1.1. Contact organisation
The Central Statistical Bureau of Latvia (CSB)
1.2. Contact organisation unit
Social Statistics Methodology Section
1.3. Contact name
Restricted from publication1.4. Contact person function
Restricted from publication1.5. Contact mail address
Lāčplēša iela 1, Rīga, LV – 1301
1.6. Contact email address
Restricted from publication1.7. Contact phone number
Restricted from publication1.8. Contact fax number
Restricted from publication2.1. Metadata last certified
27 December 20242.2. Metadata last posted
27 December 20242.3. Metadata last update
27 December 20243.1. Data description
The EU survey on the use of ICT in households and by individuals is an annual survey conducted since 2002. In Latvia, it has been conducted since 2004.
In 2024, the survey collects data on the access to information and communication technologies (ICT), on the use of the internet, e-government and e-commerce, internet of things, as well as green ICT.
3.1.1. Survey name in national and English languages
National language: Interneta lietošana 2024. gadā
English: Community survey on ICT usage in households and by individuals 2024
Questionnaire(s) in national language(s) and the translation in English are available in the Annexes below.
Annexes:
ICT questionnaire 2024 (English)
ICT questionnaire 2024 (Latvian)
3.2. Classification system
The following common concepts and definitions apply under the Integrated European Social Statistics (IESS):
- the International Standard Classification of Education (ISCED) 2011 published in the following breakdowns: low (ISCED levels 0-2: no formal education, primary education or lower secondary education), medium (ISCED levels 3-4: upper secondary or post-secondary non-tertiary education) and high (ISCED levels 5-6: tertiary programmes which normally need a successful completion of ISCED 3 or 4, or second-stage tertiary education leading to an advanced research qualification);
- the International Standard Classification for Occupation ISCO-08 at the 2-digit level;
- the Classification of Economic Activities (NACE Rev.2-2008), at section level;
- the Common classification of territorial units for statistics (NUTS 1) – finer granularity of NUTS 2 is provided on optional basis by some Member States;
- the SCL – Geographical code list;
- information about household income is provided at lower level of detail.
Additional classifications used in the national questionnaire: Additionally, data is broken down by Common classification of territorial units for statistics (NUTS 3), for Latvia they are: LV003 Kurzeme, LV005 Latgale, LV006 Rīga, LV007 Pierīga, LV008 Vidzeme, LV009 Zemgale.
3.3. Coverage - sector
The ICT survey in households and by individuals covers those households having at least one member in the age group 16 to 74 years old. Internet access of households refers to the percentage of households that have an internet access, so that anyone in the household could use the internet.
3.3.1. Differences in scope at national level
No differences in scope at national level.
3.4. Statistical concepts and definitions
The survey is collecting data of internet users, individuals who have used the internet in the three months prior to the survey.
This annual survey is used to benchmark ICT-driven developments, both by following developments for core variables over time and by looking in greater depth at other aspects at a specific point in time. While the survey initially concentrated on access and connectivity issues, its scope has subsequently been extended to cover a variety of subjects (for example, the use of internet, e-government, e-commerce, internet of things and green ICT) and socio-economic analysis (such as regional diversity, gender specificity, differences in age, education and the employment situation). The scope of the survey with respect to different technologies is also adapted to cover new product groups and means of delivering communication technologies to end-users.
For more details on the methodology applicable in each survey year, please consult the Compiler's Manual for the respective year.
Deviations from standard ICT concepts: No deviations at national level
3.5. Statistical unit
Households and Individuals
3.6. Statistical population
In the ICT usage survey, the target population for the different statistical units is:
- individuals: all individuals aged 16 to 74;
- households: all (private) households with at least one member aged 16 to 74.
Target population composed of households and/or individuals:
- Number of households: Not applicable
- Number of individuals: 1348252
3.6.1. Non-compulsory age groups
Non-compulsory age groups also included in the target population:
| No | Yes | Age scope | |
| Individuals younger than 16? | X | ||
| Individuals older than 74? | X |
3.6.2. Population not covered by the data collection
| Non-target population (the difference between the total population and the target population) | Households | Individuals |
|---|---|---|
| Approximate number of units outside the general scope of the survey (for example individuals younger than 16 or older than 74; households with all members over 74 years old). | 490753 | |
| Estimate of the resulting percentage of under-coverage (non-covered population compared to the total country), if applicable | 26.69% |
3.7. Reference area
The survey covered whole territory of Latvia. Additionally, data breakdown for NUTS 3 regions (LV003 Kurzeme, LV005 Latgale, LV006 Rīga, LV007 Pierīga, LV008 Vidzeme, LV009 Zemgale)
3.8. Coverage - Time
Year 2024
3.9. Base period
Not applicable
Percentages of ‘Households’ and Percentages of ‘Individuals’
For most questions the reference period is the last three months before the interview. Questions in the modules on e-government and eID refer to the 'last year' before the interview.
Deviation from this statement: No deviations.
5.1. Survey period
Survey period was from January 8th till May 26th, 2024.
6.1. Institutional Mandate - legal acts and other agreements
The legal basis for the 2024 EU survey on the use of ICT in households and by individuals is the Regulation (EU) 2019/1700 of the European Parliament and of the Council of 10 October 2019 establishing a common framework for European statistics relating to persons and households, based on data at individual level collected from samples (OJ L 261 I, 14 October 2019, p. 1), as implemented by the Commission Implementing Regulation (EU) 2023/1484 of 18 July 2023 specifying the technical items of the data set, establishing the technical formats for transmission of information and specifying the detailed arrangements and content of the quality reports on the organisation of a sample survey in the use of information and communication technologies domain for reference year 2024 in accordance with Regulation (EU) 2019/1700 of the European Parliament and of the Council (OJ L 182, 19 July 2023 pp. 100-149) and Commission Delegated Regulation (EU) 2023/1797 of 7 July 2023 supplementing Regulation (EU) 2019/1700 of the European Parliament and of the Council by specifying the number and titles of the variables for the use of information and communication technologies statistics domain for the reference year 2024 (OJ L 233, 21 September 2023).
Complementary national legislation constituting the legal basis for the survey on the use of ICT in households and by individuals:
- National Statistics Law
- Grozījumi Ministru kabineta 2016. gada 20. decembra noteikumos Nr. 812 "Oficiālās statistikas veidlapu paraugu apstiprināšanas un veidlapu aizpildīšanas un iesniegšanas noteikumi (No translation available in English)
6.2. Institutional Mandate - data sharing
Not applicable
7.1. Confidentiality - policy
The information provided by respondents is protected with Latvia’s “Statistics Law”:
- Section 7, part 2, point 8, which states date dissemination of official statistics should be done ensuring equal treatment of all users.
- Section 17, which states all the data process and statistical confidentiality aspects.
- Section 19, part 1, which states that official statistics should be disseminated in a way that does not allow either directly or indirectly identify a private individual or a State institution in cases other than those laid down in Section 25 of this Law.
Full “Statistics Law” is available here: Statistics Law
Regarding prevention of identification of household and individual – Microdata from ICT HH and IND survey are kept in the data servers of CSB and are not publicly available. They can be accessed using CSB internal software Metadata Driven Integrated Statistical Data Management System (ISDAVS) (developed by CSB of Latvia), and access is granted only to the persons that works with this survey. Only aggregated data is used when results of the survey are published.
7.2. Confidentiality - data treatment
Microdata (data with any identifiable information about the respondents removed) from ICT HH and IND survey are kept in the data servers of CSB and are not publicly available. They can be accessed using CSB internal software Metadata Driven Integrated Statistical Data Management System (ISDAVS) (developed by CSB of Latvia), and access is granted only to the persons who work with this survey. Only aggregated data is used when results of the survey are published.
Only institution microdata is sent to is Eurostat. The data are transmitted in accordance with the technical standards established by Eurostat.
8.1. Release calendar
Official CSB data and press release calendar is published on the website of CSB and is publicly accessible
8.2. Release calendar access
Access to Official CSB data and press release publication calendar is allowed for everyone.
The Data release calendar is available here: Advance dissemination calendar
8.3. Release policy - user access
The policy for data releases is planned year before as part of whole Data release calendar of CSB.
Regarding ICT three disseminations of data are done:
1) Data are published on public databases of Official statistical portal of Latvia.
2) An informative review on the main findings was published on 6 November 2024 (only available in Latvian);
3) Press release for the 2024 survey on individuals' online purchasing activity.
Information about these publications is put on social media accounts of CSB from were public, as well as news sites, are informed about them. After that, publications of press release are available in news sites as well, which means the additional part of public is informed about results of the survey.
Dissemination of data does not deviate from general dissemination policy of CSB.
Annual
10.1. Dissemination format - News release
Press release for the 2024 survey on individuals' online purchasing activity (published on 06 November 2024).
Website to press release.
10.2. Dissemination format - Publications
An informative review on the main findings was published on 6 November 2024 (only available in Latvian).
Website to publication.
10.3. Dissemination format - online database
Survey data was published on the Official statistics of Latvia website on November 5th 2024.
Website to online data base where all data from ICT surveys are published.
10.3.1. Data tables - consultations
Any questions regarding the content of published data tables should be directed to the person responsible listed on the survey metadata page on the Official statistics of Latvia website.
Website to metadata page.
10.4. Dissemination format - microdata access
No microdata was made available to public.
10.5. Dissemination format - other
No other disseminations of data were made.
10.5.1. Metadata - consultations
Any questions regarding metadata should be directed to the person responsible listed on the survey metadata page on the Official statistics of Latvia website.
Website to metadata page.
10.6. Documentation on methodology
Information about the ICT HH survey is available here: Use of ICT in households
Information that is published about this survey:
- Contact information of person and institution overseeing survey.
- Statistical presentation which includes data description, statistical concepts and definitions, descriptions of statistical unit and statistical population.
- Comparability.
- Statistical processing which includes descriptions of source data and data collection
10.6.1. Metadata completeness - rate
Not available.
10.7. Quality management - documentation
Quality guidelines of the CSB is an informative document describing the CSB and the main aspects of its activity: stages, methods and organizational principles of producing the national statistics, policy of data protection and dissemination. The objective of these Guidelines is to promote the implementation of the CSB’s operational strategy by involving in this process every employee of the CSB, developing the communication with society and extending the knowledge of every interested person – respondent, data user and all society – about the activity of CSB.
11.1. Quality assurance
The CSB has Quality guidelines which is an informative document describing the CSB and the main aspects of its activity: stages, methods and organizational principles of producing the national statistics, policy of data protection and dissemination. The objective of these Guidelines is to promote the implementation of the CSB’s operational strategy by involving in this process every employee of the CSB, developing the communication with society and extending the knowledge of every interested person – respondent, data user – about the activity of CSB.
Annexes:
11.2. Quality management - assessment
In order to ensure higher quality to a maximum extent from both ethical and professional aspect, national statistics similarly to the EU statistics must follow the principles of impartiality, reliability, relevance, cost-effectiveness, statistical confidentiality and transparency. The CSB operates in compliance with principles stipulated by the European Statistics Code of Practice that comprises the independence standard of the European Statistical System, provides further guarantee for good operation of ESS and ensuring reliable statistics.
One of the CSB’s activities is to introduce the basics of the Total Quality Management System – to identify statistical and organizational processes and develop their descriptions in compliance with requirements of the quality management system. The fundamental idea of the quality management system is to promote complete satisfaction of wishes and needs of data users to a maximum extent by continuous improvement of the statistical institution's activity.
12.1. Relevance - User Needs
At European level, European Commission users (e.g. DG CNECT, DG GROW, DG JUST, DG REGIO, DG JRC etc.) are the principal users of the data on ICT in households and by individuals and contribute in identifying/defining the topics to be covered. Hence, main users are consulted regularly (at hearings, task forces, ad hoc meetings) for their needs and are involved in the process of the development of the model questionnaires at a very early stage.
User needs are considered throughout the whole discussion process of the model questionnaires aiming at providing relevant statistical data for monitoring and benchmarking of European policies.
At national level, main data users are Ministry of Transport, Ministry of Economics and Ministry of Environmental Protection and Regional Development.
12.2. Relevance - User Satisfaction
No actions to measure user satisfaction were made.
12.3. Completeness
All mandatory variables requested from Eurostat were included in the Transmission format. Variables were recoded following the descriptions that were in the Transmission format in accordance with the technical standards established by Eurostat.
12.3.1. Data completeness - rate
All mandatory variables have been transmitted.
13.1. Accuracy - overall
Described below.
13.2. Sampling error
The precision estimation is done by the ultimate cluster method (Hansen, Hurwitz and Madow, 1953) with Taylor linearization for non-linear statistics and residual estimation from the regression model to take weight calibration into account. CSB Latvia developed R package vardpoor (published on CRAN R project) is used for estimation of standard errors.
The estimation of standard errors was done by the ultimate cluster method (Hansen, Hurwitz and Madow, 1953) with Taylor linearization for non-linear statistics and residual estimation from the regression model to take calibration into account.
Unit non-response:
The variance estimator has to be adjusted to take unit non-response into account. Different methods can be used: methods based on the assumption that respondents are missing at random or completely at random within e.g. strata or constructed response homogeneity groups, methods using the two-phase approach, etc.
Calibration:
Methods to account for the effect of calibration on variance should be used, e.g. Deville and Särndal method (1992).
Sampling method – estimation method
Main reference in the literature: E. Sarndal, B. Swensson, J. Wretman (1992), Model Assisted Survey Sampling.
Additional comments on the reliability and representativeness of the results of the indicators:
Estimated standard errors in sections for variables meet all requirements (2% requirement for overall proportions and 5% requirement for proportions in subgroups). The final sample size (8501 individuals) is reduced provided the unit response rate keeps stable at the 0.65 level.
13.2.1. Sampling error - indicators
Precision estimates for the question "Individuals having ordered goods or services for private use over the internet in the last 12 months" (individuals who ticked 'Within the last 3 months' or 'Between 3 months and a year ago' in in the question “When did you last buy or order goods or services for private use over the internet?”):
- Number of respondents (absolute value for ‘Yes’ answers): 3488
- Estimated proportion (in %): 64.97%
- Standard error (in percentage points): 0.53
Details of the breakdowns are available in document "Standard errors – Mandatory – Optional questions_LV – 2024" in the Annexes below.
13.3. Non-sampling error
See more details on non-sampling error below.
13.3.1. Coverage error
Sample frame is made in a way, to create the best possible coverage of target population, while minimizing over-coverage errors and their impact. For more detail see section 18.1.1.
13.3.1.1. Over-coverage - rate
Unweighted over-coverage - rate: 2.01%
Design weighted over-coverage - rate: 2.03%.
13.3.1.2. Common units - proportion
Not requested in the ICT survey.
13.3.2. Measurement error
Measurement errors: No such errors occurred.
Questionnaire design and testing: For all the data collection methods electronic questionnaire in Metadata Driven Integrated Statistical Data Management System (ISDAVS) (developed by CSB of Latvia) was designed. Testing of the questionnaire was done mainly by CSB employees from the Social Statistics department as well as employees from Data collection sections which were directly responsible for data collection.
Interviewer training: Interviewer seminars were held to introduce interviewers with the new form of questionnaire. This seminar also included in-depth description of the new questions as well as information about things that need to be taken into account from previous surveys.
Proxy interview rates: Not applicable.
13.3.3. Non response error
Information about non-respondents:
The most common reason for non-response was refusal to take part in the survey, followed by inability to contact respondents. The inability to contact respondents was primarily due to issues with the telephone numbers provided. These issues included numbers that had no recipients (e.g., they belonged to someone else, were no longer in use, or were unreachable). The second most common reason for non-response was that the person reached did not match the intended respondent listed.
13.3.3.1. Unit non-response - rate
The unit non-response rate is the ratio of the number of in-scope non-respondents (= number of rejected interviews) to the number of eligible elements selected from the sampling frame.
Unit non-response rate for
- Households: Not applicable
- Individuals (aged 16-74): 32.1%
13.3.3.1.1. Unit non-response – sample sizes
| Number of households | Number of individuals (aged 16-74) |
Number of individuals (< 16) |
Number of individuals (> 74) |
|
| Gross sample [A]The number of households/individuals initially selected from the sampling frame (if not applicable, indicate why below the table) | 8500 | |||
| Ineligible: out-of-scope [B] For example, when a selected household is not in the target population because all members are over 75 years old or when no dwelling exists at the selected address, or a selected individual has died between the reference data of the sampling frame at the moment of the interview. | 171 | |||
| Number of eligible elements [C]Gross sample size corrected of the ineligible cases | 8329 | |||
| Net sample size or final sample [D]The net sample size (or final sample) corresponds to the number of households/individuals that can be used in the final database. | 5656 | |||
| Unit response rate [E] = [D] / [C]The unit response rate is the ratio of the number of in-scope respondents (= the number of achieved interviews or the net sample size) to the number of eligible elements selected from the sampling frame. | 67.9% |
13.3.3.1.2. Unit non-response – methods, minimization and substitution
- Methods used for dealing with unit non-response: Re-weighting by identified response homogeneity groups (created using sample-level information).
- Methods used for minimizing unit non-response: Compared to the 2023 survey, the response rate increased by 0.6 percentage points (67.2% in 2023, 67.9% in 2024). CAWI data collection was used to launch the survey. Before it began, respondents were sent letters and e-mails to inform them that they had been included in the sample, were asked (if possible) to complete the questionnaire using the CAWI, and informed that if they did not do so they would be contacted by an interviewer. Those respondents who could not be contacted by phone were interviewed in person. During data collection, 744 respondents were interviewed face-to-face (CAPI).
- Substitution permitted: No.
- Substitution rate (in %): Not applicable.
13.3.3.2. Item non-response - rate
Items with low response rates (observed rates in %): Household income has a high non-response rate of 74% and is therefore imputed.
13.3.4. Processing error
No processing errors accrued.
Data was checked comparing it to last year’s data (internally as well as by Eurostat), data that had the biggest differences were checked again in micro level and no problems were found.
No editing of the data took place.
13.3.5. Model assumption error
Not applicable
14.1. Timeliness
Date of data dissemination at national level:
The data was dissemination on national level was done on November 5th 2024.
If the calculation is done from the day the fieldwork ended, then it is 163 days. Such time lag is due to after the fieldwork is ended data is checked, weighted and aggregated tables are created. After all that, data is validated by Eurostat and only after confirmation of the data being correct, they are published in Official statistics of Latvia website.
14.1.1. Time lag - first result
Restricted from publication14.1.2. Time lag - final result
Restricted from publication14.2. Punctuality
28 days
14.2.1. Punctuality - delivery and publication
Final dataset which was accepted by Eurostat was uploaded to EDAMIS on September 6th 2024, which was 28 days ahead of schedule.
15.1. Comparability - geographical
There is no problem of comparability across the country’s regions.
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not relevant
15.2. Comparability - over time
Possible limitations in the use of data for comparisons over time: Not relevant
15.2.1. Length of comparable time series
The length of comparable time series depends on the module and variable considered within each of the modules of the survey.
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
All statistics are coherent within the dataset provided by the country.
15.4.1. Survey questionnaire – mandatory questions
MANDATORY questions in the Eurostat model questionnaire 2024:
All mandatory questions were included in the model questionnaire with no deviations from Eurostat’s version of model questionnaire.
Table 15.4.1. of document "Standard errors – Mandatory – Optional questions_LV – 2024" in the Annexes lists the questions for which the coverage of subjects and characteristics reflected in the national questionnaire differs from Annex 2 of the Commission Delegated Regulation (EU) 2023/1797 of 7 July 2023.
15.4.2. Survey questionnaire – optional questions
Adoption of OPTIONAL questions and items in the Eurostat model questionnaire 2024:
Table 15.4.2. of document "Standard errors – Mandatory – Optional questions_LV – 2024" in the Annexes lists the optional questions from the annual Eurostat model questionnaire 2024 included in the national questionnaire and their coverage for age groups beyond the standard scope.
15.4.3. Survey questionnaire – additional questions at national level
Additional questions introduced in the national questionnaire in 2024: No additional questions
15.4.4. Survey questionnaire – deviations
Effects of deviations from the routing used in the Eurostat model questionnaire: No deviations from the routing used in the Eurostat model questionnaire.
17.1. Data revision - policy
Planned revisions of statistical data are understood as:
- further updates of previously published data of higher aggregation level, by adding more detailed information on the aggregation level;
- revision of published data by applying seasonal adjustment method or changing the definition of reference period;
- revision of published data pursuant to the changes in the methodology or classifications.
In general, statistical data is revised pursuant to the planned revision cycle and timetable: information is stored on the errors in the data sources or calculations after data publishing till the next planned data publishing date, thus following the planned revision cycle and timetable, as well as avoiding to carry out data revision too frequently.
Unplanned revisions of statistical data are such revisions, which cannot be impartially connected to the previously defined revision cycle. Necessity to carry out unplanned revisions can emerge when identifying significant errors in data sources or calculations, as well in cases if methodology or data sources are changed without being planned to. Unplanned data revisions are carried out in exceptional cases when the amount of revision according to the assessment of the CSB’s experts has a significant impact on the quality of remaining statistical data.
Revised and/or further to be revised statistical data, when adding them to publicly available databases or statistical publications, are particularly stipulated or marked. It is carried out as:
- reference to the revision policy or a link to the CSB web site;
- report on the amount of carried out revisions and assessment of their impact.
As the result of significant methodological changes, the revised data is published only after the introduction of the most important data users with reasons for the expected revision, methodology used in recalculations, possible impact of data revision and other related information. Informing the data users can be carried out through a press release of respective content timely placed on the CSB Web site or having discussions with data users.
17.2. Data revision - practice
No data revision to report.
17.2.1. Data revision - average size
Not relevant
18.1. Source data
The source of the raw data is described with more details in the paragraphs below.
18.1.1. Sampling frame
The sampling frame included all individuals aged 16 to 74, who were permanent residents in private households in the Republic of Latvia at the time the sampling process began. This sampling frame was created using an automated tool developed by the Central Statistical Bureau (CSB). The tool integrates information from various registers and additional sources in line with the definition of the target population. These registers include the Register of Natural Persons, the National Address Register, and data on short-term residence permits.
The information used for the sampling frame was based on data from November, which was the most recent available at the time. The sample was independent, and participation in the survey was voluntary.
18.1.2. Sampling design
The 2024 ICT survey was a "stand-alone survey" and was not integrated into any other social surveys.
The sampling design for the ICT 2024 survey employed a one-stage systematic stratified sampling method. Stratification was based on the type of territory (Riga (the capital city), 9 state cities, towns, and rural areas), gender, and age groups (16-24, 25-34, 35-44, 45-54, 55-64, 65-74), resulting in a total of 48 strata. An additional 4 strata were added for respondents with unknown territorial variables, categorized by gender and age groups (16-44 and 45-74).
Before selection, the units were sorted by strata, ATVK (Classification of Administrative Territories and Territorial Units), polygon, neighborhoods (for two cities), and random number.
For the allocation of units within strata, a mean value between the Neyman optimal allocation method and the proportional allocation approach was used.
18.1.3. Net effective sample size
Restricted from publication18.2. Frequency of data collection
Annual
18.3. Data collection
1) Methods used to gather data: Data was gathered using CAWI, CATI and CAPI methods.
2) Short description of the survey method:
Overall 5656 interviews were collected, using two data gathering methods:
- a) Web survey (CAWI) from which ... interviews (9.2% of achieved interviews) were collected.
- b) Telephone interviews (CATI) from which ... interviews (77.7 % of achieved interviews) were collected.
- c) Face to face interviews (CAPI) from which ... interviews (13.2% of achieved interviews) were collected
3) Variables completed from an external source:
The only variables that were gathered using administrative registers were the social demographics ones:
- G1. Age in completed years (all items) - Information obtained from Population register.
- G2. Sex - Information obtained from Population register.
- G3. Country of birth - Information obtained from Population register.
- G4. Country of main citizenship - Information obtained from Population register.
- G11. Occupation in the main job - Information obtained from State Revenue Service.
- G12. Region of Residence - Information obtained from Population register.
- G15. Degree of urbanisation - Information obtained from Population register.
18.4. Data validation
The filters of the model questionnaire were implemented in data collection systems, they were tested before the start of the survey to make sure they are working correctly and are in line with Eurostat’s model questionnaire.
Validations implemented in the data collection system was:
- If the person says he/or she used internet between 1 year and 3 months ago, that he or she cannot say that they bought something on the internet in the last three months.
- Person cannot say “none of the above” if some reply options “from above” are checked.
Aggregated results were checked comparing them to results from previous years, it was done internally as well as by Eurostat. If the changes in percentages were more than +/- 5% Or data was considered as outlier microdata was checked again.
18.5. Data compilation
Details on imputation and grossing procedures are described in paragraphs below.
18.5.1. Imputation - rate
For the target indicator "Individuals having ordered goods or services for private use over the internet in the last 12 months" (individuals who ticked 'Within the last 3 months' or 'Between 3 months and a year ago' in the question “When did you last buy or order goods or services for private use over the internet?”:
- Imputation rate (% of observations): 0%
- Imputation rate (share of estimate): 0%
18.5.2. Use of imputation methods
Methods used to impute item non-response: The hot-deck method was applied for imputing occupation and household income data.
18.5.3. Grossing-up procedures
Grossing up procedures have been applied to Individuals and/or Households: Individuals and Households
Description of the weighting procedures:
For households: The final household weights were calculated after the calculation of individual weights by dividing the final individual weight by the number of individuals in the household.
For individuals: Weighing process was done in three steps:
- First, design weights were computed as normed inverse of the inclusion probabilities according to the sampling design.
- Second, weights were adjusted for non-response – multiplied by a factor inversely proportional to the response rate within each weighing cell (strata).
- Third non-response weights were calibrated in order to meet consistency between known auxiliary and survey variables - on the basis of demographic data breaking down by the type of territory (Riga, cities, towns, rural areas), 6 age groups (16-24; 25-34; 35-44; 45-54; 55-64; 65-74), sex and 6 administrative territories (NUTS3 level, statistical regions).
18.6. Adjustment
Not relevant
18.6.1. Seasonal adjustment
Not relevant
No other comments.
The EU survey on the use of ICT in households and by individuals is an annual survey conducted since 2002. In Latvia, it has been conducted since 2004.
In 2024, the survey collects data on the access to information and communication technologies (ICT), on the use of the internet, e-government and e-commerce, internet of things, as well as green ICT.
The survey is collecting data of internet users, individuals who have used the internet in the three months prior to the survey.
This annual survey is used to benchmark ICT-driven developments, both by following developments for core variables over time and by looking in greater depth at other aspects at a specific point in time. While the survey initially concentrated on access and connectivity issues, its scope has subsequently been extended to cover a variety of subjects (for example, the use of internet, e-government, e-commerce, internet of things and green ICT) and socio-economic analysis (such as regional diversity, gender specificity, differences in age, education and the employment situation). The scope of the survey with respect to different technologies is also adapted to cover new product groups and means of delivering communication technologies to end-users.
For more details on the methodology applicable in each survey year, please consult the Compiler's Manual for the respective year.
Deviations from standard ICT concepts: No deviations at national level
Households and Individuals
In the ICT usage survey, the target population for the different statistical units is:
- individuals: all individuals aged 16 to 74;
- households: all (private) households with at least one member aged 16 to 74.
Target population composed of households and/or individuals:
- Number of households: Not applicable
- Number of individuals: 1348252
The survey covered whole territory of Latvia. Additionally, data breakdown for NUTS 3 regions (LV003 Kurzeme, LV005 Latgale, LV006 Rīga, LV007 Pierīga, LV008 Vidzeme, LV009 Zemgale)
For most questions the reference period is the last three months before the interview. Questions in the modules on e-government and eID refer to the 'last year' before the interview.
Deviation from this statement: No deviations.
Described below.
Percentages of ‘Households’ and Percentages of ‘Individuals’
Details on imputation and grossing procedures are described in paragraphs below.
The source of the raw data is described with more details in the paragraphs below.
Annual
Date of data dissemination at national level:
The data was dissemination on national level was done on November 5th 2024.
If the calculation is done from the day the fieldwork ended, then it is 163 days. Such time lag is due to after the fieldwork is ended data is checked, weighted and aggregated tables are created. After all that, data is validated by Eurostat and only after confirmation of the data being correct, they are published in Official statistics of Latvia website.
There is no problem of comparability across the country’s regions.
Possible limitations in the use of data for comparisons over time: Not relevant