Statistical processing

Source data

Municipalities report data on individually attributable expenditure to Statistics Denmark. Data are submitted either through system-to-system transfers from municipalities' administrative financial management systems or via the web-based reporting solution, IDEP, which is accessed through Virk.dk. Through IDEP, municipalities can access all data they have reported. Most municipalities submit their data via IDEP.

When municipalities collect and report data through IDEP, this is primarily done in one of the following ways, or through a combination of these methods. The method used depends on the municipality's accounting practices and the availability of data:

1. Expenditure and the expenditure period are extracted from the municipality's financial management system.
2. Expenditure and the expenditure period are extracted from the municipality's case management system.
3. Expenditure and the expenditure period are compiled and processed in a municipality-specific spreadsheet before being reported.

The data reported by municipalities are reconciled with the municipal accounting data from the Municipal Accounts and Budgets statistics.

Frequency of data collection

Data are collected annually from Denmark's 98 municipalities.

Data collection

Data are primarily reported through Statistics Denmark's web-based reporting solution, IDEP, which can be accessed via the statistics reporting page: statistikkens oplysningsside or through Virk.dk. Alternatively, municipalities submit data directly from their administrative financial management systems through system-to-system reporting.

All submissions are consolidated in IDEP, where municipalities have access to their own reported data.

Data validation

The data are validated annually in cooperation with the municipalities. As part of the validation process, an aggregated validation report is made available to each municipality. The report is generated from the reported data and presents the number of recipients together with the corresponding expenditure, broken down by type of social service. Each municipality reviews and approves its own report. To support the validation process, municipality-specific lists at the individual and social service level are also provided. Together with a set of automatically generated validation queries, these lists enable municipalities to verify that the reported information is consistent with their own records and accounting data, and to identify and correct any errors in the underlying data. The lists identify observations requiring further validation and forming the basis of the automatically generated validation queries. These include, among other things, unusually high or low expenditure, missing information, and overlapping expenditure periods across social services.

As part of the validation process, the reported data are reconciled with the municipal accounting data reported for the Municipal Accounts and Budgets statistics. Total expenditure is compared with net expenditure in the StatBank table: REGK100 broken down by type of social service. Municipalities where the difference between the reported expenditure and the accounting data exceeds 5 per cent or DKK 1 million are included in the detailed validation process. In many cases, this comparison results in corrections to the reported data. In other cases, municipalities are able to explain the differences between the statistics and the accounting data.

Municipalities can access the validation reports, detailed lists and automatically generated validation queries through the web-based reporting solution, IDEP. If a municipality considers that the lists do not accurately reflect its data, a dialogue is initiated between the municipality and Statistics Denmark to clarify and resolve the identified discrepancies. The process continues until the data have been reconciled and approved by both the municipality and Statistics Denmark.

As a general rule, only approved data are included in the published statistics. If a municipality is unable to approve its data before publication, Statistics Denmark and the municipality continue their collaboration after publication to ensure that the data are reconciled before the next annual release.

The validation process focuses in particular on ensuring that municipalities have reported the mandatory accounting codes in accordance with the requirements set out in the Executive Order on Data Reporting.

Data compilation

As a general rule, Statistics Denmark does not apply weighting, grossing-up or other statistical adjustments to compensate for missing data.

Validated data reported either through municipalities' financial management systems or through Statistics Denmark's web-based reporting solution (IDEP) are integrated into the statistical register. Regardless of the reporting method, all submissions must comply with the requirements of the Executive Order on Data Reporting. This ensures a consistent data basis and enables the integration of data across reporting methods.

Before the Micro-data are compiled, the reported data undergo a series of standardised processing steps. First, empty records and duplicate records are removed. Observations with accounting code combinations that are not covered by the mandatory reporting requirements set out in the Executive Order on Data Reporting are then excluded. For the remaining observations, only the mandatory elements of the accounting code combination are retained, while all other elements are replaced by "x". Finally, the data are restricted to records with an expenditure period within the reference year, meaning that records with start and end dates before the reference year are excluded from the Micro-data.

Individuals are identified during data processing based on CPR number or, where a CPR number is not available, an alternative personal identification number. Alternative personal identification numbers are used, among other cases, for individuals without a CPR number, such as certain foreign nationals, and for anonymous stays under Section 109 of the Danish Social Services Act. In some cases, the same alternative personal identification number may be used for more than one individual. This may result in an underestimation of the number of individuals in the Micro-data and should therefore be taken into account when conducting analyses based on these data. The personal identification is subsequently pseudonymised, whereby CPR numbers and alternative personal identification numbers are replaced by a unique person ID for further data processing and in subsequent datasets.

A number of variables are derived for use in further data processing.

Age is calculated based on the date of birth derived from the CPR number and the relevant reference date at year-end.

Sex is derived from the last digit of the CPR number. If a CPR number is not available, sex may in certain cases be derived from the alternative personal identification number.

Duration is calculated as the number of unique calendar days in the period between the start and end dates.

The individual unit expenditure is calculated based on reported expenditure and duration as the average daily expenditure multiplied by 365.25, according to the formula (expenditure / duration) * 365.25. The factor 365.25 corresponds to the average number of calendar days per year and ensures that leap years are taken into account in the calculation.

Taking the described data processing into account, the Micro-data are made available in two registers:

Kommunale udgifter til social indsatser - total (Individ_udgifter_total), data reflects differences in municipalities’ reporting practices, where some municipalities report one total expenditure amount per citizen and service for the year, while others report expenditure per citizen and service distributed by month and number of days. The data are restricted to expenditure periods within the reference year, and expenditure periods outside the reference year are therefore excluded.

Kommunale udgifter til social indsatser - sum (Individ_udgifter_sum), calculates duration at the individual, municipal and service levels. If a citizen has multiple periods for the same service, the periods are checked for any overlap. Overlapping periods are merged so that the same calendar day is counted only once. Expenditure is aggregated at the same level, after which the unit expenditure is calculated based on the total expenditure and the total unique duration. Duration is calculated by counting unique days in the reference year, and expenditure periods outside the reference year are therefore excluded.

The StatBank tables SIU001 and SIU002 are based on the following Micro-data: Individ_udgifter_total

In the StatBank tables, unit expenditure is calculated at the individual level within each StatBank cell. For each individual, all expenditure amounts within the relevant cell are summed, while duration is calculated as the number of unique calendar days with observations in the cell. Where expenditure periods overlap, each calendar day is counted only once when calculating duration, while all expenditure amounts are included. On this basis, the mean, median and quartiles are calculated across the individual unit expenditures within each cell.

For reasons of data confidentiality, the tables are subject to statistical disclosure control prior to publication. Disclosure control is carried out using Tau-Argus and includes both primary disclosure control of cells that are sensitive in themselves and secondary disclosure control of cells that could either be used for indirect identification or to recalculate suppressed values. The median and quartiles are calculated as the average of three observations to avoid disclosing individual observations.

In 2025, the statistics cover only sections of the Danish Social Services Act relating to adults. Citizens under the age of 18 are therefore outside the scope of the statistics and are not included in the data underlying the StatBank tables. In addition, observations with an unknown person ID are excluded from the data underlying the tables. Finally, municipalities with negative quartiles for services are excluded from the StatBank tables. All figures are rounded to 0 decimal places.

Adjustment

No corrections are made besides those corrections described in the chapters on data validation and data processing.