Electricity prices for household consumers - bi-annual data (from 2007 onwards) (nrg_pc_204)

National Reference Metadata in Single Integrated Metadata Structure (SIMS)

Compiling agency: Statistics Sweden


Eurostat metadata
Reference metadata
1. Contact
2. Metadata update
3. Statistical presentation
4. Unit of measure
5. Reference Period
6. Institutional Mandate
7. Confidentiality
8. Release policy
9. Frequency of dissemination
10. Accessibility and clarity
11. Quality management
12. Relevance
13. Accuracy
14. Timeliness and punctuality
15. Coherence and comparability
16. Cost and Burden
17. Data revision
18. Statistical processing
19. Comment
Related Metadata
Annexes (including footnotes)
 



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1. Contact Top
1.1. Contact organisation

Statistics Sweden

1.2. Contact organisation unit

Agriculture and Energy Unit

1.5. Contact mail address


2. Metadata update Top
2.1. Metadata last certified 13/07/2022
2.2. Metadata last posted 15/06/2022
2.3. Metadata last update 15/06/2022


3. Statistical presentation Top
3.1. Data description

European statistics on electricity prices for household and final non-household customers.

3.2. Classification system

Internal Eurostat classification system based on annual electricity consumption bands and tax levels.

3.3. Coverage - sector

Household sector and final non-household sector (industry, services, offices, agriculture, etc).

3.4. Statistical concepts and definitions

The prices are reported in national currencies per kWh and according to different bands of consumption.

For the household sector, these bands are:

  • DA: customers consuming less than 1000 kWh.
  • DB: customers consuming 1000 kWh or more but less than 2500 kWh.
  • DC: customers consuming 2500 kWh or more but less than 5000 kWh.
  • DD: customers consuming 5000 kWh or more but less than 15000 kWh.
  • DE: customers consuming 15000 kWh or more.

For the final non-household sector, the bands are:

  • IA: customers consuming less than 20 MWh.
  • IB: customers consuming 20 MWh or more but less than 500 MWh.
  • IC: customers consuming 500 MWh or more but less than 2000 MWh.
  • ID: customers consuming 2000 MWh or more but less than 20000 MWh.
  • IE: customers consuming 20000 MWh or more but less than 70000 MWh.
  • IF: customers consuming 70000 MWh or more but less than 150000 MWh.
  • IG: customers consuming 150000 MWh or more.

There exist 2 different levels of disagregation for semestrial and annual prices:

1- Semestrial prices:

These prices are reported twice a year and are divided in 3 levels:

  • Level 1 prices: prices excluding taxes and levies.
  • Level 2 prices: prices excluding VAT and other recoverable taxes and levies.
  • Level 3 prices: prices including all taxes and levies.

2- Annual prices:

These prices are reported once a year together with the data for the second semester and are divided into the following components and taxes:

  • Energy and supply: generation, aggregation, balancing energy, supplied energy costs, customer services, after-sales management and other supply costs.
  • Network cost: transmission and distribution tariffs, transmission and distribution losses, network costs, after-sale service costs, system service costs, and meter rental and metering costs.
  • Value added taxes (VAT): as defined in Council Directive 2006/112/EC.
  • Renewable taxes: taxes, fees, levies or charges relating to the promotion of renewable energy sources, energy efficiency and CHP generation.
  • Capacity taxes: Taxes, fees, levies or charges relating to capacity payments, energy security and generation adequacy; taxes on coal industry restructuring; taxes on electricity distribution; stranded costs and levies on financing energy regulatory authorities or market and system operators.
  • Environmental taxes: taxes, fees, levies or charges relating to air quality and for other environmental purposes; taxes on emissions of CO2 or other greenhouse gases. This component includes the excise duties.
  • Nuclear taxes: taxes, fees, levies or charges relating to the nuclear sector, including nuclear decommissioning, inspections and fees for nuclear installations.
  • All other taxes: taxes, fees, levies or charges not covered by any of the previous five categories: support for district heating; local or regional fiscal charges; island compensation; concession fees relating to licences and fees for the occupation of land and public or private property by networks or other devices.

In addition to these elements, the network cost is split into the respective shares of transmission and distribution. The relative share of consumption in the different consumption bands is reported by the countries and used to calculated the single national electricity prices (weighted averages for consumer bands IA-IF and DA-DE) but not published because it could be used to re-calculate some confidential values.

3.5. Statistical unit

Household and final non-household consumers divided into consumption bands.

3.6. Statistical population

The target population consists of all companies active at the market for household and final non-household consumers. A cut off approach is used for surveying the population. There should be 75% of the market over the cut off limit, where 13 suppliers are surveyed.

3.7. Reference area

National level

3.8. Coverage - Time

Electricity prices data for Sweden are available since 1997.

3.9. Base period

Not applicable.


4. Unit of measure Top

Prices are reported in national currency per kWh. However, Eurostat also calculates and publishes the prices in EURO and PPS (purchasing power parity).
Relative shares of sub-component of the network component and consumption volumes are reported in percentages.


5. Reference Period Top

For semestrial prices, the reference periods are from January to June for semester 1 and from July to December for semester 2.

For annual prices, the reference period is the whole calendar year (from January to December).


6. Institutional Mandate Top
6.1. Institutional Mandate - legal acts and other agreements

At EU level:

  • Regulation (EU) 2016/1952 of the European Parliament and of the Council of 26 October 2016 on European statistics on natural gas and electricity prices and repealing Directive 2008/92/EC (Text with EEA relevance).
  • Commission Implementing Regulation (EU) 2017/2169 of 21 November 2017 concerning the format and arrangements for the transmission of European Statistics on natural gas and electricity prices pursuant to Regulation (EU) 2016/1952 of the European Parliament and of the Council (Text with EEA relevance).
  • Commission Implementing Decision (EU) 2018/1734 of 14 November 2018 granting derogations to the Federal Republic of Germany, the Kingdom of Spain, the Italian Republic and the Republic of Cyprus as regards the provision of statistics pursuant to Regulation (EU) 2016/1952 of the European Parliament and of the Council (notified under document C(2018) 7465) (Text with EEA relevance).
  • http://data.europa.eu/eli/reg_impl/2019/803/oj Commission Implementing Regulation (EU) 2019/823 concerning the content of quality reports on European statistics on natural gas and electricity prices pursuant to Regulation (EU) 2016/1952 of the European Parliament and of the Council (Text with EEA relevance).

At national level:

  • Law regulating the official statistics in Sweden (2001:99)
  • Laws regarding the quality and accessibility (2001:100)
  • Law regulating Statistics Sweden (SCB-FS 2016:17)
  • Law regarding Swedish Energy Agency (STEMFS 2016:5)

 

6.2. Institutional Mandate - data sharing

At EU level:

  • Eurostat does not share the data collected with other organisation appart from its usual dissemination chanel (Eurostat's database, statistic explained articles and press or news release) .

At national level:

  • Data is sent to eurostat
  • Data is shared with the Swedish Energy Agency


7. Confidentiality Top
7.1. Confidentiality - policy

At EU level:

  • Regulation (EC) No 223/2009 of the European Parliament and of the Council, of 11 March 2009, on the transmission of data subject to statistical confidentiality to the Statistical Office of the European Communities.

At national level:

  • The Public Acess to Information and Secrecy Act (2009:400)
7.2. Confidentiality - data treatment

Published data should not allow identification of single consumers or single companies. Since the data published is aggregated prices and no single quantity is published, no method for disclosure protection is used.


8. Release policy Top
8.1. Release calendar

The release calender is available at the official web site for Statistics Sweden. At the web page for the survey the next date for publishing is announced.

8.2. Release calendar access

Publishing calendar (scb.se)

8.3. Release policy - user access

Statistics is published on Statistics Sweden’s web site, aimed at the public. Dissemination is thereby conducted to all users at the same time.


9. Frequency of dissemination Top

Electricity prices in Sweden are published on a semestrial basis on Eurostat's website.

At Statistics Sweden’s web site the data is published on a semestrial basis.


10. Accessibility and clarity Top
10.1. Dissemination format - News release

No news release

10.2. Dissemination format - Publications

No news release

10.3. Dissemination format - online database

No news release but the data is published on Statistics Swedens website.

10.3.1. Data tables - consultations

Not applicable

10.4. Dissemination format - microdata access

The microdata may be available by request for researchers after a confidentiality vetting procedure. The Public Access to Information and Secrecy Act protects data for individual respondents (microdata), but it is possible to apply for access to data for research or statistical purposes. The general policy of Statistics Sweden is to conduct a confidentiality vetting for every request of microdata releases. When access to microdata is granted, data will be compiled by the responsible department and delivered to the user in a secure way.

10.5. Dissemination format - other

Not applicable

10.5.1. Metadata - consultations

Metadata not available

10.6. Documentation on methodology

Metadata not available

10.6.1. Metadata completeness - rate

Not applicable

10.7. Quality management - documentation

Documents regarding quality management are available on Statistics Sweden’s website

https://www.scb.se/hitta-statistik/statistik-efter-amne/energi/prisutvecklingen-inom-energiomradet/energipriser-pa-naturgas-och-el/


11. Quality management Top
11.1. Quality assurance

The quality assurance framework at Statistics Sweden is in line with the ISO 20252 standard. Use of best practices is endorsed by requirements on the Business Support System. Quality reviews with compliance monitoring are performed for a sample of surveys and processes continuously.

11.2. Quality management - assessment

The general quality of this survey is of satisfactory standard. In an effort to improve the quality, the survey will be altered in the near future. The most glaring problems in producing the statistics are time constraints and constraints in resources and personnel.  Administration has been harmonized and more time spent improving the survey. Lastly, it has created more time for the staff to go more in depth in understanding the market.


12. Relevance Top
12.1. Relevance - User Needs

This survey fills an important role for Statistics Sweden regarding prices. There are similar surveys that track offered prices for a specific time-period but this survey tracks de facto prices for that specific time-period.

Important users are the Swedish Energy Agency, the Swedish Energy Markets Inspectorate and companies in the industry. The main use is to follow the price development within the electricity market. Other main users are social services  and housing societies using data for determining cost of living.

 

12.2. Relevance - User Satisfaction

No systematic measure is in place at Statistics Sweden but we accept e-mails and suggestions put forth in such a manner.

12.3. Completeness

Sweden is able to provide all the data requested by the relevant regulations and guidelines

12.3.1. Data completeness - rate

100 %


13. Accuracy Top
13.1. Accuracy - overall

The human error is mostly at fault for possible errors in the survey. These errors are corrected before publication by asking for revised information if the errors are detectable (i.e break a pattern) or are outside an acceptance interval (i.e. developing contrary to the rest of the market). The big source of inaccruacy is that the population of the survey might be non-representative.

13.2. Sampling error

This survey is not a sample survey

13.2.1. Sampling error - indicators

Not applicable

13.3. Non-sampling error

 

Errors might occur due to the market shifting, since the scope of the survey is based on historical figures (the included objects might not reach 75 % coverage a given year due to market changes). If a suspected measurement value is detected the respondent is asked to revise or comment why the information provided is accurate. Information is included in the sub-concepts S.13.3.1-S.13.3.5.

 

13.3.1. Coverage error

Under coverage errors might occur due to lack of update regarding the frame of the survey. As it stands it has not been updated since 2007 and is now updated every year.

13.3.1.1. Over-coverage - rate

No known over-coverage rate.

13.3.1.2. Common units - proportion

100% of the data is collected by the survey except regarding taxes.

13.3.2. Measurement error

Possible measurement errors might come from the respondents adding taxes to the prices. Revising scripts and understanding the process is vital in minimizing this kind of errors.

13.3.3. Non response error

The level of unit non-response is 5-10%, i.e. roughly 2 companies. The weighted rate of unit non-response is probably much lower, since non-response objects are small.

In estimation, non-response is considered to be random, and no adjustments are done. The non-response bias is probably small.

No breakdown of non-response is possible due to lack of data. Estimating the effects on non-response is done by counterfactual analysis. I.e., would the time-series change if the respondent didn’t answer previous semester, if yes their value would be imputed for the current semester.

 

13.3.3.1. Unit non-response - rate

The level of unit non-response is 5–10%, i.e. roughly 2 companies. The weighted rate of unit non-response is probably much lower, since non-response objects are small.

13.3.3.2. Item non-response - rate

All providers who responded to the survey provided all information required.

13.3.4. Processing error

The processing errors hitherto have been due to taxes added to the respondents’ data and revised data being overwritten by original data. Rewriting the solutions and making them more robust has been implemented. 

13.3.5. Model assumption error

At the estimation of prices a model assumption is made that companies below the cut off limit are similar to companies over the limit. This might result in a model assumption error. 


14. Timeliness and punctuality Top
14.1. Timeliness

Electricity providers that participate in the national data collection are requested to provide the electricity price data within 4 weeks after the reference period. After arrival, the statistical office checks the micro-data for correctness, consistency and completeness and national averages are calculated and reported to Eurostat during the third month after the reference period.

14.1.1. Time lag - first result

The first version of the electricity price questionnaire for households for the 1st semester of 2019 was sent 90 days after the reference period.

The first version of the electricity price questionnaire for households for the 2nd semester of 2019 was sent 90 days after the reference period.

The first version of the electricity price questionnaire for households for the 1st semester of 2020 was sent 90 days after the reference period.

The first version of the electricity price questionnaire for households for the 2nd semester of 2020 was sent 90 days after the reference period.

The first version of the electricity price questionnaire for households for the 1st semester of 2021 was sent 120 days after the reference period.

The first version of the electricity price questionnaire for households for the 2nd semester of 2021 was sent 90 days after the reference period.

The first version of the electricity price questionnaire for non-households for the 1st semester of 2019 was sent 90 days after the reference period.

The first version of the electricity price questionnaire for non-households for the 2nd semester of 2019 was sent 90 days after the reference period.

The first version of the electricity price questionnaire for non-households for the 1st semester of 2020 was sent 90 days after the reference period.

The first version of the electricity price questionnaire for non-households for the 2nd semester of 2020 was sent 60 days after the reference period.

The first version of the electricity price questionnaire for non-households for the 1st semester of 2021 was sent 86 days after the reference period.

The first version of the electricity price questionnaire for non-households for the 2nd semester of 2021 was sent 60 days after the reference period.

 

14.1.2. Time lag - final result

2019 and 2020 was within the deadline.  No second version. 

1st semester 2021 was was submitted with one month delay where as 2nd semster 2021 was within the deadline. 

 

14.2. Punctuality

The legal deadline for submitting the questionnaires is the third month after the reference period. 5-10 % do not hand in information in time, to improve this survey should be sent out sooner so that the respondents can plan their time better. One reminder is sent when deadline has passed. Another reminder is sent 2 weeks after the deadline. Lastly if the company hasn´t sent the information required by that time phone calls are made to make contact with said company.

14.2.1. Punctuality - delivery and publication

The legal deadline for submitting the questionnaires is the third month after the reference period. One delivery were not on time, according to 14.1.2 above. The reasons for delay was human errors with regarding to scripts handling the data. This problem did not alter the prices. 


15. Coherence and comparability Top
15.1. Comparability - geographical

The data is comparable to data collected in other geographical areas.

15.1.1. Asymmetry for mirror flow statistics - coefficient

Not applicable

15.2. Comparability - over time

From 2007 a new method was used for calculating prices. Before 2007 the average price a specific day was collected and analyzed. After 2007 the data collected was the average price a given semester. This makes comparability over time fairly poor. A major modification of the sample frame of the survey was made in 2020 to increase the quality of inflow of data mainly by decreasing the undercoverage. 

15.2.1. Length of comparable time series

4

15.3. Coherence - cross domain

Not applicable

15.3.1. Coherence - sub annual and annual statistics

Not applicable

15.3.2. Coherence - National Accounts

Not applicable

15.4. Coherence - internal

Not applicable


16. Cost and Burden Top

The cost for production of this statistics is 200 000 Swedish crowns per year. There is no estimate regarding cost for the respondents.

The survey keeps the questions needed to be answered to a bare minimum. The gathering of information is being made over the internet by our own web-based tool.


17. Data revision Top
17.1. Data revision - policy

The data is revised during semester 2.   

Statistics Sweden has a revision policy (in Swedish): https://www.scb.se/contentassets/99b579ae03d245c1a5700c12947746cf/revideringspolicy-2018.pdf

17.2. Data revision - practice

The main reasons for revisions are revised data from the companies due to manual errors. 

17.2.1. Data revision - average size

Household electricity prices collection: 4.031697044

Non-household electricity prices collection: 161.3565977


18. Statistical processing Top
18.1. Source data

The data is provided by the electricity companies.

18.2. Frequency of data collection

Half-year intervals.

18.3. Data collection

The data is collected via an online survey. The companies responding to this survey are given a username and a password. Via the login information they can reach Statistics Sweden’s web site and respond to the survey regarding electricity prices.

18.4. Data validation

Data is validated by outlier detection and time series analysis both on a macro and a micro level. Lastly, there are surveys regarding price levels offered monthly which the data can be compared to for analisis and if the patterns diverge it calls for more investigation.

18.5. Data compilation

The data is compiled by taking the weighted average price from the respondents and using outlet points and delivered quantites of electricity. 

18.5.1. Imputation - rate

Imputation for not responding companies has been made with last available data, the imputation rate is approximately 4%. 

18.6. Adjustment

If rounding errors or when wrong measurement have been used, an e-mail is sent to the respondent in question asking for confirmation and afterwards the error is manually corrected.

18.6.1. Seasonal adjustment

Seasonable adjustments are not carried out.


19. Comment Top

 


Related metadata Top


Annexes Top