Accuracy and reliability
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Research, Technology and Culture, Business StatisticsMr. Ole Olsen
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Overall, the results are expected to be reliable. Figures for errors are not yet compiled. The main challenge on quality is the imputation for smaller enterprises, where costs/employee rations are used. This method has been assessed in 2015 and found valid.
In years without data collection the results are less secure. Analyses show close relation between turnover and environmental costs on the short run. For investments the results of the estimation is less good due to few observations behind the results.
Overall accuracy
There have not yet been compiled statistical errors. However, at well measurement errors and grossing up errors exists.
The quality on the results on current costs are considered good. The Investments are less accurate, as they are much more volatile. Further, for the cleaner investments it is difficult to measure the environmental compoment.
Sampling error
As an imputation model is used for the not-selected, there are in principle no sampling errors
Non-sampling error
The main source for error is related to measurement, as the identification of some elements is difficult, in particular the internal costs and the cleaner technology investments.
And other source for errors is the imputations for smaller enterprises as the assumptions behind may not be fully correct. An analysis of the assumption shows that smaller enterprises in fact are different, however, the difference is minor and does not require further correction.
In years without data collection the insecurity is higher than in the years with data collection.
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
The overall quality is expected to be satisfying. However, the investments in cleaner technology is very difficult to measure
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
Revisions will be implemented at next dissemination. Results for latest year are preliminary.