Statistical processing

Source data

KAS is based on the Labour Market Account (LMA). The data sources in LMA are various internal and external registers, e.g.:

• eIncome register
• The central business register
• The register with information about persons receiving public benefits
• The educational register
• The employment classification module
• The income register
• The population register
• The register for persons receiving maternity or sickness benefit

Frequency of data collection

The statistic is annually.

Data collection

The data collection is done by separate processing of each source register. After that a transverse data processing is done (also called treatment of overlaps) where information in the various registers are compared, and corrected when needed. Finally data are linked to other registers to add background information and form the population.

Data validation

The data foundation for KAS isThe Labour Market Account (LMA). LMA is produced both with and without an hourly standardization. The non-hourly standardized longitudinal register (LMA-UN) is the data foundation for RAS, and therefore the data validation takes place in LMA-UN.

In connection to the production of LMA a comprehensive validation of each input data is done. The most important ones are:

1. The data source for wage earner jobs are the eIncome register. The wage earner jobs contains information about which workplace the job is at. The workplace is the foundation for the information about industry, sector and geography. In some cases the reporting from the employer are incorrect. In that case a correction of the errors are conducted. The eIncome register contains information about work function (DISCO-08) for persons employed at workplaces covered by the wage statistic. If the workplace is not covered by the wage statistic the information about work function comes from the work classification module when it's available here. In addition other errors are corrected by the eIncome register.

2. The data source for information about self-employed is the business register, the income statistic, the eIncome register and the unemployment statistic. These sources are individually validated at the formation of information about self-employed.

3. The data source for information about absence due to sickness and maternity leave is the statistic of maternity leave and sickness benefits. Data is processed a great deal compared to e.g. a temporary determination of whether the absence is from employment or unemployment.

Transverse data treatment/data validation

The purpose of the transverse treatment/validation of data is to erase, correct or create labour market conditions in cases where the various data sources do not coincide. This is done by a so called treatment of overlaps. The rules used for the treatment are complex. Here some of the most important areas are mentioned:

• Selection of jobs for self-employed on basis of a series of criteria
• Determination of whether the absence due to sickness or maternity leave is from employment or unemployment
• Harmonizing information about subsidized employment

After that data is connected to other registers etc.

Data compilation

The data compilation in LMA takes place in several steps. The first step in the data processing is to identify and correct errors in data from various sources, and put data in one joint and homogenous source data base. From different statistics data on public benefits, wage earners, self-employed, assisting spouses, persons in education, maternity leave and sickness benefits are joint. An imputation of the paid hours for self-employed and assisting spouses are also done. Afterwards 'illegal overlaps' between conditions are being corrected, and connections between various conditions are made.

After the processing of overlaps a classification of the population’s attachment to the labour market are made on the basis of the international guidelines from ILO, which is further described in item 2.2 Classification system. The guidelines consist among others of a set of rules for prioritizing the primary attachment to the labour market. The guidelines dictates that employment is prioritized higher than unemployment, while unemployment is prioritized higher than conditions outside the labour force. Data is also linked the business register to get background information (industry, sector, address for the work place) concerning the work places where the employed persons work. Linking to the population register is also made with the aim of deciding whether the person is resident in Denmark at the time of reference.

From this processing of data the so called LMA-UN is made, and this non-hourly standardized longitudinal register with information about the populations connection to the labour market is the data foundation for KAS.

An average calculation

Information about the population's primary attachment to the labour market is the mains variable in KAS, and the statistic is an average of the primary attachment to the labour market over the year divided into quarters. That means that the average of the quarter is calculated bases on information about the primary labour market attachment on every day of the given quarter. Since LMA contains information about the population on every day of the year, it is therefore possible to calculate an average that includes all of the activities a person would have in the specific quarter. This method is chosen to present the most precise image of the population's attachment to the labour market, by including every person and their labour market attachment in the calculation to the exact extent the activity is relevant.

Background information Besides from the primary attachment to the labour market KAS also contains information about the person, such as education, age and residence, and about the workplace, such as industry, sector and workplace municipality. These information are also included in the average calculation with the exact number of days in the specific condition. That means that a person who for example changes municipality of residence during the quarter are included in both municipalities with the precise number of days. By including changes during the quarter it is possible to present a more precise image of the population and the population's attachment to the labour market.

An exception of the above is the information about the populations highest completed education. This information are included in KAS, but is in contrast to the rest of the information not gathered directly from LMA. The information about education is gathered from Statistic Denmarks register of education. This register is like LMA a longitudinal register with information about the populations highest completed education on every day in the year. The educational level which is applicable for the person on the first day if the quarter, represents the level in the entire quarter. For the average calculation of the primary labour market attachment for the year the level of education per September the 30. is applicable for the hole period. That is because it's the same reference time as is used for the status in the register of education and in RAS.

Adjustment

No corrections of data besides what is described under data validation and data compilation.