Volume indices of industrial production
Volume indices of industrial production characterize changes in the volume of industrial production during the reference period in comparison with the base period.
Concepts and definitions
Volume index of industrial production
Main industrial grouping
Main industrial groupings are formed as an industrial sector Section (B, C, D) intermediate, by regrouping the 3-digit groups in compliance with the Statistical Classification of Economic Activities (NACE Rev. 2).
There are 5 basic production groups:
- intermediate goods;
- capital goods;
- durable consumer goods;
- non-durable consumer goods.
Data collection and statistical processing
Survey method and data source
Each month until the 25th date information on industrial production during the reference period at current prices is collected, according to the classes of Statistical Classification of Economic Activities (NACE Rev. 2). Data on volume indices of industrial production 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 output (volume) 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, the number of enterprises surveyed monthly comprised 1 456. In 2018, their share in the total volume of industrial production exceeded 80 %.
Calculation of Industrial Production Index (henceforth – IPI) is based on the chain index method; within the framework of it the average monthly volume of production manufactured (at constant prices) previous year is used as a calculation basis and the value added of enterprises manufactured two years ago by NACE sections, chapters, groups and classes is used as weights. IPI is calculated by recalculating production output indicator at constant prices with the help of producer price indices. Weights are changed every year, thus changes in the structure of industry are taken into account.
2015 is base or reference period (2015 = 100).
Data are collected and published in compliance with:
- Statistical Classification of Economic Activities (NACE Rev. 2);
- Main industrial grouping (MIG 2009).
Data revisions are carried out, if a respondent updates, supplements or corrects data on any of the previous periods, or if the methodology changes.
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