Accuracy and reliability
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Food Industries, Business StatisticsHenrik Bolding Pedersen
+45 20 57 88 87
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The sample covers all holdings in the target population with a Standard Output (SO) of at least EUR 25,000. Sampling uncertainty is reduced by selecting relatively more large holdings, where variability is greater, and relatively fewer small holdings. Potential sources of uncertainty include voluntary participation and differences in accounting periods, although both are considered to have only a limited impact on overall accuracy. Standard errors and coefficients of variation are calculated for four key variables across 22 groups of holdings. Expected non-response is taken into account by increasing the sampling rate in strata where higher non-response has been observed
Overall accuracy
The 2024 sample is designed to represent the target population of agricultural holdings with a Standard Output (SO) of at least EUR 25,000, as defined by the 2024 Farm Structure Survey.
Systematic errors A potential source of systematic error is the eligibility of holdings for selection. Participation is voluntary and, for agricultural holdings, requires that accounts cover a full calendar year. Holdings in the process of establishment or closure are therefore excluded. The effect of voluntary participation has not been formally assessed, while the restriction to calendar-year accounts is considered to have little impact because relatively few holdings use alternative accounting periods. Excluding holdings under establishment or liquidation may result in a slight overestimation of economic performance, since holdings undergoing compulsory liquidation cannot be included.
The reliability of the reported accounting data is considered high because most information is extracted directly from the annual accounts. Some supplementary variables rely on estimates made by the accountant or farmer, such as the annual labour input of the farmer and unpaid family labour.
Sampling error The statistics contain many variables and detailed breakdowns. Sampling uncertainty increases with the level of detail. For 2024, uncertainty has been calculated for key indicators such as operating result and return on assets for full-time holdings.
Sampling error
For 2024, sampling uncertainty for full-time holdings was estimated using the mean, standard error and coefficient of variation (CV) for operating result and return on assets:
Operating result Conventional agriculture: Mean DKK 1,570,000; Standard error DKK 92,000; CV 0.06. Organic agriculture: Mean DKK 759,000; Standard error DKK 102,000; CV 0.13. Horticulture: Mean DKK 651,000; Standard error DKK 79,000; CV 0.12.
Return on assets Conventional agriculture: Mean 4.6%; Standard error 0.1; CV 0.03. Organic agriculture: Mean 3.5%; Standard error 0.2; CV 0.05. Horticulture: Mean 4.8%; Standard error 0.5; CV 0.09.
Sampling uncertainty increases with the level of detail in the published tables.
Non-sampling error
Coverage errors may arise because participation is voluntary and eligible holdings must have a complete calendar-year accounting period. Non-response caused by selecting the sample before the reference year is mitigated by drawing a larger initial sample. Historical analyses show non-response rates of approximately 9–13 per cent for full-time holdings.
The reported accounting data are considered highly reliable because they are extracted directly from farm accounting systems. Administrative data, including information on agricultural subsidies, are used to supplement the accounts. Individual calibration weights based on economic size, type of farming and geographical region are applied to produce population estimates.
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
Coverage and sample survey
The sample survey covers about 10 pct. of the entire population within agriculture as a whole. If the sub-populations are considered, the selection ratio, however, varies considerably, partly to take account of the greater spread of results among the large farms, partly to achieve a sufficiently large number of farms in order to be able to represent the small sub-populations. In connection with the selection procedure, we have aimed at including the greatest possible number of farms in the statistics over several years in succession.
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
Preliminary results for the main groups are published when at least 50 per cent of the sample has been received and processed, normally in early July. Final results covering the full sample are published in October.
Figures for the most recent reference year remain provisional and may be revised following the additional validation carried out after transmission of the data to the FSDN.