of the third income class. However, women aged 35-44 mostly converge to income class 3. d) Finally, the fourth group includes men aged 35-74 who mostly converge to income classes 4 and 5. Age group 55-75 mostly converges to income class 5. As far as the SES survey is concerned (see graph 4),: a) The first group coincides exactly with the relative first group of the EU-SILC b) The second group, though, includes women aged 25-74 and men aged 25-34 reaching income of the second income class c) The third group includes men aged 35-44 reaching income of the third income class and d) The fourth group includes men 45-74 reaching income of the fourth and fifth income class. EU SILC: Study of the impact on comparability of national implementations 27

Graph 3. EU-SILC: Gender +Age X Income classes 4 5 M:16-24 F:16-24 1 M:55-74 F:55-74 F:45-54 M:45-54 2 M:25-34 M:35-44 3 F:25-34 F:35-44 Graph 4. SES: Gender + Age X Income classes 5 F:16-24 M:16-24 1 M:55-74 4 M:45-54 F:55-74 2 F:25-34 M:25-34 F:35-44 F:45-54 3 M:35-44 EU SILC: Study of the impact on comparability of national implementations 28

10. NUMBER OF EMPLOYEES BY INCOME CATEGORIES, AGE GROUPS AND GENDER Applying X 2 ν distribution tables with significance level a=0,05, for both variables (age group/income categories for males and females), in both surveys (EU-SILC and SES), it arises that income category depends significantly on the age group of the employee. The dependence degree of the two variables is strong for both surveys, 37,57% for EU-SILC and 41,36% for SES. What s left to be studied is if in both surveys, the same age groups depend on the same income categories. This will be done using corresponded factor analysis and Hierarchical cluster analysis and the results will be presented at factor level (see tables 10-13). Table 10. Number of employees by income classes and age groups, Male, EU SILC Age groups 0-4.999 5.000-9.999 Income classes 10.000-19.999 20.000-29.999 30.000 + Total 16-24 31.671 74.921 18.570 0 0 125.162 25-34 34.614 206.630 208.131 13.074 5.442 467.891 35-44 18.271 87.148 261.314 41.375 17.327 425.435 45-54 9.167 59.299 198.766 38.754 18.347 324.333 55-74 6.103 24.842 58.789 18.994 7.430 116.158 Total 99.826 452.840 745.570 112.197 48.546 1.458.979 EU SILC: Study of the impact on comparability of national implementations 29

Table 11. Number of employees by income classes and age groups, Female, EU-SILC Age groups 0-4.999 5.000-9.999 Income classes 10.000-19.999 20.000-29.999 30.000 + Total 16-24 21.564 59.886 11.206 0 430 93.086 25-34 29.492 132.517 141.634 6.695 1.634 311.972 35-44 23.720 87.403 179.216 11.052 3.714 305.105 45-54 17.755 53.586 90.965 15.962 3.954 182.222 55-74 3.929 7.468 16.964 2.947 668 31.976 Total 96.460 340.860 439.985 36.656 10.400 924.361 Table 12. Number of employees by income categories and age groups, Male, SES Income classes Age groups 0-4.999 5.000-9.999 10.000-19.999 20.000-29.999 30.000 + Total 16-24 11.125 24.996 4.776 43 23 40.963 25-34 16.537 83.402 81.463 5.150 608 187.160 35-44 7.073 37.467 102.090 17.668 3.537 167.835 45-54 3.115 18.795 83.501 32.807 7.145 145.363 55-74 1.342 6.110 25.153 8.924 4.304 45.833 Total 39.192 170.770 296.983 64.592 15.617 587.154 EU SILC: Study of the impact on comparability of national implementations 30

Table 13. Number of employees by income categories and age groups, Female, SES Income classes Age groups 0-4.999 5.000-9.999 10.000-19.999 20.000-29.999 30.000+ Total 16-24 9.783 23.771 3.176 83 59 36.872 25-34 12.371 70.064 48.698 1.389 432 132.954 35-44 6.933 41.328 51.255 4.678 499 104.693 45-54 3.669 23.06 26.143 4.124 621 57.643 55-74 811 4.603 4.191 681 99 10.385 Total 33.567 162.852 133.463 10.955 1.710 342.547 EU SILC: Study of the impact on comparability of national implementations 31

11. NUMBER OF EMPLOYEES BY ECONOMIC ACTIVITY The distribution of employees by economic activity for both surveys does not present statistically significant difference. Economic activities D. Manufacturing industry and G. Wholesale and retail trade, however present higher percentages of employees (see table 14). Table 14. Number of employees by economic activity Economic activity EU SILC N SES N EU SILC % SES % C. Mining and quarrying D. Manufacturing industry E. Electricity, gas and water supply 18.437 6.455 0,0124 0,0069 385.828 292.957 0,2595 0,3151 33.875 36.278 0,0228 0,0390 F. Construction 197.030 50.764 0,1325 0,0546 G. Wholesale and retail trade H. Hotels and restaurants I. Transport, storage and communication J. Financial intermediation 331.712 214.667 0,2231 0,2309 140.181 90.844 0,0943 0,0977 193.796 105.996 0,1304 0,1140 74.273 63.399 0,0500 0,0682 K. Real estate 111.591 68.339 0,0751 0,0735 Total 1.486.723 929.699 1,0000 1,0000 EU SILC: Study of the impact on comparability of national implementations 32

12. NUMBER OF EMPLOYEES BY GENDER The distribution of employees by gender for both surveys does not present statistically significant difference. Men represent approximately the 2/3 of employees (see table 15). Table 15. Number of employees by gender Gender EU SILC N SES N EU SILC % SES % Male 1.458.978 587.153 0,6122 0,6316 Female 924.361 342.546 0,3878 0,3684 Total 2.383.339 929.699 1,0000 1,0000 13. NUMBER OF EMPLOYEES BY AGE GROUPS The distribution of employees by age group for both surveys does not present statistically significant difference (see table 16). Age group 25-34 represents approximately the 1/3 of employees. Table 16. Number of employees by age groups Age groups EU SILC N SES N EU SILC % SES % 16-24 218.249 77.835 0,0916 0,0837 25-34 779.864 320.114 0,3272 0,3443 35-44 730.541 272.528 0,3065 0,2931 45-54 506.554 203.005 0,2125 0,2184 55-74 148.133 56.217 0,0622 0,0605 Total 2.383.341 929.699 1,0000 1,0000 EU SILC: Study of the impact on comparability of national implementations 33

14. NUMBER OF EMPLOYEES BY EDUCATION LEVEL The distribution of employees by educational level for both surveys exempting persons having completed primary education present statistically significant difference. According to EU-SILC 42,84% of employees have completed lower secondary education, while according to SES 47,41% of employees have completed upper secondary education(see table 17).. Table 17. Number of employees by education level Education level EU SILC N SES N EU SILC % SES % Never attended any level of education - Primary education Lower secondary education Upper secondary education Post secondary non tertiary education- First and second stage of tertiary education Total 268.062 137.582 0,1347 0,1484 852.839 124.059 0,4284 0,1338 165.541 439.695 0,0832 0,4741 683.682 39.187 0,3434 0,0423 20.534 186.862 0,0103 0,2015 1.990.658 927.385 1,0000 1,0000 EU SILC: Study of the impact on comparability of national implementations 34

15. NUMBER OF EMPLOYEES BY OCCUPATION The distribution of employees by occupation for both surveys does not present statistically significant difference. Office clerks and customer services clerks and Extraction and building trades workers, other craft and related trades workers. Metal machinery and related trades workers. Precision, handicraft, printing and related trades workers present the largest percentages among employees. Applying X 2 ν distribution tables with significance level a=0,05, for both variables (occupation/income categories), in both surveys (EU-SILC and SES), it arises that income category depends significantly on the occupation of the employee. The dependence degree of the two variables is strong for both surveys, 45,18% for EU-SILC and 47,03% for SES (see tables 18-20). What s left to be studied is if in both surveys, the same occupations depend on the same income categories. This will be done using corresponded factor analysis and Hierarchical cluster analysis and the results will be presented at factor level. Table 18. Number of employees by occupation Occupation EU SILC N SES N EU SILC % SES % 1. Legislators and senior officials-corporate managers 2. Physical, mathematical, engineering science and other professionals 3. Physical, engineering science associate professionals and other associate professionals 51.099 40.302 0,0218 0,0434 393.350 87.509 0,1676 0,0942 253.608 90.632 0,1081 0,0975 4. Office clerks and customer services clerks 448.628 220.969 0,1912 0,2378 5. Personal and protective services workers, models, salespersons and demonstrators miscellaneous 381.598 125.999 0,1626 0,1356 6. Skilled agricultural and fishery workers 19.129 1.415 0,0082 0,0015 7. Extraction and building trades workers, other craft and related trades workers. Metal machinery and related trades workers. Precision, handicraft, printing and related trades workers 8. Stationary-plant and related operators, drivers and mobile plant operators, machine operators and assemblers 9. Sales and services elementary occupations, agricultural, fishery and related labourers in mining, construction, manufacturing and transport 391.763 120.190 0,1669 0,1293 212.447 116.351 0,0905 0,1252 195.266 126.048 0,0832 0,1356 Total 2.346.888 929.415 1,0000 1,0000 EU SILC: Study of the impact on comparability of national implementations 35