Data on turnover indices of service enterprises are used in the evaluation of service sector development.

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.

Definitions

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.

Service group includes the following sections:

  • wholesale and retail trade; repair of motor vehicles and motorcycles (NACE Rev. 2 section G);
  • wholesale, retail trade and repair of motor vehicles and motorcycles (NACE Rev. 2 division 45);
  • wholesale trade, except of motor vehicles and motorcycles (NACE Rev. 2 division 46);
  • transportation and storage (NACE Rev. 2 section H);
  • accommodation and food service activities (NACE Rev. 2 section I);
  • information and communication (NACE Rev. 2 section J);
  • real estate activities (NACE Rev. 2 section L);
  • professional, scientific and technical activities (NACE Rev. 2 section M);
  • administrative and support service activities (NACE Rev. 2 section N);
  • arts, entertainment and recreation (NACE Rev. 2 section R);
  • other service activities (repair, hairdressing salons, dry-cleaning) (NACE Rev. 2 section S without 94).

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 2010 shows changes of turnover of corresponding period compared to average monthly (quarterly) turnover of 2010. 

Data availability

Dissemination format and release calendar

Monthly and quarterly data are published at 60th day after the end of reference period. Trade and Servicesmonthly/quarterly data

Classifications

Data are collected and published according to Statistical Classification of Economic Activities (NACE Rev. 2).

A Classification Catalogue with classification codes and their explanations has been published on the CSB website.

Customised data sets

If you would like to obtain statistical data that are not available in publications or in the CSB online data base, please send us an information request:
 - postal mail: 1 Lāčplēša Street, Riga, Latvia, LV-1301;
 - e-mail: info [at] csb [dot] gov [dot] lv;
 - visiting Information centre.

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Additional information

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.

Data collection

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" and 4-turnover "Survey on Turnover" and CSB quarterly questionnaire 3-turnover "Survey on Turnover";
  • for data imputation information from Value Added Tax declaration from State Revenue Service are used.

Target population

Enterprises and peasant farms economically active in the reference year the main economic activity of which meets following Section, Division, and class of the Statistical Classification of the Economic Activities (NACE Rev.2), corresponds to 45 (wholesale and retail trade and repair of motor vehicles and motorcycles), 46 (wholesale), 95 (repair of computers and personal and household goods) 96 (other personal service activities), sections H (transportation and storage), J (information and communication), L (real estate activities), M (professional, scientific and technical activities), N (administrative and support service activities), P (education), Q (human health and social work activities), R (arts, entertainment and recreation).

Sample size

Enterprises for the survey are selected using the simple stratified random sampling.

Stratification is carried out according to two indicators characterizing enterprise: net turnover of the enterprise and main kind of activity of an enterprise: 45, 46.1, 46.2, 46.3, 46.4, 46.5, 46.6, 46.7, 46.9, 49.1, 49.2, 49.3, 49.4, 49.5, 50, 51, 52.1, 52.21+ 52.22+ 52.23, 52.24, 52.29, 53.1, 53.2, 55, 56, 58, 59, 60, 61, 62, 63, 68.1, 68.2+68.3, 69.1, 69.2, 70.1, 70.2, 71, 72, 73.1, 73.2, 74, 75, 77.2, 77, 78, 79, 80, 81.1+81.3, 81.2, , 82, 85.1+85.2+85.3+85.4, 85.5+85.6, 86, 87, 88, 90, 91, 92, 93.1, 93.2, 95.1, 95.2, 96.01+96.03+96.09, 96.02+96.4. Net turnover groups are determined different for every group of kind of activity defined.

The selection is developed as independent selection from other enterprise survey selections.
 

        

Year Sample size
2016 4 980
2015 4 868
2014 5 541
2013 5 489
2012 5 510
2011 5 550
2010 5 520

Statistical processing

Calculation methods

Data are extrapolated with mathematical methods and results on the country are obtained in general. Indices are calculated in the form of 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.

Software

JDemetra+

Seasonal adjustment method

TRAMO/SEATS

Last model revision

For data of the 1st quarter of 2017

Base period

For data of turnover indices of services enterprises base year is 2010.

Data revision

Data may be revised in the next publishing period. All reference year quarters may be revised, in case of essential changes data of previous years’ quarters are also changed. Main reasons for revision can be update of provisional data, update of the kind of activity of enterprises or methodological changes.

Comparability

Comparability over time

Quarterly data are comparable since 2000.
Monthly data are comparable since 2015.

International comparability

Eurostat

Information on turnover indices of service enterprises in EU-28 and in each country separately is available in the homepage of Statistical Office of the European Union (Eurostat) in section: Statistics/ Browse/Search database/ Industry, trade and services/ Short-term business statistics/ Trade and services..

http://epp.eurostat.ec.europa.eu

Confidentiality

Confidentiality of the information provided by respondents is protected by the Section 17 of the Statistics Law stipulating rights and obligations of the Central Statistical Bureau of Latvia and other state authorities producing official statistics. Read more

Contact person on methodology

Name

Surname Phone number Position Email
Ieva Vanaga

+371 67366738

Head of the Section

Ieva [dot] Vanaga [at] csb [dot] gov [dot] lv

Last update

30.05.2016

Turnover and turnover indices of retail trade and retail trade enterprises selling motor vehicles

Turnover index of accommodation and food service enterprises

Turnover indices of wholesale enterprises

Explanation of symbols

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Magnitude zero

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Less than half of the unit employed

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Data not available or too uncertain for presentation

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Figure not applicable because column heading and stub line make entry impossible, absurd or meaningless

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Data not released for confidentiality reasons

If data are absolute numbers

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Magnitude zero