Statistical processing

Source data

Absence data

The data for the governmental sector are collected by Moderniseringsstyrelsen (The Agency for the Modernisation of Publlic Administration) on a quarterly basis from the whole governmental sector. The information from the local government sector are collected in association with KRL; an actor in the local government sector. The data for the private sectors are collected as a sample of 2600 enterprises in collaboration with the employer unions, Danish Employers' Confederation, Finance Denmark and Insurance and Pension. The information are registered in the enterprises own earnings and absence systems or a spread sheet.

Earnings data

The absence periods are matched with the job from which the person has been absent. The data from the earnings statistics are used to create the jobs. For the governmental sector data are collected from the governmental earnings systems. Data are reported monthly for all individual employee. Earnings data for the local government sector are collected in association with KRL. The data for the private sectors are also collected in collaboration with the employer unions, Danish Employers' Confederation, Finance Denmark and Insurance and Pension. The information are registered in the enterprises own earnings systems.

Other

The register of People receiving public benefits is used to exclude persons in flexible jobs or light jobs. The register of benefits during sickness or in connection with childbirth is used to exclude chronically sick persons, to create the periods of maternity leave in the central government sector and to validate the periods of absence. .

Frequency of data collection

Data is collected on a yearly basis.

Data collection

The data for the governmental sector are collected by Moderniseringsstyrelsen (The Agency for the Modernisation of Publlic Administration) on a quarterly basis. The information from the local government sector are collected in association with KRL; an actor in the local government sector. The data for the private sectors are collected as a sample of 2600 enterprises in collaboration with the employer unions, Danish Employers' Confederation, Finance Denmark and Insurance and Pension. The information are registered in the enterprises own earnings and absence system or a spread sheet.

The sample of private enterprises has the following structure:

• All enterprises with 250 or more full-time employee must register information on absence.
• No enterprises with less than 10 full-time employee will be requested to register information on absence.
• For enterprises between 10 and 250 full-time employee the likelihood of being chosen to be in the sample depends on the size (measured in number of full-time employee) and industry.

Data validation

The submitted data undergoes an error control. In some cases enterprises are contacted in order to clear up questions to the data or to get data resubmitted. The validation causes that some data must be left out in cases where it is not possible to correct the errors.

Typical errors would be that the same absence period is reported twice or several times or that two or more periods overlap. It is especially the longer periods that have these problems. In these cases absence periods are left out so that no overlapping periods occur.

For the private sector a number of absence periods are not correctly reported. The starting date and the ending date of the absence period might be registered wrongly. The absence hours might be reported at one day regardless of how long the period has been. The absence hours might be reported summarized for a month, a quarter or a hole year. The enterprises do in some cases use systems to register absence data that are intended for other purposes than collecting absence data for Statistics Denmark. This causes data with systematic errors. The reported data are if possible corrected but in some cases data from entire enterprises have to be left out. The errors are corrected by for instance deleting the starting date or the ending date of the absence period by recalculating the date using the number of absence hours. In other cases the absence hours are deleted and recalculated according to the length of the period or in cases of errors caused by systems the absence hours are recalculated depending on the errors.

For most of the private enterprises, from an increasing part of the local government sector and from the central government sector where the period of absence is less than one whole day, we receive the actual number of hours of absence. For all other absence periods people are assumed to work 5 days a week. This is a necessary assumption in cases where we only receive registration of absence periods and not hours of absence.

To minimize the burden of registering we reuse the data form the earnings statistics to derive the number of working hours that a person could have been working had he not been absent. These hours of work are called possible hours of work. The possible hours of work are used when the absence rate is calculated. To be able to reuse the earnings data each absence period must be attached to its belonging job. The mach will not be possible if the person who has been absent does not exist in the earnings data or if the absence period does not lie within the duration of the job. Due to this some absence periods has to be excluded.

For the municipality sector the identification variables that are used to attach the absence periods to their belonging job are validated. This is especially necessary in case of changes of organization as for instance the reform of municipalities in 2007 and in cases of changes of systems to register absence data.

For the private enterprises it is evaluated whether each enterprise has reported absence for the entire enterprise and for all groups of employees. It is further more evaluated whether the number of jobs that are reported to the statistics of earnings correspond with the number of employees that are reported to the statistics of absence.

Data compilation

To minimize the burden of registering we reuse the data form the earnings statistics to derive the number of working hours that a person could have been working had he not been absent. These hours of work are called possible hours of work. The possible hours of work are used to calculate the absence rate and number of absence days per full-time employee. To be able to reuse the earnings data each absence period must be attached to its belonging job. The mach will not be possible if the person who has been absent does not exist in the earnings data or if the absence period does not lie within the duration of the job. Due to this some absence periods has to be dropped.

Holidays, special holidays and care are excluded from the possible days of work. Special holidays and care are reported directly to the statistics of absence. Holidays are calculated on the basis of the duration of the employment. This does not necessarily correspond to the actual vacation taken. The result is that the measures of absence are overestimated for persons who are new on the labour market or who does not take all the vacation that they are entitled to.

When the periods of absence are attached to the belonging job, hours of absence are calculated for the periods where the hours of absence are not reported. The hours of absence are calculated by using the start date and end date of the absence period and by assuming a five days week. The hours of absence are calculated on basis on the degree of employment from the Statistics of earnings.

The absence for the private enterprises is enumerated in two steps. In the first step is enumerated to the population of enterprises that report to the statistics of earnings. For this enumeration a number of background variables for the enterprises and their employees are used. The background variables are gender, region, education, occupation, industry and type of salary-earners which are all variables that have an influence on the level of absence. In the second step the absence is enumerated to the total population of private enterprises with 10 employees and more. The enumeration is based on information on number of full-time employees and industry from the Central Business Register.

Adjustment

No adjustments are made other than what is already described under 3.4 Data validation and 3.5 Data compilation.