Accuracy and reliability

Overall accuracy

The statistic is based on data which covers the full population, and since the data in question are audited accounts, the overall accuracy is expected to be high. A high precision is also ensured through a series of quality processes during the compilation of the statistic. Newly created public companies of minor economic significance are in a few cases added with a one-year delay.

Accounting data entered wrongly are also a source of error, which is minimized by comparison with information from the previous year. If necessary, the company in question is contacted to validate the data. Automatic procedures check for errors in the data entry and general accounting errors, including the balance sheet, i.e. data is checked for inconsistency.

Sampling error

The statistic is a complete statistic based on accounting information from the total public sector. Thus there is no sample uncertainty.

Non-sampling error

The data material covers the entire population but newly created public companies of minor economic significance are in a few cases added with a one-year delay.

Accounting data entered wrongly are also a source of error, which is minimized by comparison with information from the previous year. If necessary, the company in question is contacted to validate the data. Automatic procedures check for errors in the data entry and general accounting errors, including the balance sheet, i.e. data is checked for inconsistency.

If the financial year for a public corporation is different from the calendar year; the calendar year with the longest accounting period is selected as the financial year.

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

This statistics is based on final account information from the government institutions and public corporations included in the statistic. As a general rule, all accounting information has been received by the time of publication and as such the quality of the statistic is estimated to be high. The primary sources of errors are:

• Errors in the account material - a company will occasionally send in corrections regarding previous accounting material. These are usually few and minor corrections have do not impact that published statistic.
• Errors in the national account-related classification of transactions - a potential source of errors that is minimised by validating data through a check of annual developments on company level as well as industrial classification level.
• Incomplete population - occasionally, a public company has not been classified as public at the time of its start-up and is thus not included in the statistic. This is usually companies with very little activity, however, and cause no significant impact on the figures.

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

The figures for the latest two years are provisional, as revisions to the prior two years of published data may occur during the collection of current accounting data from the public companies and general government, but the difference between provisional and final figures are small.