Data on consumption of energy resources in households are used to find out information on the amount of fuel, electricity and heat consumed in households, costs thereof as well as motor vehicles and electrical devices used in households.


Housing in a multi-dwelling building.

Centralized heat production in certain territory, where heat energy is supplied to consumers trough main and/or distribution heat supply networks or without them.

Furnaces burning the fuel effectively and economically, and in which innovative burning technologies with increased heat exchange are used.

Appliance for the acquisition of the heat energy trough the pipe placed in the borehole, soil, or water tank, in which non-freezing liquid is circulating. Heat pump transforms the acquired energy in order to use it for the heating and preparation of hot water.

In dwellings having centralised heating (collective and district heating) the total heated floor space (m2) is equal to the total floor space of premises (this information is available in the Land Register certificate rental agreement of the household).

Usually the calculations of heating costs are based on this floor space.

In the households where inhabitants purchased and used fuel by themselves only the space actually heated was included, i.e., living premises and various auxiliary premises.

In selected household the heating system (dwelling, individual house) may be centralized or non-centralized.

  • Centralized heating appliances (central heating boilers, combined or two-functional central heating and hot water boilers) heating whole dwelling.
  • Non-centralised heating appliances (furnaces, ovens, electric heaters etc.) are used to heat separate premises in the dwelling.

Private car stock of the households (cars and motorcycles) is surveyed regardless the vehicles are privately owned or temporary used.

Several persons living in one dwelling and sharing expenditures or one person having separate housekeeping.

A private house for one or several families.

  • Water supply of the dwelling is centralised and the household pays for hot water consumption according to readings of hot water meters or according to the number of residents registered within the dwelling;
  • Household supplies hot water using combined heating and hot water boilers;
  • Household supplies hot water using hot water boilers.

In the last two cases households purchase fuel by themselves.

Data availability

Dissemination format and Release calendar

Theme Reference period Actual release datesort icon Remarks
Energy Consumption in Households
  • 2015
Energy Consumption in Households
  • 2010

Survey is conducted approximately once in five years.

Energy Consumption in Householdssurvey 1996, 2001, 2006, 2010, 2015

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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Data collection

Survey method and data source

Data on consumption of energy resources in households are acquired with the help of sample survey and household participation in the survey is voluntary. Data sources used were following:

  • In 1996, 2001 and 2006 "Survey on consumption of energy resources in household";
  • In 2010 and 2015 statistical report form EPM-1 "Survey on consumption of energy resources in household".

Target population

The basic unit of the survey is private household. The survey does not include collective households (homes for the elderly, homes for disabled children, students` hostels, hotels, soldiers` barracks, hospitals, sanatoriums, places of liberty deprivation, etc.).

The sample for the survey was formed as two-stage stratified random sampling. First stage includes primary sample unit that is formed by the population census districts. In the second stage housings are selected.

Sample size

In order to form the sample, the Dwelling Register was used.

Sample size in 1996 was 4400 households, in 2001 – 8000 households, and in 2006 – 7061 household, in 2010 – 10986 households, in 2015 – 11043 households.

For 2015 the sample breakdown by different household groups (strata) was the following:

  • in Riga – 3295 households;
  • in 8 cities under State jurisdiction – 2316 households;
  • in other towns – 1848 households;
  • in rural areas – 3612 households.

Statistical processing

Calculation methods

For the estimates the final weights are used. The final weights are calculated basing on the probable inclusion of the sampling unit in the sample. The sample is formed as two-stage stratified random sample. In the first stage the primary sampling units (PSU) are selected. In the second stage the sampling units are selected from the PSU with the help of random sampling. And as a result of that the design weights are acquired. The design weights are value inverse to the sampling unit inclusion in the sample. Afterwards the obtained design weights are adjusted in accordance with the non-response rate, and finally the weights are calibrated according to the external information (number of natural gas users and cubic meters consumed). After the calibration the final weights are obtained, that are used for estimates.

Data revision

The published data are final and are not revised.


Comparability over time

Data on consumption of energy resources in households are comparable with the results of 1996, 2001, 2006 and 2010.


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
Līga Meļko 67366863 daļas vadītājs

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Explanation of symbols


Magnitude zero


Less than half of the unit employed


Data not available or too uncertain for presentation


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


Data not released for confidentiality reasons

If data are absolute numbers


Magnitude zero