Structure of earnings survey 2014 (earn_ses2014)

National Reference Metadata in ESS Standard for Quality Reports Structure (ESQRS)

Compiling agency: Statistics Belgium


Eurostat metadata
Reference metadata
1. Contact
2. Statistical presentation
3. Statistical processing
4. Quality management
5. Relevance
6. Accuracy and reliability
7. Timeliness and punctuality
8. Coherence and comparability
9. Accessibility and clarity
10. Cost and Burden
11. Confidentiality
12. Comment
Related Metadata
Annexes (including footnotes)
 



For any question on data and metadata, please contact: Eurostat user support

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1. Contact Top
1.1. Contact organisation

Statistics Belgium

1.2. Contact organisation unit

Labour Market Statistics

1.5. Contact mail address

North Gate
Koning Albert II-laan 16 

1000 Brussels


2. Statistical presentation Top
2.1. Data description

The Structure of Earnings Survey (SES) is a 4-yearly survey which provides EU-wide harmonised structural data on gross earnings and hours paid which are collected under Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs, and Commission Regulation (EC) No 1738/2005 amending Regulation (EC) No 1916/2000 as regards the definition and transmission of information on the structure of earnings.

 

2.2. Classification system

The following classifications are used:

- NACE Rev. 2 for the economic activity;

- ISCO-08 for the occupation of the worker;

- ISCED11 for the highest successfully completed level of education and training;

- NUTS for the regional breakdown.

2.3. Coverage - sector

The Belgian SES refers to local units belonging to enterprises with at least 10 employees in the areas of economic activities defined by NACE Rev. 2 sections B to S excluding O.

2.4. Statistical concepts and definitions

Employees are all persons who have a direct employment contract with the enterprise or local unit and receive remuneration, irrespective of the type of work performed, the number of hours worked (full or part-time) and the duration of the contract (fixed or indefinite).

Mean annual gross earnings also cover all 'non-standard payments', i.e. payments not occurring in each pay period, such as: 13th or 14th month payments, holiday bonuses, quarterly or annual company bonuses and annual payments in kind.

Mean monthly gross earnings in the reference month cover remuneration in cash paid before any tax deductions and social security contributions payable by wage earners and retained by the employer, and are restricted to gross earnings which are paid in each pay period during the reference month.

Mean hourly gross earnings are defined as gross earnings in the reference month divided by the number of hours paid during the same period.

Number of hours paid includes all normal and overtime hours worked and remunerated by the employer during the reference month. Hours not worked but nevertheless paid are counted as 'paid hours' (e.g. for annual leave, public holidays, paid sick leave, paid vocational training, paid special leave, etc.).

2.5. Statistical unit

The SES covers all activities defined in NACE Rev. 2 sections B to S (excluding O) for local units that belong to enterprises with at least 10 employees.

2.6. Statistical population

The SES refers to local units belonging to enterprises with at least 10 employees in the areas of economic activities defined by NACE Rev. 2 sections B to S excluding O.

2.7. Reference area

The SES refers to local units belonging to enterprises with at least 10 employees in the areas of economic activities defined by NACE Rev. 2 sections B to S excluding O.

2.8. Coverage - Time

Reference year = 2014;

Reference month = October

2.9. Base period

Not applicable.


3. Statistical processing Top
3.1. Source data

The Belgian SES makes use of three different administrative sources:

  • The national register of enterprises (DBRIS)
  • The earnings and working hours database of the National Office for Social Security (ONSS)
  • The national register of individuals (RN)

A tailor-made questionnaire (NSI) is still necessary for obtaining the information that isn't available in existing datasets. The table below gives an overview of the different Eurostat variables and the way Statistics Belgium obtained them:

 

Variable Eurostat DBRIS ONSS RN NSI
Region x      
Size of the enterprise x      
Economic activity x      
Economic and financial control   x    
Collective pay agreement   x    
Number of employees in the local unit x      
Grossing-up factor for local units x      
Sex     x  
Age     x  
Occupation       x
Level of education and training       x
Length of service in the enterprise       x
Full-time or part-time employee   x    
% share of a full-timer’s normal hours   x    
Type of employment contract       x
Number of weeks to which the gross annual earnings relate   x    
Number of hours paid during the reference month       x
Number of overtime hours paid in the
reference month
      x
Annual days of holiday leave       x
Gross annual earnings in the reference year   x    
Annual bonuses and allowances not
paid every pay period
  x    
Gross earnings in the reference month       x
Earnings related to overtime       x
Special payments for shift work       x
Average gross hourly earnings in the
reference month
      x
Grossing-up factor for employees       x

 

 

3.2. Frequency of data collection

The Belgian SES is organised on an annual basis.

3.3. Data collection

The SES 2014 was conducted based on a two-stage sampling approach. In the first stage, a stratified random sample of local units was drawn. The stratification criteria were the economic activity, the number of employees and the region of the local unit. The questionnaire, the explanation and a list of local units for which the survey needed to be filled in were sent to the head offices of the selected local units. We chose not to send the questionnaire to every local unit in the sample, since a central pay-roll administration is usually responsible for the payment of all wages. The possibility of a mistake by the enterprise, for example by taking the wrong local unit, is very limited, because every local unit in Belgium has its own unique administrative number. The continuously updated business register was used to define the sampling frame.

The chances of selection largely depended on the number of employees a local unit has. In the second stage, the local unit had to select a number of employees according to the instructions in the explanation. Local units with fewer than 300 employees had to select a proportion of their total number of workers:

 

Number of selected wage earners for local units with fewer than 300 employees 

 

Total number of employees Proportion
Fewer than 20 100%
20 - 49 50%
50 - 99 25%
100 - 199 14.3%
200 - 299 10%

 

Local units with 300 employees or more needed to select a fixed absolute number of workers:

Number of selected wage earners for local units with at least 300 employees

 

Total number of employees Number of wage earners to be selected
300 - 349 30
350 - 449 35
450 - 549 40
550 - 699 45
700 - 899 50
900 - 1,099 55
1,100 - 1,299 60
1,300 - 1,599 65
1,600 - 1,999 75
2,000 - 2,999 85
3,000 - 3,999 100
4,000 - 4,999 115
5,000 - 6,499 130
6,500 - 7,999 145
8,000 - 9,499 160
9,500 - 11,999 180
12,000 or more 200

 

To ensure that the sample was drawn on a coincidental basis, every local unit received a letter of the alphabet. The local unit had to start its selection of employees with the wage earner whose surname began with that letter. If the number of wage earners was not reached at the letter ‘Z’, the selection continued with the letter ‘A’. No stratification criteria were used in this second stage, because we wanted to keep this step as easy as possible for the respondents.

3.4. Data validation

Data validation consists of global checks and plausibility checks. Global checks are necessary to ensure that complete data are available. Plausibility checks on all variables were done to ensure that the data are reasonable and consistent with other variables.

3.5. Data compilation

Not applicable

3.6. Adjustment

Not applicable


4. Quality management Top
4.1. Quality assurance

Before transmission to Eurostat, the results of the SES are checked internally by the validation team. Also Eurostat validates the results by using several global checks and plausibility checks. Finally the Quality Report contains all relevant information to enable the quality of the statistic to be evaluated.

4.2. Quality management - assessment

SES microdata are checked for completeness and consistency.


5. Relevance Top
5.1. Relevance - User Needs

The results and data of the Structure of Earnings Survey (SES) are often used by the Belgian general public. Students, research centres, universities, trade unions, the media, private companies and public administration institutions can all be considered as important users of the SES.

One reason for this interest from a wide range of users comes from the large survey sample. Because of these large numbers, the SES can give a correct image of the gross earnings by several independent variables. Together with the Labour Force Survey, the SES is for example the only national source where earnings can be linked with important personal characteristics such as the level of education or the occupation of the worker. The rather unique combination between individual features on the one hand and enterprise characteristics on the other hand can also explain the broad use of the SES.

5.2. Relevance - User Satisfaction

Although almost all demands can be met by the existing information and variables, there is still much interest in more personal characteristics of the workers. Aspects such as nationality or household situation of the worker often influence the earnings and labour time. Also in the framework of the gender pay gap this information would be very useful.

5.3. Completeness

Not applicable.

5.3.1. Data completeness - rate

Not applicable.


6. Accuracy and reliability Top
6.1. Accuracy - overall

The SES 2014 was conducted based on a two-stage sampling approach. In the first stage, a stratified random sample of local units was drawn. The stratification criteria were the economic activity, the number of employees and the region of the local unit. The questionnaire, the explanation and a list of local units for which the survey needed to be filled in were sent to the head offices of the selected local units. We chose not to send the questionnaire to every local unit in the sample, since a central pay-roll administration is usually responsible for the payment of all wages. The possibility of a mistake by the enterprise, for example by taking the wrong local unit, is very limited, because every local unit in Belgium has its own unique administrative number. The continuously updated business register was used to define the sampling frame.

The chances of selection largely depended on the number of employees a local unit has. In the second stage, the local unit had to select a number of employees according to the instructions in the explanation. Local units with fewer than 300 employees had to select a proportion of their total number of workers:

Number of selected wage earners for local units with fewer than 300 employees 

 

Total number of employees Proportion
Fewer than 20 100%
20 - 49 50%
50 - 99 25%
100 - 199 14.3%
200 - 299 10%

 

Local units with 300 employees or more needed to select a fixed absolute number of workers:

Number of selected wage earners for local units with at least 300 employees

 

Total number of employees Number of wage earners to be selected
300 - 349 30
350 - 449 35
450 - 549 40
550 - 699 45
700 - 899 50
900 - 1,099 55
1,100 - 1,299 60
1,300 - 1,599 65
1,600 - 1,999 75
2,000 - 2,999 85
3,000 - 3,999 100
4,000 - 4,999 115
5,000 - 6,499 130
6,500 - 7,999 145
8,000 - 9,499 160
9,500 - 11,999 180
12,000 or more 200

 

To ensure that the sample was drawn on a coincidental basis, every local unit received a letter of the alphabet. The local unit had to start its selection of employees with the wage earner whose surname began with that letter. If the number of wage earners was not reached at the letter ‘Z’, the selection continued with the letter ‘A’. No stratification criteria were used in this second stage, because we wanted to keep this step as easy as possible for the respondents.

6.2. Sampling error

See 6.2.1. for more information concerning the sampling errors.

6.2.1. Sampling error - indicators

In general, the coefficients of variation are low, although there are several exceptions. Especially in the breakdowns with a limited number of workers, it is almost impossible to organise a survey in which these groups are measured correctly without being exhaustive. This problem appears in several NACE-sections, in the ISCO 1 and finally in the age groups under 20 and 60 years and over.

Please see the attached document for detailed figures on the Coefficients of variation.



Annexes:
Coefficients of variation
6.3. Non-sampling error

See further for more details on the non-sampling errors.

6.3.1. Coverage error

There were no differences between the reference and the study population. The universe and the sample survey were drawn up from the most recent business register available at the time. This register gives an overview of all enterprises and local units that had wage earners in service on 30 September 2014. Under or over coverage was therefore possible but would have a very limited impact, as only those local units who started or ceased their activities during the month of October could be affected.

With regard to the size of the enterprise Belgium chose to exclude the small enterprises with fewer than ten employees. We also excluded the NACE section O in our sample. This means that the Belgian datasets only include the local units covered by the Regulation.

6.3.1.1. Over-coverage - rate

Not applicable

6.3.1.2. Common units - proportion

Not applicable

6.3.2. Measurement error

In order to detect outliers and other quality problems, several aggregated checks were integrated into the different data collection tools. More complicated inconsistency problems were solved internally or by contacting the local unit on a bilateral basis.

6.3.3. Non response error

The unit response rate for the entire survey amounts to 71%. The table below gives an overview of the response rates by economic activity: 

Main economic activity

Number of local units in the sample

Number of local units in the survey

Response rate

X08

25

21

84%

X09

1

0

0%

X10

327

221

68%

X11

36

31

86%

X12

13

12

92%

X13

90

69

77%

X14

35

23

66%

X15

10

9

90%

X16

53

32

60%

X17

56

38

68%

X18

53

33

62%

X19

10

10

100%

X20

169

119

70%

X21

56

36

64%

X22

87

65

75%

X23

154

112

73%

X24

103

65

63%

X25

255

168

66%

X26

81

49

60%

X27

77

56

73%

X28

148

94

64%

X29

84

66

79%

X30

27

25

93%

X31

38

25

66%

X32

59

44

75%

X33

63

41

65%

X35

84

61

73%

X36

39

35

90%

X37

22

15

68%

X38

112

86

77%

X39

16

15

94%

X41

160

112

70%

X42

132

96

73%

X43

322

234

73%

X45

193

118

61%

X46

593

399

67%

X47

737

524

71%

X49

318

235

74%

X50

11

8

73%

X51

13

10

77%

X52

174

131

75%

X53

115

109

95%

X55

110

68

62%

X56

208

114

55%

X58

50

36

72%

X59

31

23

74%

X60

32

24

75%

X61

77

28

36%

X62

122

85

70%

X63

40

24

60%

X64

238

202

85%

X65

67

50

75%

X66

83

51

61%

X68

61

32

52%

X69

82

53

65%

X70

114

80

70%

X71

136

99

73%

X72

64

50

78%

X73

66

46

70%

X74

50

27

54%

X75

10

10

100%

X77

74

40

54%

X78

451

371

82%

X79

58

38

66%

X80

45

26

58%

X81

338

235

70%

X82

130

92

71%

X84

17

0

0%

X85

710

640

90%

X86

398

255

64%

X87

599

412

69%

X88

504

337

67%

X90

52

36

69%

X91

59

36

61%

X92

20

8

40%

X93

93

53

57%

X94

160

98

61%

X95

30

23

77%

X96

67

43

64%

Total

10.597

7.497

71%

6.3.3.1. Unit non-response - rate

See 6.3.3 for more information

 

6.3.3.2. Item non-response - rate

See 6.3.3. for more information

 

6.3.4. Processing error

See further for more details.

6.3.4.1. Imputation - rate

Item imputation rate

Data completeness is one of the advantages of an administrative register. Consequently, for those variables of which the information is derived from existing datasets, the item imputation rates equals to 0 %.

For the variables included in the questionnaire, the item imputation rate is highest for the level of education. For 15.402 workers or 11.0 % of the cases, this information was imputed. Enterprises often inform us about the difficulties to obtain this specific piece of information. In general, the level of education is less relevant for enterprises, since their workers can compensate a lower degree of education by experience or other skills. This information therefore often remains uncentralised.

The occupation of the worker is the other variable with an high item imputation rate. For all the other variables the item imputation rates are less than 0.2 %.

 

Overall imputation rate

Given the very low item imputation rates, the overall rate is also negligible. Here all the information at the level of the local unit is derived from administrative datasets, the overall imputation rate for Record A equals to 0 %. Also for Record B this imputation rate is limited to 0.9 %.

6.3.5. Model assumption error

No assumptions are made.

6.4. Seasonal adjustment

No seasonal adjustment takes place.

6.5. Data revision - policy

SES data aren't revised.

6.6. Data revision - practice

SES data aren't revised.

6.6.1. Data revision - average size

SES data aren't revised.


7. Timeliness and punctuality Top
7.1. Timeliness

The two records with the thoroughly checked and internally approved data were sent to Eurostat on 28 June 2016. The data delivery took place before the deadline stipulated by the Regulation.

7.1.1. Time lag - first result

The two records with the thoroughly checked and internally approved data were sent to Eurostat on 28 June 2016. The data delivery took place before the deadline stipulated by the Regulation.

7.1.2. Time lag - final result

The two records with the thoroughly checked and internally approved data were sent to Eurostat on 28 June 2016. The data delivery took place before the deadline stipulated by the Regulation.

7.2. Punctuality

The field work started by sending the questionnaires on January 2015. At first the respondents/ enterprises had time until the end of February to fill in the questionnaire. Respondents who did not answer within this deadline received a first reminder early March and a second in April.

More intensive contact attempts were held in May and June. They aimed at convincing respondents to participate and at increasing the unit response rate. For the most important local units phone contacts were replaced with a visit. An employee of Statistics Belgium could then help respondents fill in the questionnaire when this was necessary. The field work was closed in September 2015, i.e. eight
months after the start.

Data processing started as soon as the questionnaires were sent to the respondents. For the overall quality of the data, we aim to check the received data as soon as possible. This allows us to contact the respondent within an acceptable time span when errors or missing items are detected.

Besides the survey data, some administrative sources were used to calculate the Eurostat variables. Even if these sources have several advantages, such as the correctness and the completeness of the data, they also have an important disadvantage: some of them were not received before spring 2016.

The final results of the SES 2014 were published in July 2016.

7.2.1. Punctuality - delivery and publication

See general point 7.2.


8. Coherence and comparability Top
8.1. Comparability - geographical

Belgium has strictly followed the content of the Regulation. Geographical comparability should therefore be ensured.

A remark for education professionals is nevertheless in place. In Belgium the contractual labour time of these professionals differs substantially from the effectively performed labour time. This group of employees works several non-paid hours per week preparing classes and correcting student exams. This rather limited number of hours paid influences the amount of the hourly earnings, so variable B32 is used as the denominator there. The hourly earnings for this specific group of employees are therefore rather high and could differ substantially from the earnings available for other countries.

8.1.1. Asymmetry for mirror flow statistics - coefficient

Not applicable

8.2. Comparability - over time

The SES 2014 is completely comparable with the SES 2010, there the same method and data sources are used.

Compared with the SES 2006, the SES 2010 used another classification for the variables concerning the economic activity of the local unit and for the occupation of the worker. Because the economic activity is one of the three stratification criteria, this change in classification could influence the comparability of the results between these two reference years.

Additionally, the surveys starting from reference years 2006 differ from the SES 2002 in two ways:

  1. In 2002, the main economic activity of the local unit was unknown. For this survey we worked with the assumption that the economic activity of the local unit was exactly the same as the activity of the enterprise to which it belonged. Since the SES 2006, this problem has been solved, so one enterprise could have local units executing different activities.
  2. In 2002, the definition of a local unit did not correspond with the concept used by Eurostat. According to the Belgian definition, a company could never have more than one local unit with the same economic activity in one municipality. This meant that in 2002 a company was supposed to count up the wage earners of all its local units in every municipality. In the meantime, the Belgian definition of a local unit was adapted to the European rules. Since the SES 2006, it is therefore possible that one enterprise has several local units with the same activity in the same municipality.
8.2.1. Length of comparable time series

See point 8.2.

8.3. Coherence - cross domain

The following table compares the survey’s variable “Gross annual earnings in the reference year” with the variable “wages and salaries” from the national accounts. Comparisons between these two sources should nevertheless be done carefully, because several differences concerning the target population and the followed methodology exist. The figures of the national accounts include for example businesses with fewer than ten employees, while these enterprises are excluded in the SES.

Given the above remarks, the figures are nevertheless comparable for the majority of economic activities:

A13

NA - D11

SES - B41

D11 / B41

X08-X09

48.375

44.052

91%

X10-X12

38.322

40.175

105%

X13-X15

33.121

38.748

117%

X16-X19

39.251

44.397

113%

X19

109.205

73.165

67%

X20

65.439

56.449

86%

X21

59.304

51.481

87%

X22-X23

44.259

46.048

104%

X24-X25

43.931

45.849

104%

X26

54.353

56.169

103%

X27

44.191

46.103

104%

X28

47.049

45.668

97%

X29-X30

46.075

45.088

98%

X31-X33

42.404

44.206

104%

X35

74.125

66.852

90%

X36-X39

45.907

47.230

103%

X41-X43

36.870

40.093

109%

X45-X47

37.882

38.971

103%

X49-X53

39.216

40.334

103%

X55-X56

24.493

24.999

102%

X58-X60

53.900

49.361

92%

X61

56.471

54.249

96%

X62-X63

62.468

54.550

87%

X64-X66

60.798

57.054

94%

X68

33.562

46.905

140%

X69-X71

52.896

58.091

110%

X72

78.644

67.280

86%

X73-X75

45.408

45.814

101%

X77-X82

26.517

26.364

99%

X85

37.962

40.814

108%

X86

37.361

35.461

95%

X87-X88

28.151

26.866

95%

X90-X93

33.341

32.033

96%

X94-X96

33.150

36.621

110%

 

 

8.4. Coherence - sub annual and annual statistics

Not applicable

8.5. Coherence - National Accounts

See 8.3. for a comparison between National Accounts and the SES.

8.6. Coherence - internal

Not applicable


9. Accessibility and clarity Top
9.1. Dissemination format - News release

Every year, Statistics Belgium publishes a press release to explain and illustrate the main results of the SES. This communiqué is generally broadly covered by Belgian newspapers and news agencies.

9.2. Dissemination format - Publications

In Belgium, the SES is organised on a yearly basis and is therefore well-known by the general public. Nevertheless, each year we use several channels to disseminate the SES results.

The results of the SES are also integrated in several publications. Some key results are included in the annual key figures published by Statistics Belgium. Also the annual Gender Pay Gap Report is worth mentioning. This elaborate publication describes the differences between men and women in the Belgian labour market. The SES is by far the most important source of this report.

9.3. Dissemination format - online database

The main channel to communicate the results is the dedicated section on the website of Statistics Belgium. This webpage contains the most popular aggregated tables, but visitors can also compose their own tables with our dynamic application. The earnings information is one of the most popular sections of the website, with more than 1,000 unique visitors every month.

9.3.1. Data tables - consultations

See 9.3. for more information on this point.

9.4. Dissemination format - microdata access

Researchers can obtain microdata for their research project. On the website of Statistics Belgium, researchers can find more information on the procedure.  

The Belgian SES anonymised microdata are also accessible via CD-ROM by following the Eurostat procedure.

9.5. Dissemination format - other

For users needing more detailed data, Statistics Belgium can produce tailor-made tables. 

9.6. Documentation on methodology

The metadata are published on the website of Statistics Belgium.

9.7. Quality management - documentation

The metadata are published on the website of Statistics Belgium.

9.7.1. Metadata completeness - rate

100%

9.7.2. Metadata - consultations

The metadata are published on the website of Statistics Belgium.


10. Cost and Burden Top

Statistics Belgium tries to reduce the burden for enterprises by using intensively administrative datasets. Yet a questionnaire is necessary to complete missing information. The cost for business to complete this questionnaire is measured yearly.


11. Confidentiality Top
11.1. Confidentiality - policy

The Belgian confidentiality policy is followed. More information can be found on the website of Statistics Belgium.

11.2. Confidentiality - data treatment

The Belgian confidentiality policy is followed. More information can be found on the website of Statistics Belgium.


12. Comment Top

Not applicable


Related metadata Top


Annexes Top