1. The computation of the first estimates
Mr. Mika Sirviö, Statistics Finland

2. Compilation of turnover indices
Releases of preliminary turnover indices with the delay less than 75 days
VAT data not yet available
The first releases are based on the sample only
Year-on-year change is estimated from the sample

3. The sample of turnover indices
The sample contains 2000 enterprises
Accounts for the majority of economic activity in Finland
Year-on-year changes calculated from the sample correlate with aggregate changes for all enterprises

4. Development of different size categories
However, the development varies between different enterprise size categories
Turnover has grown at a faster annual rate in small and medium sized manufacturing enterprises than in large enterprises, 5.0% vs. 2.7%
In construction sector the difference was even greater, 10.7% vs. 4.5%

5. Development (trend) of turnover in enterprises of different sizes in manufacturing industry

6. Revisions of the first estimates
Different development by size classes together with the slow accumulation of the data causes revisions in the indices of turnover
Other reasons for revisions:
changes in classification category (e.g. change of industry)
changes in value or source data
company reorganisations
enterprise openings and closures

7. Revisions of the year-on-year change of the first estimates by industry

8. Problems at the turning points of the economy
The problems become more crucial at the turning points of the economy
Growth and recession usually affect companies of different size at different points in time
The business cycle is reflected first in the large enterprises engaging in foreign trade
Small enterprises are less likely to survive from economic fluctuation
Or they tend to reach the growth path slower than large enterprises

9. Current imputation methods
Five different imputation rules are used for enterprises with missing data (t = month to be estimated):
Mean annual change
Geometric mean of monthly changes
Previous turnover
Mean Turnvoer
Turnover of comparison month

10. Current imputation methods
The rules are tested with data concerning the five latest months
The rule with the smallest largest prediction error is chosen as the best rule

11. Imputation and recession
Recession inflicts also on imputation of missing values, which is based on historical turnover values of enterprises
Imputation does not perform well for the enterprises with abnormal observations
In the current situation imputations and outlier treatment are controlled more carefully than normally

12. Goals
Improvement of the quality of data acquired from the direct data collection
Aim to take into account the influence of the companies left outside the inquiry methodologically
Use of regression models to estimate the rest of the population as a whole

13. Proposed methods for estimation
Robust regression models that utilize the information on the wages of the current month