Statistics Belgium

Labour Market Statistics

North Gate
Koning Albert II-laan 16 

1000 Brussels

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New concept added with the migration to SIMS 2.0.
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New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

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New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

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New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

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New concept added with the migration to SIMS 2.0.
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New concept added with the migration to SIMS 2.0.
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New concept added with the migration to SIMS 2.0.
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Different sources of the SES

In Belgium, the emphasis is clearly shifting towards an intensive use of administrative sources wherever possible. For this survey three important administrative sources were used:

• 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)

The questionnaire only included these variables where no information was available from the administrative sources (NSI). The table below gives an overview of the different Eurostat variables and the way Statistics Belgium obtained them:

Source of each variable

Sampling technique

The SES 2010 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 universe consisted of 55,989 local units. Eventually 9,420 local
units were included in the sample survey. 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 

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

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.

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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.

Use of SES – variables in tailor-made tables

To indicate the importance of a variable for the general public, the above table gives an overview of the number of times a variable has been used in tailor-made tables. These tables are made to cover specific demands. On a yearly basis, our service receives around 250 demands for such tailor-made tables. Demands for microdata are not included in this list, as these demands normally contain almost every variable.

The most popular variable is by far gross monthly earnings during the reference month. Other frequently asked variables are economic activity, occupation, sex and the variable indicating whether an employee is working on a full-time or part-time basis. We also notice a limited interest for several other variables and some of them, such as the annual days of holiday leave, are not even included in any of the tailormade tables.

Overview of the most important users of the SES

In Belgium, the Structure of Earnings Survey is organised on a yearly basis. Therefore, this survey has many structural users, who make use of the results every year. The next section gives an overview of the main users and their projects.

• Every year ‘The Institute for the Equality of Women and Men’ publishes a detailed report concerning the gender pay gap in Belgium. Since the beginning of this report, the SES has been used as the source of the necessary figures. The advantage of the SES is that this survey makes it possible to calculate several breakdowns, e.g. by gender. In Belgium, this report has an important reporting and policy recommendation function.
• The Federal Public Service Finance calculates the average tax wedges every year. To make international comparisons possible, a representative wage is used. This international concept corresponds to the average wage of full-time wage earners working in the NACE sections B-N. In other words, the FPS Finance calculates the average wages in Belgium on the basis of the SES. This survey has another important advantage. The data make it possible to take into account the impact of structural changes on the labour market, such
  as the shift to part time work.
• The Department of Applied Economics of the Free University of Brussels conducts research into the impact of wage dispersion on the performance of enterprises. For this research, the SES variables are linked to variables from the Structural Business Survey, such as turn-over or profit.
• The Federal Planning Bureau manages a labour market database that was created within the framework of the European EU KLEMS productivity measurement project and serves as the backbone for a Social Accounting Matrix compatible with Belgian National Accounts aggregates. Although this database is primarily grounded on administrative data, some information, such as the earnings by level of education or occupation, is only available in
  the SES.
• The Central Economic Council, an advisory body for the business community, uses the SES to support their reports with the necessary figures. The wage and the labour time data from the SES are also used as an input for social bargaining.

Description of the gaps and less relevant parts

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.

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See 6.2.1. for more information concerning the sampling errors.

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, in the ISCED 6 and finally in the age groups under 20 and 60 years and over.

Please see the attached documents Coefficients of variation.

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

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 2010.

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. No official numbers were available for under coverage. The number of selected local units that did not exist anymore at the moment of the survey or of which the number of employees had been reduced to fewer than 10 wage earners, amounted to 106 local units, or 1.1% of the sample survey.

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.

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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.

The unit response rate for the entire survey amounts to 82 %. As indicated in the table below, these rates vary substantially between the different economic activities. Especially in the non-business economy the response rates are relatively low.

Unit response rate by economic activity

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See further for more details.

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 4,307 workers or 3.1 % 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.

Additionally, with a rate of 2.1 %, the annual days of holiday leave are often imputed. The calculation of these days is often complex, since several aspects such as age or working hours must be taken into account.

For all the other variables the item imputation rates is 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 0.6 %.

No assumptions are made.

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The two records with the thoroughly checked and internally approved data were sent to Eurostat on 28 June 2012. The data delivery took place before the deadline stipulated by the Regulation.

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The field work started by sending the questionnaires on 15 January 2011. 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 2011, 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 2012.

The final results of the SES 2010 were published in July 2012.

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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.

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Compared with the SES 2006, the SES 2010 uses 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 with reference years 2006 and 2010 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.

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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. The biggest variation can be found in section L. However, these real estate activities only count a limited number of workers. It could also be mentioned that in this NACE section 60 % of the workers are employed in small enterprises excluded from the SES sample.

Comparison between the SES and the national accounts

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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. Moreover, the SES is also used for other press releases, in which the data are combined with the results from other surveys. A press release dedicated to singles is a recent example of this approach.

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. A similar initiative is taken by the Labour Market section. This division of Statistics Belgium publishes their own yearbook, containing more detailed information on the most important figures of the different statistics. Finally, 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.

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.

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For users needing more detailed and unique data, Statistics Belgium offers two possibilities. On the one hand, we produce aggregated tables according to the preferences of our users. On a yearly basis, our service receives around 250 demands for such tailor-made tables. On the other hand, we give researchers the possibility to use micro-data for their research projects. The number of demands for
these data is limited to a few projects every year.

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The metadata are published on the website of Statistics Belgium.

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