Joint Programming Initiative

More Years, Better Lives

The Potential and Challenges of Demographic Change

Data Warehouse Labour Market and Social Protection (DWH LM&SP) – career data on retired individuals
Datawarehouse Arbeidsmarkt en Sociale Bescherming (DWH AM&SB) – loopbaangegevens gepensioneerden

Topic
Work and Productivity
Social Systems and Welfare
Relevance for this Topic
Country Belgium
URL
www.ksz-bcss.fgov.be/nl/bcss/nodepage/content/websites/belgium/
www.ksz-bcss.fgov.be/nl/bcss/nodepage/content/websites/belgium/
More Topics

Governance

Contact information

Chris Brijs
Crossroads Bank for Social Security
Willebroekkaai 38
1000 Brussels
Belgium
Phone: +32 2 741 83 67
Fax: +32 2 741 83 00
Email: chris.brijs(at)ksz-bcss.fgov.be
Url: www.ksz-bcss.fgov.be/nl/bcss/nodepage/content/websites/belgium/

Timeliness, transparency

The data are available two years following collection.

Type of data


Registry

Type of Study


Longitudinal administrative data

Data gathering method

Registries

Type of data


Registry

Type of Study


Longitudinal administrative data

Data gathering method

Registries


Access to data


The data are available for academic and policy research. Researchers and policy-makers can either use the microdata or online modules to generate aggregate data.

Conditions of access


To apply for microdata, a data request has to be submitted to the Crossroads Bank for Social Security. The Crossroads Bank then investigates whether this request furthers the ‘knowledge, conception and management of social security’. Subsequently, the Crossroads Bank investigates whether the request is technically and organisationally feasible. The researchers applying for the data are informed about the Crossroads Bank’s decision within two months. In a next step, the Crossroads Bank submits the data request to the Privacy Commission (i.e. Commission for the protection of privacy [Commissie voor de bescherming van de persoonlijke levenssfeer / Commission de la protection de la vie privée]), and more specifically to the subcommittee on Social Security & Health [Comité Sociale Zekerheid and Gezondheid / Comité Sécurité Sociale and Santé], that meets once a month. The Privacy Commission investigates whether the data request is in line with privacy legislation. If the Privacy Commission believes this is so, the data request still has to be authorised by the Crossroad Bank’s Management Committee [Beheerscomité / Comité de Gestion]. In practice, however, this committee follows the Privacy Commission’s advice. Within a month after the decision of the Management Committee, the Crossroads Bank provides a plan with regard to the delivery of the data. Once a contract is set up between the institute requesting the data and the Crossroads Bank, the institute has to notify the Privacy Commission. No fixed prices are available. From our experience, however, we know that most data requests cost between €2,000 and €3,000. If the data are linked to data that are not available in the Data Warehouse Labour Market and Social Protection (e.g. survey data or other administrative data such as fiscal data), the data request is substantially more expensive. Aggregate tables using the data from the Data Warehouse Labour Market and Social Protection can be generated using online modules available on the Crossroad Bank’s website (cf. supra). These modules can be used freely and without any cost. The website is only available in French or in Dutch.


Anonymised microdata are available for a period of up to 6 months after the application. Aggregate tables using the data from the Data Warehouse Labour Market and Social Protection are immediately available.


Anonymised microdata; aggregated tables in online module


SAS, Excel, PDF


Data are available in Dutch and French.

Access to data


The data are available for academic and policy research. Researchers and policy-makers can either use the microdata or online modules to generate aggregate data.

Conditions of access


To apply for microdata, a data request has to be submitted to the Crossroads Bank for Social Security. The Crossroads Bank then investigates whether this request furthers the ‘knowledge, conception and management of social security’. Subsequently, the Crossroads Bank investigates whether the request is technically and organisationally feasible. The researchers applying for the data are informed about the Crossroads Bank’s decision within two months. In a next step, the Crossroads Bank submits the data request to the Privacy Commission (i.e. Commission for the protection of privacy [Commissie voor de bescherming van de persoonlijke levenssfeer / Commission de la protection de la vie privée]), and more specifically to the subcommittee on Social Security & Health [Comité Sociale Zekerheid and Gezondheid / Comité Sécurité Sociale and Santé], that meets once a month. The Privacy Commission investigates whether the data request is in line with privacy legislation. If the Privacy Commission believes this is so, the data request still has to be authorised by the Crossroad Bank’s Management Committee [Beheerscomité / Comité de Gestion]. In practice, however, this committee follows the Privacy Commission’s advice. Within a month after the decision of the Management Committee, the Crossroads Bank provides a plan with regard to the delivery of the data. Once a contract is set up between the institute requesting the data and the Crossroads Bank, the institute has to notify the Privacy Commission. No fixed prices are available. From our experience, however, we know that most data requests cost between €2,000 and €3,000. If the data are linked to data that are not available in the Data Warehouse Labour Market and Social Protection (e.g. survey data or other administrative data such as fiscal data), the data request is substantially more expensive. Aggregate tables using the data from the Data Warehouse Labour Market and Social Protection can be generated using online modules available on the Crossroad Bank’s website (cf. supra). These modules can be used freely and without any cost. The website is only available in French or in Dutch.


Anonymised microdata are available for a period of up to 6 months after the application. Aggregate tables using the data from the Data Warehouse Labour Market and Social Protection are immediately available.


Anonymised microdata; aggregated tables in online module


SAS, Excel, PDF


Data are available in Dutch and French.


Coverage


1955-2012


Information on the careers of employees: 1955; Information on the careers of civil servants and self-employed: entire career for all individuals retiring from 2001 onwards.


Population dataset; no sample


Breakdown by region (Flanders, Wallonia, Brussels Capital Region), by province, by municipality and by district.


The total population is covered.


The DWH LM & SP is the most important dataset to study social systems and welfare in Belgium. To understand the data that are available, note that first pillar pensions in Belgium are calculated on the basis of the previous career (most importantly, the number of years worked and the wages earned). Hence, datasets have been set up that contain such career information. Separate datasets exist to calculate the pensions of employees, the self-employed and civil servants. The Sigedis dataset contains information on the careers of employees since the mid 1950’s. This career information is not only available for retirees, but also for individuals of active age. The career information used to calculate the pensions of the self-employed and civil servants, in contrast, is only available for retirees. The reason is that this information is only gathered at the time of retirement. The data on the self-employed are available from the National Institute for the Social Security of the Self-employed and the data on civil servants is from the Pension Service of the Public Sector [Pensioendienst voor de overheidssector / Service des pensions du secteur publique].


The following studies use the information available on the careers of retired individuals: • Braes, S., Herremans, W., & Sels, L. “De M/V loopbaan(kloof). Een reconstructie van de loopbaanopbouw van recent gepensioneerden”. Over.Werk 21(3) (2011): 13-19. • Van Looy, D., De Preter, H., & Mortelmans, D. “Arbeidsduurvermindering en pensioneringsintenties van vijftigplussers op de Vlaamse arbeidsmarkt”. Over.Werk 22(2) (2012): 28-36.

Coverage


1955-2012


Information on the careers of employees: 1955; Information on the careers of civil servants and self-employed: entire career for all individuals retiring from 2001 onwards.


Population dataset; no sample


Breakdown by region (Flanders, Wallonia, Brussels Capital Region), by province, by municipality and by district.


The total population is covered


The DWH LM & SP is the most important dataset to study social systems and welfare in Belgium. To understand the data that are available, note that first pillar pensions in Belgium are calculated on the basis of the previous career (most importantly, the number of years worked and the wages earned). Hence, datasets have been set up that contain such career information. Separate datasets exist to calculate the pensions of employees, the self-employed and civil servants. The Sigedis dataset contains information on the careers of employees since the mid 1950s. This career information is not only available for retirees, but also for individuals of active age. The career information used to calculate the pensions of the self-employed and civil servants, in contrast, is only available for retirees. The reason is that this information is only gathered at the time of retirement. The data on the self-employed are available from the National Institute for the Social Security of the Self-employed and the data on civil servants is from the Pension Service of the Public Sector [Pensioendienst voor de overheidssector / Service des pensions du secteur publique].


The following studies use the information available on the careers of retired individuals: • Braes, S., Herremans, W., & Sels, L. “De M/V loopbaan(kloof). Een reconstructie van de loopbaanopbouw van recent gepensioneerden”. Over.Werk 21(3) (2011): 13-19. • Van Looy, D., De Preter, H., & Mortelmans, D. “Arbeidsduurvermindering en pensioneringsintenties van vijftigplussers op de Vlaamse arbeidsmarkt”. Over.Werk 22(2) (2012): 28-36.


Linkage


NACE-coding is used (i.e. statistical classification of economic activities in the European Community, developed by Eurostat)


The National Register number is integrated in all administrative datasets. In this way, information available in the Data Warehouse Labour Market and Social Protection can be linked to data from the National Register [Rijksregister / Registre National], containing additional information on personal and household characteristics. As many other administrative datasets and survey datasets contain National Register numbers, it becomes possible to link the Data Warehouse Labour Market and Social Protection data to several other datasets. In this regard, it is important to notice that the Privacy Commission has stated under what conditions survey data from Statistics Belgium can be linked to the Data Warehouse.

Linkage


NACE-coding is used (i.e. statistical classification of economic activities in the European Community, developed by Eurostat)


The National Register number is integrated in all administrative datasets. In this way, information available in the Data Warehouse Labour Market and Social Protection can be linked to data from the National Register [Rijksregister / Registre National], containing additional information on personal and household characteristics. As many other administrative datasets and survey datasets contain National Register numbers, it becomes possible to link the Data Warehouse Labour Market and Social Protection data to several other datasets. In this regard, it is important to notice that the Privacy Commission has stated under what conditions survey data from Statistics Belgium can be linked to the Data Warehouse.


Data quality


General information on data quality of the DWH LM&SP: Data quality is high. However, given the detail of the information, data cleaning is far from straightforward and requires a thorough understanding of Belgian social security. Given the complexity of the recoding that is needed to make the data available for scientific research, errors can occur. These errors can be adjusted in collaboration with the Crossroads Bank for Social Security. Changes in legislation and registration can impact the content of the variables. Specific information related to the study of the careers of self-employed: The data on the self-employed are of lower quality than the data on employees and civil-servants.

Data quality


General information on data quality of the DWH LM&SP: Data quality is high. However, given the detail of the information, data cleaning is far from straightforward and requires a thorough understanding of Belgian social security. Given the complexity of the recoding that is needed to make the data available for scientific research, errors can occur. These errors can be adjusted in collaboration with the Crossroads Bank for Social Security. Changes in legislation and registration can impact the content of the variables. Specific information related to the study of the careers of self-employed: The data on the self-employed are of lower quality than the data on employees and civil-servants.


Applicability


Strengths: The typical strengths associated with administrative data apply. The use of administrative data is cost-effective, data quality is high, non-response is inexistent, etc. Specifically for life-course researchers, there are several added advantages, such as lack of attrition in between waves, lack of memory bias, etc. Typical for the Belgian situation is that all administrative datasets contain the National Register number and can therefore accurately be linked. Weaknesses: Apart from the typical weaknesses of administrative data (e.g. lack of data on opinions, motivations etc.), the following problems can be mentioned: (1) There is no information on educational levels; (2) Due to an evolution in register systems, the data contain some statistical breaks; (3) Data on personal and household characteristics only become available with a three year time lag; (4) Information on the Data Warehouse Labour Market and Social Protection is only available in French and Dutch; (5) Belgian social security is extremely complex. As a consequence, the data that follow from it are also highly technical. This means that it is almost impossible to use the data without thorough and detailed knowledge of the Belgian social security system. We therefore strongly advise foreign researchers to collaborate with Belgian research teams that have experience with the data. A specific strength of the career data on retired individuals has to do with the time span, with data on employees going back as early as 1955. A weakness is that, given the large time span, many data breaks occur.

Applicability


Strengths: The typical strengths associated with administrative data apply. The use of administrative data is cost-effective, data quality is high, non-response is inexistent, etc. Specifically for life-course researchers, there are several added advantages, such as lack of attrition in between waves, lack of memory bias, etc. Typical for the Belgian situation is that all administrative datasets contain the National Register number and can therefore accurately be linked. Weaknesses: Apart from the typical weaknesses of administrative data (e.g. lack of data on opinions, motivations etc.), the following problems can be mentioned: (1) There is no information on educational levels; (2) Due to an evolution in register systems, the data contain some statistical breaks; (3) Data on personal and household characteristics only become available with a three year time lag; (4) Information on the Data Warehouse Labour Market and Social Protection is only available in French and Dutch; (5) Belgian social security is extremely complex. As a consequence, the data that follow from it are also highly technical. This means that it is almost impossible to use the data without thorough and detailed knowledge of the Belgian social security system. We therefore strongly advise foreign researchers to collaborate with Belgian research teams that have experience with the data. A specific strength of the career data on retired individuals has to do with the time span, with data on employees going back as early as 1955. A weakness is that, given the large time span, many data breaks occur.


  • The information about this dataset was compiled by the author:
  • Hans Peeters
  • (see Partners)