Ville Koskinen Compilation methods of short term turnover and wage sum statistics Ville Koskinen

Ville Koskinen History Prior to 1999 a turnover index for trade was compiled from a stratified sample of approximately 3500 firms. Observation unit was commodity group. In 1999 the method was entirely revised. Currently: Observation unit is an enterprise or a kind-of-activity unit. The base data is the VAT data. Size of the sample has been reduced and all major industries are covered. Level estimation in has been replaced by estimation of year-on-year change from a panel of enterprises and kind- of-activity units.

Ville Koskinen History continued In an other major improvement in data collection: Internet-based data collection. The T+27 flash estimate for retail trade was introduced in Currently used only as a part of the European flash estimate but national publication is being planned. T+50 estimates for other services and construction were introduced this year Several improvements in index calculation, editing and imputation methods have been made during the last few years.

Ville Koskinen The change estimation method The indices are calculated by multiplying last year’s corresponding month’s index by the change in turnover/wage sum. Only the base year is formed by summing up. Firm X T-12 T Change Only comparable values are used! Firm ZFirm Y

Ville Koskinen The change estimation method continued The index formula is simply Effects of startups and closures are calculated by comparing “lost” (closure) or “new” (start-up) turnover and the total sum on the base years corresponding month. Closure effect Start-up effect Change of continuing businesses

Ville Koskinen General properties of the method The index number is recalculated until the VAT data is final. Because of nearly total data the revised index is almost free of error. This allows for liberties: Only estimation of change is necessary.  “Size matters” so stratification is not necessary and sample sizes required for the calculation of estimates are relatively small.

Ville Koskinen Discussion Because of the sheer size of the VAT data: statistical methods are less crucial … and computational methods more important E.g. efficient tools for checking are required. Challenges for the future: How to get most out of the data? Speeding up the publication of the indices is not feasible just by speeding up the data collection => Estimation and imputation methods are required Coherence of short term and structural statistics could be better

Ville Koskinen Questions?