Turnover index of accommodation and food service enterprises
Data on the turnover index of accommodation and food service enterprise are used in the estimation of development of services sector.
Services turnover is an income from the provision of services, excluding value added tax. Services turnover index characterizes development of the sector by quarters and months.
Concepts and definitions
Turnover index [services]
Turnover index an is indicator which shows turnover changes during a reference period, in comparison with base period. It is expressed as per cent.
Turnover index at current prices shows turnover changes in the corresponding period, when turnover was at prices of the period.
Turnover index against previous period (month or quarter) characterizes the turnover changes within the corresponding period (quarter). This indicator is essentially influenced by the factors of seasonal and calendar character. As a typical example enterprise turnover increase in the 2nd and 3rd quarter in air passenger transport, activity of hotels and camp-sites, services of travel agencies and tour operators can be mentioned here.
Turnover index against corresponding period of previous year shows the turnover changes within 12 months or 4 quarters. For example, turnover changes in the 4th of 2015 over the 4th quarter of 2014. 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 corresponding period 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 full-scope survey and data are collected from:
- CSB monthly questionnaires 2-turnover "Survey on Turnover";
- for data imputation information from Value Added Tax declaration from State Revenue Service are used.
Economically active enterprises and farms, which are economically active during the reference year and main sector of which, according to Statistical Classification of Economic Activities, Rev. 2, correspond to division 55 and 56 of section I "Accommodation and food service activities".
Services sectors exclude budgetary institutions (e.g., in health and education) and from 2015 excludes companies controlled and financed by public bodies. Survey population is regularly supplemented with new enterprises.
|Year||Number of surveyed enterprises|
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).