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Accuracy and reliability

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Food Industries, Business Statistics
Mona Larsen
+45 24 81 68 47

MLA@dst.dk

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Pigs

The greatest factor of inaccuracy is updating and matching of the different registers. The relative standard deviation - sampling errors - for pigs is 0.5 per cent to 1.5 per cent. A maximum of 5 per cent has to be observed to meet EU's requirements. As part of a quality assessment statistical errors are calculated for all variables.

Overall accuracy

The population includes all active farms in Denmark and is integrated in the Statistical Business Register (ESR), which is kept by Statistics Denmark, and which is registered with pigs in the Central Livestock Register (CHR). In order to ensure that the population is up to data Statistics Denmark regularly makes register merges with IACS and every quarter with the Central Livestock Register (CHR). The assumption is that if a farm applies for single payment or reports livestock to the livestock register it must be expected to be active in agriculture and should accordingly be marked as such in the register of Statistics Denmark.

Sampling error

The standard deviation - sampling errors - for pigs is 0.5 per cent to 1.5 per cent. A maximum of 5 per cent has to be observed to meet EU's requirements. As part of a quality assessment statistical errors are calculated for all variables.

When the holdings are selected, they are divided into 22 strata according to the type of pigs and total number of pigs at the holding. The number of pigs is information from the last survey in which the holding has participated. If a holding with sows has 5,000 pigs or more, it will always be in the pig survey. If a holding with weaners under 50 kilo and pigs for slaughtering has 10,000 pigs or more, it will always be in the pig survey. All the other holdings are selected randomly for the first time, and then the holding will be included in the sample at a maximum of 8 times. The selection method is optimum, i.e. the strata of the total sample are divided so that the variance of the estimated total number of pigs is minimized.

Non-sampling error

At the survey on 01 October 2026, the response rate was 96.0 percent - i.e. a non-response rate of 4.4 percent for the farms and 3,7 percent for the pigs. At the survey on 01 July 2026, the response rate was 96.7 percent - i.e. a non-response rate of 3.3 percent for the farms and 1.8 percent for the pigs. At the survey on 01 April 2026, the response rate was 98.2 percent - i.e. a non-response rate of 1.8 percent for the farms and 2.3 percent for the pigs. At the survey on 01 January 2026, the response rate was 98.0 percent - i.e. a non-response rate of 2.0 percent for the farms and 2.1 percent for the pigs.

From the census of April 1, 2018 a new stratification of the pig population has been applied. However, this has minimal significance for comparability, a difference of less than 1 per cent has been found. on this calculation method and earlier.

The farmer has to count the pigs at the first day in the quarter.

The are a little more uncertainty about when a female pig over 50 kilo is count as a female pigs for breeding or as a pig for slaughtering.

An other source to mistake, can be that the farmer "forgot" to include pigs from all his farms, especially from renting farms.

The split of pigs below and respectively a live weight of 50 kg can be a little uncertain as in the farm the pigs is normally spilt a live weight of 30 kg.

Quality management

Statistics Denmark follows the recommendations on the organisation and management of quality set out in the Code of Practice for European Statistics and the accompanying implementation model, the Quality Assurance Framework. Read more about these on the page Quality in official statistics.

Quality management is supported by common principles, guidelines and managerial responsibility for quality in statistical products and processes. The aim is to ensure a systematic and consistent approach to quality across the entire statistical production.

Quality assurance

Quality assurance at Statistics Denmark is integrated into the statistical production processes and is carried out in accordance with the principles of the Code of Practice for European Statistics. Read more on the page Quality in official statistics.

Quality assurance includes the continuous use of standardised procedures, documentation in line with international standards and internal controls related to data collection, data processing and dissemination. Experience gained from production is continuously used to identify needs for adjustments and improvements.

Quality assessment

The information is reliable and provides a good basis for preparing forecasts.

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

Only final figures are published.