1. Business Sampling 25th April 2012 Peter Linde Survey and Methods Statistics Denmark

2. Methods Methods: Support whole Statistics Denmark A part of business statistics, where most work are Steering committee – four Directors 6 persons working med sampling, SA, imputation, … Optimizing the 30 business surveys one of the tasks … inspection every 3-4 year … when new sources … increasing sampling error

3. Business register Business register is the frame for all business Statistics It is updated by business, Statistics Denmark and official authorities Statistics Denmark is e.g. responsible for sector code When at statistics discover a problem it contact the unit working with Business register Business in general has a low interest in sector code, but sometimes at interest not to be a concrete sector because of the price for insurance A business can cover several sectors – is this updated? Then Business register is updated with active business. The under or over cover is very small – that’s is enough to make statistics Problems with sector must be solve in the estimation Metadata about change over time

4. Sampling and estimation business surveys Principles for optimizing samples Least possible mean error 99% participation - mandatory No bias – simple random sampling inside strata a)Panels must not give bias b)Two steps when calibrating weights 1)Against the selection population 2)Against the known population when published Burden for small companies Medium size companies participate at most 3/5 years Adjust for cut off

5. Two steps when calibrating weights Step one: The known population when sample is selected If e.g. sector is not correct information is sent to business register All other surveys also send back if something is wrong In addition, companies and other offices can update the business register Step two: When the statistics is published a locked version is used for all statistics with the accepted updates Adjust for cut-off by ancillary information

6. Panels must not give bias (1) Panels are used to optimize estimation of changes and to reduce sampling costs If a company is changing to a smaller size strata - with a smaller selection probability - a proportional numbers of these companies are given free –and opposite when companies grow Else an underestimation will arise when the economy grows - and opposite an overestimation when the economy is decreasing