Turnover and turnover indices of retail trade
Data on turnover and turnover indices of retail trade are used in the evaluation of development of sectors.
Concepts and definitions
Retail trade is the resale of new and used goods (sale without transformation) mainly to general public for individual or household consumption or utilisation performed at stores, kiosks, trading places, markets, stands etc., as well as retail trade by enterprises taking mail-orders, street vendors and peddlers, consumer co-operatives, auction houses, etc.
According to Statistical Classification of Economic Activities (NACE Rev. 1.1) retail trade does not include retail trade of automotive fuel in gas filling stations, but according to NACE Rev. 2 – includes.
Retail trade enterprise is company main economic activity of which is retail trade.
Turnover [trade and services]
Turnover is income from sale of goods and provision of services, from which trade discounts are subtracted, as well as value added tax (VAT) and other taxes, which are directly related with sale.
Turnover index (types)
Turnover index is an indicator which shows turnover changes during a reference period, in comparison with base period. It is expressed as per cent.
Turnover index in current and constant prices shows the turnover changes in relevant period, when the turnover is at prices of the relevant period. This indicator shows changes, when the turnover of each period is taken in prices of reference period.
Turnover index at constant prices shows the turnover changes in relevant period, when the turnover is recalculated in the prices of base period. As basic prices average prices of 2010 are used. Consumer price index for the relevant commodity or service group is used as deflator. This indicator shows turnover changes, if the prices stayed remained stable in reference time period.
Turnover index against previous period (month/quarter) characterizes the turnover changes within the corresponding period (month/ quarter). This indicator is essentially influenced by the factors of seasonal and calendar character. As very characteristic example the rapid increase of retail sale turnover in December can be mentioned, which is related to Christmas and New Year celebrations.
Turnover index against corresponding period of previous year shows the turnover changes within 12 months or 4 quarters. For example, turnover changes of January 2016 against January 2015 show the turnover changes in January 2016 in comparison with corresponding period a year before. This indicator is used for the calculation of Gross Domestic Product in macroeconomic analysis.
Turnover index over average monthly (quarterly) turnover of 2015 shows changes of turnover of relevant period (monthly/quarterly) compared to average (monthly/quarterly) turnover of 2015.
Index is a numeral indicator, which indicates consecutive changes of some social or economic phenomenon as percent.
It is comparison indicator of one phenomenon in two stages.
Data collection and statistical processing
Survey method and data source
Data are obtained conducting a sample size survey. Information is collected from:
- CSB statistical report form 1-turnover "Survey on turnover";
- For data imputation information from Value Added Tax declaration collected from State Revenue Service are used.
Target population is all economically active enterprises main activity of which is retail trade (NACE Rev. 2. division 47 "Retail trade, except of motor vehicles and motorcycles").
Enterprises for the survey are selected using the simple stratified random sampling.
Enterprises are stratified by the kind of activity according to Statistical Classification of Economic Activities in the European Community (NACE Rev. 2) and turnover. The larger the enterprise’s turnover, the larger the possibility for the enterprise to be included into the sample.
The selection is developed as independent selection from other enterprise survey selections.
|Year||Number of sampled enterprises|
Data with mathematic methods are extrapolated and results acquired characterise whole country. Turnover indicators of selected sectors with consumer price index are recalculated at current prices (average prices of 2010). Afterwards turnover index is calculated. Indices are calculated as non-adjusted, seasonally adjusted and calendar adjusted data.
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.
Data are revised due to provisional information update, update of kind of activity of enterprise, seasonal adjustment and methodological changes. Revision is carried out in the next publishing period. Non-adjusted data are revised for previous two months, but seasonally and calendar adjusted data – in all previously published data row.
Data are collected and published in compliance with Statistical Classification of Economic Activities in the European Community (NACE Rev. 2).