Accuracy and reliability
Contact info
Labour and Income, Social Statistics.Torben Lundsvig
+45 3917 3421
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The statistics summarize the reports of birth or adoption that have triggered the payment of due to maternity leave. The expectation is that all cases are reported. However, there are a number of cases that will only be reported long after the end of the year to which the case relates, why the last year is not fully updated. In order to get a picture of a parent's year's use of the maternity law, it has been necessary to link several registers and set up an algorithm for calculating the parents' entitlement. There is a risk of programming errors here, just as the algorithm rules are a choice.
Overall accuracy
The statistics are based on records of cash disbursements. Administrative data involving the disbursement of money will usually be reliable and those parts of the data base must therefore be considered as very solid.
Regarding maternity leave, it should be noted that many men do not take maternity leave even if they could. A maternity leave of zero days does not trigger unemployment benefits and is not reported to the register, but from an equality point of view such zero maternity leaves should be included in the inventories. For those tables where zero childbirth overlaps are included, this is an algorithmic calculation based on other data sources. The rules of the algorithm will affect the results of the statistics. No calculations have been made on how much a change in the algorithm rules would affect, for example, the average number of days on maternity leave.
Furthermore, experience shows that the number of full-time persons in the register for the last year is about 1 percent too low the first time a year is published. Due to a clever definition of the statistical database tables, the published figures are hardly affected by the under-update.
Sampling error
Not relevant for these statistics.
Non-sampling error
A statistic that has an administrative data source is dependent on
-
The practice that has arisen in connection with the building of the administrative organization
and culture together with the attached IT system. -
The programs and the business logic the data supplier provides.
Examples of uncertainties related to 1).
- Reports come in very late compared to the time period the reports cover.
Examples of uncertainties related to 2).
- One year to date data delivery can be wrong initiated, so it still is not all reports that are delivered
to Statistics Denmark.
Such errors are counteracted by volume control over time.
Quality management
Statistics Denmark follows the recommendations on organisation and management of quality given in the Code of Practice for European Statistics (CoP) and the implementation guidelines given in the Quality Assurance Framework of the European Statistical System (QAF). A Working Group on Quality and a central quality assurance function have been established to continuously carry through control of products and processes.
Quality assurance
Statistics Denmark follows the principles in the Code of Practice for European Statistics (CoP) and uses the Quality Assurance Framework of the European Statistical System (QAF) for the implementation of the principles. This involves continuous decentralized and central control of products and processes based on documentation following international standards. The central quality assurance function reports to the Working Group on Quality. Reports include suggestions for improvement that are assessed, decided and subsequently implemented.
Quality assessment
As the Statistics can be compared with older statements from previous administrative systems, there is some control that the overall results look "correct". The quality of the statistics at the overall level must therefore be considered good
Data revision - policy
Statistics Denmark revises published figures in accordance with the Revision Policy for Statistics Denmark. The common procedures and principles of the Revision Policy are for some statistics supplemented by a specific revision practice.
Data revision practice
There are some delays in reporting absences on daily benefits due to childbirth. For this reason, the annual statistics are published in March-April, so that Statistics Denmark can include some of the delayed reports in the annual run. The latest year is recalculated one year after the first publication, after which the figures are considered final. In case of table changes, the tables are recalculated for all years. For the April 2023 publication, the two central IT programs have been quality checked, which has resulted in minor corrections. For the sake of clarity, all statistical bank tables have been recalculated for all years.