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Working time accounts

How many hours do employees and self-employed people work in a quarter of a year? Which industries demonstrate the highest number of hours worked? The working time accounts calculate hours worked and can be distributed according to socio-economic status, industries, and other relevant factors.

Selected statistics on Working time accounts

This page shows selected popular statistics on the subject of Working time accounts. In Statbank Denmark, you can find more data and compile your own statistics.

Development in hours worked

Here you can see the quarterly development in hours worked in Danish-registered companies. Both employees and self-employed persons are included in the calculation.
More about the figure
Last update
15.3.2024
Next update
14.6.2024
Source data

The Danish Working time accounts (WTA) are based on a combination of census and survey data. The WTA are compiled on the basis of four primary data sources:

  1. Labour Market Accounts see Documentations of statistics LMA
  2. Structure of Earnings see Documentations of statistics SES
  3. A-Income Statistics see Documentations of statistics AINCOME
  4. Employment Statistics for Employees see Documentations of statistics BfL.

(1) With the Labour Market Accounts (LMA) monthly statements are available on employment, jobs, temporary absences and paid hours of work and for employees also compensation of employees throughout the calendar year for all the years covered by LMA data.

LMA form the basis of WTA on paid hours of work for self-employed and assisting spouses. In LMA these are calculated on the basis of hours paid for employees, but enumerated with how much more self-employed and assisting spouses are working according to labour force survey (LFS). Furthermore, WTA uses the latest developments in LMA to project jobs, employment and paid hours of work for self-employed and assisting spouses.

With LMA longitudinal data, it has become significantly easier to establish, whether leave has its origin in employment or unemployment. WTA uses information on leave from LMA covering all months of the year. Furthermore, continuing recent trends from LMA, WTA projects information on leave from employment (sickness and maternity) to months where no structural data exist.

Another huge quality improvement is that LMA can produce preliminary structural data for the reference year 2016 to be available already in August 2017.

(2) Structural Earning Statistics (SES) are used to convert paid hours of work from LMA to actual hours worked during the year in WTA.

Furthermore, data from the SES are used as help information to describe the distribution of hours worked over the months of the year in the WTA. Earning statistics are used for identifying jobs for workers paid by the hour, who are characterized by not being paid during absence. Therefore, the distribution of paid hours of work by hourly workers can represent the distribution of actual hours worked over the months of the year.

Furthermore, studies based on the labour force survey (LFS) shows that self-employed and assisting spouses do not have a significantly different distribution of hours worked over the year than employees. This information is in the WTA used for calculating the relative distribution of hours worked compared to hours paid for over the months of the year for all employed.

So although from eIncome (LMA and employment statistics for employees) only information on paid hours of work in the month are available, the WTA can thereby calculated how much this represents in hours worked per. month, based on the knowledge of how actual hours of work are distributed relative to paid hours of work over the months. Paid hours of work generally have a different distribution over the months of the year than actual hours worked due to the fact that absence is not evenly spread over the months of the year.

(3) Income statistics data (AINCOME) based on reports from the Danish Central Pension System (CPS) are used for adjusting compensation of employees in the WTA to include earnings of funded labour market pension.

(4) The Employment Statistics of Employees (BFL) contains monthly data on jobs, hours paid and compensation of employees throughout the year for employees. The information is used in the WTA to project compensation of employees, hours paid for, employment, primary and sideline (secondary, third etc.) jobs for employees during periods when there is no AMR data. Given that LMA include preliminary structural data, then the projection period is reduced so that the maximum length of projection is 15 months. The 15-month projection occurs in the calculation of the first quarter in June, while for example the calculation of second quarter figures in September will only be projected for six months. This increases the quality of the WTA statistics considerably.

In deciding which data sources to apply in compiling the WTA, attention is centred on the major advantages provided by each individual statistics. For example, LMA are used to ensure complete coverage in the calculation of employment, number of jobs, aggregate payroll costs and paid hours of work. This includes personal interviews used for obtaining information on groups that are not covered by the administrative registers. Information from the wage and salary system of the enterprises is used to convert paid hours of work into hours worked during the year.

The Working Time Accounts are exclusively based on existing data sources, which are subsequently converted to the concepts used in the WTA. The WTA is flexible in its choice of primary sources, which can be replaced by other sources, if these have proved to be more accurate. The choice of primary source decides the amount of data editing necessary. When it comes to integrating all the sources, however, all the concepts are consistent in conforming to international standards and every variable fulfils the requirement of the system for the WTA.

Data in WTA are summarized (aggregated) prior to integration and projected so that the output data alone are broken down by socioeconomic status (whether you are an employee, self-employed or assisting spouse), industries, sectors, gender and amount of work.

Hours worked by industry

Here you can see hours worked broken down by industry. Both employees and self-employed persons are included in the calculation.
More about the figure
Last update
15.3.2024
Next update
14.6.2024
Source data

The Danish Working time accounts (WTA) are based on a combination of census and survey data. The WTA are compiled on the basis of four primary data sources:

  1. Labour Market Accounts see Documentations of statistics LMA
  2. Structure of Earnings see Documentations of statistics SES
  3. A-Income Statistics see Documentations of statistics AINCOME
  4. Employment Statistics for Employees see Documentations of statistics BfL.

(1) With the Labour Market Accounts (LMA) monthly statements are available on employment, jobs, temporary absences and paid hours of work and for employees also compensation of employees throughout the calendar year for all the years covered by LMA data.

LMA form the basis of WTA on paid hours of work for self-employed and assisting spouses. In LMA these are calculated on the basis of hours paid for employees, but enumerated with how much more self-employed and assisting spouses are working according to labour force survey (LFS). Furthermore, WTA uses the latest developments in LMA to project jobs, employment and paid hours of work for self-employed and assisting spouses.

With LMA longitudinal data, it has become significantly easier to establish, whether leave has its origin in employment or unemployment. WTA uses information on leave from LMA covering all months of the year. Furthermore, continuing recent trends from LMA, WTA projects information on leave from employment (sickness and maternity) to months where no structural data exist.

Another huge quality improvement is that LMA can produce preliminary structural data for the reference year 2016 to be available already in August 2017.

(2) Structural Earning Statistics (SES) are used to convert paid hours of work from LMA to actual hours worked during the year in WTA.

Furthermore, data from the SES are used as help information to describe the distribution of hours worked over the months of the year in the WTA. Earning statistics are used for identifying jobs for workers paid by the hour, who are characterized by not being paid during absence. Therefore, the distribution of paid hours of work by hourly workers can represent the distribution of actual hours worked over the months of the year.

Furthermore, studies based on the labour force survey (LFS) shows that self-employed and assisting spouses do not have a significantly different distribution of hours worked over the year than employees. This information is in the WTA used for calculating the relative distribution of hours worked compared to hours paid for over the months of the year for all employed.

So although from eIncome (LMA and employment statistics for employees) only information on paid hours of work in the month are available, the WTA can thereby calculated how much this represents in hours worked per. month, based on the knowledge of how actual hours of work are distributed relative to paid hours of work over the months. Paid hours of work generally have a different distribution over the months of the year than actual hours worked due to the fact that absence is not evenly spread over the months of the year.

(3) Income statistics data (AINCOME) based on reports from the Danish Central Pension System (CPS) are used for adjusting compensation of employees in the WTA to include earnings of funded labour market pension.

(4) The Employment Statistics of Employees (BFL) contains monthly data on jobs, hours paid and compensation of employees throughout the year for employees. The information is used in the WTA to project compensation of employees, hours paid for, employment, primary and sideline (secondary, third etc.) jobs for employees during periods when there is no AMR data. Given that LMA include preliminary structural data, then the projection period is reduced so that the maximum length of projection is 15 months. The 15-month projection occurs in the calculation of the first quarter in June, while for example the calculation of second quarter figures in September will only be projected for six months. This increases the quality of the WTA statistics considerably.

In deciding which data sources to apply in compiling the WTA, attention is centred on the major advantages provided by each individual statistics. For example, LMA are used to ensure complete coverage in the calculation of employment, number of jobs, aggregate payroll costs and paid hours of work. This includes personal interviews used for obtaining information on groups that are not covered by the administrative registers. Information from the wage and salary system of the enterprises is used to convert paid hours of work into hours worked during the year.

The Working Time Accounts are exclusively based on existing data sources, which are subsequently converted to the concepts used in the WTA. The WTA is flexible in its choice of primary sources, which can be replaced by other sources, if these have proved to be more accurate. The choice of primary source decides the amount of data editing necessary. When it comes to integrating all the sources, however, all the concepts are consistent in conforming to international standards and every variable fulfils the requirement of the system for the WTA.

Data in WTA are summarized (aggregated) prior to integration and projected so that the output data alone are broken down by socioeconomic status (whether you are an employee, self-employed or assisting spouse), industries, sectors, gender and amount of work.

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Productivity
Here you can see figures for productivity, which is a measure of how much you get out of the hours worked when producing goods and services.
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Complete national accounts
See the complete national accounts, which use the earnings and employment data from the working time accounts.

On the statistics – documentation, sources and method

Gain an overview of the purpose, contents and quality of the statistics. Learn about the data sources of the statistics, the contents of the statistics and how often they are published.

See the documentation of statistics to learn more:

Working time accounts

The purpose of the Danish working time accounts (WTA) is to compile time series on hours worked and calculate wage and employment data for companies registered in Denmark. The statistics integrate and aggregate existing statistics, including the Labor Market Accounts (LMA) and Employees, and it is comparable since 2008.

Need more data on Working time accounts?

You can go on searching on your own in Statbank Denmark. Find more detailed figures, e.g. on hours worked, earnings and employment broken down by sector, industry and socio-economic status.