Industrial turnover index
Data on industrial turnover index are used to measure monthly development of market demand for industrial goods and services.
Concepts and definitions
Income from sale of goods and provision of services, from which trade discounts, as well as value added tax and other taxes directly related to sales are deducted.
Industrial Turnover Index
Data collection and statistical processing
Survey method and data source
Each month until the 25th date information on industrial turnover during the reference period at current prices according to the classes of NACE Rev. 2. is collected. Data are obtained with the help of enterprise survey, building a threshold sample. Data are collected from the CSB monthly statistical report form 1-r "Survey of industrial activity".
Industrial production turnover statistics is acquired by surveying economically active enterprises the main or secondary activity whereof covers industry (in line with the Sections B – Mining and Quarrying, C – Manufacturing, and D – Electricity, gas, steam and air conditioning supply, except for Group 35.3 – Steam and air conditioning supply, of the Statistical Classification of Economic Activities in the European Community (NACE Rev. 2)) and which a year before in industrial production employed 20 or more persons.
The sample additionally includes enterprises employing fewer than 20 people, to ensure that the data compiled on Divisions of NACE Rev. 2 (data at 2-digit level) cover at least 80 % of business structural statistics turnover in 2018.
The population of enterprises surveyed during the reference year may be revised by supplementing it with new economically active enterprises (in line with the mentioned criteria), specifying economic activities of the enterprises, upon receipt of revised information from respondents, as well as when the latest data are received from administrative sources.
In 2020 each months 1 456 enterprises are surveyed. In 2018, their share in mining and quarrying and manufacturing volume exceeded 80 %.
Industrial turnover index is nondeflated turnover index and calculation thereof includes Section B (Mining and quarrying) and Section C (Manufacturing). Weights are industrial turnover of 2015 in breakdown–domestic market and export.
2015 is base of comparison period (2015 = 100).
Data are collected and published according to Statistical Classification of Economic Activities in the European Community (NACE Rev. 2).
Data revisions are made, if respondent specifies, supplements or corrects data on some of the previous periods or if methodology is specified.
Calendar and seasonal adjustment
A time series is a sequence of observations collected at regular time intervals, for example, a monthly time series. It characterises indicator changes or development thereof. Seasonality and calendar effects are present in a large number of economic time series.
Seasonality or seasonal fluctuations of time series mean those movements, which recur with similar intensity in the same season each year. For example, each year Christmas shopping time can be observed in time series reflecting retail sales statistics. Change of seasons, social habits and influence of institutional factors are among the main causes of seasonality.
The calendar effects cover influence of calendar on time series. It is impact left by differing number of working days (or Mondays, Tuesdays and other days of the week) in months on changes of indicator. For example, number of working days differing among the months may affect goods produced time series.
When the time series are influenced by seasonality or calendar effects, it may be difficult to get clear understanding on indicator changes over the time. Seasonal adjustment is made to eliminate seasonal fluctuations and calendar effects in time series.
As a result seasonally adjusted time series, from which seasonality and calendar effects have been removed, are produced. It means that seasonally adjusted time series provide an estimate for what is “new” in the series, for example turning points in trends, business cycle or irregular component. Moreover seasonal adjustment results in calendar adjusted time series, in which calendar effects or varying number of working days in months has been eliminated. Specifics of seasonally adjusted statistics allows improving data comparability over time:
- Seasonally adjusted time series do not contain seasonal fluctuations and calendar effects, thus it is possible to compare, for example, data on the current month with the previous month's data.
- Calendar adjusted time series are not influenced by calendar effects and are used to compare, for example, statistics on current month with the data on corresponding month of the previous year.
The seasonal adjustment is made taking into account seasonal adjustment guidelines developed by the European Statistical System.
Contact person on methodology
Industrial and Construction Statistics Section