The Central Statistical Bureau of Latvia

Trade and Services Statistics Section

Lāčplēša iela 1, Rīga, LV – 1301

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 2022, the survey collects data on the access to information and communication technologies (ICT), on the use of the internet, e-government, e-commerce, internet of things, as well as green ICT.

National language: Interneta lietošana 2022. gadā

English: Community survey on ICT usage in households and by individuals 2022

Questionnaire(s) in national language(s) and the translation in English are available in the annex.

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.

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.

No differences in scope at national level.

The survey is collecting data of internet users, individuals who have used the internet in the three months prior to the survey. Regular internet users are individuals who used the internet, on average, at least once a week 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 e-government and e-commerce) 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 so as 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 Methodological Manual for the respective year on CIRCABC - Methodological Manual - Information society statistics (europa.eu).

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:  1 153 119

Non-compulsory age groups also included in the target population:

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).

Year 2022

Not applicable

Percentages of ‘Households’ and Percentages of ‘Individuals’

Reference period is the 1st quarter of 2022.

Survey period was from 20 January 2022 till 9 June 2022.

The legal basis for the 2022 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, 14.10.2019, p. 1), as implemented by the Commission Implementing Regulation (EU) 2021/1223 of 27 July 2021 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 2022 pursuant to Regulation (EU) 2019/1700 of the European Parliament and of the Council (OJ L 2269, 27.07.2021, pp. 1-45).

Complementary national legislation constituting the legal basis for the survey on the use of ICT in households and by individuals:

• National Statistics Law (https://likumi.lv/ta/en/en/id/274749)
• OGrozījumi Ministru kabineta 2016. gada 20. decembra noteikumos Nr. 812 "Oficiālās statistikas veidlapu paraugu apstiprināšanas un veidlapu aizpildīšanas un iesniegšanas noteikumi (https://likumi.lv/ta/id/328691-grozijumi-ministru-kabineta-2016-gada-20-decembra-noteikumos-nr-812-oficialas-statistikas-veidlapu-paraugu-apstiprinasanas) (No translation available in English)

Not applicable.

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: https://likumi.lv/ta/en/en/id/274749

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.

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 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.

Official CSB data and press release calendar is published on the website of CSB and is publicly accessible.

Access to Official CSB data and press release publication calendar is allowed for everyone.

The Data release calendar is available here.

The policy for data releases is planned year before as part of whole Data release calendar of CSB.

Regarding ICT two disseminations of data are done:

1) Data are published on public databases of Official statistical portal (https://stat.gov.lv/en/statistics-themes/information-technologies).

2) Press release is published on Official statistical portal (Press release about survey 2022 is available here: https://stat.gov.lv/en/statistics-themes/information-technologies/computers-and-internet/press-releases/8195-internet?themeCode=DL).

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 do not deviate from general dissemination policy of CSB.

Annual

Press release about main findings was published on 4 November 2022.

Link to the press release: https://stat.gov.lv/en/statistics-themes/information-technologies/computers-and-internet/press-releases/8195-internet?themeCode=DL

No publications were made.

Publication of data in online data bases in Official statistical portal was done on 2 November 2022.

Link to online data base where all the data from ICT surveys are published: https://stat.gov.lv/en/statistics-themes/information-technologies

Not available.

No microdata was made available to public.

No other disseminations of data were made.

Not available.

Information about the ICT HH and IND survey is available here: https://stat.gov.lv/en/metadata/5864-use-ict-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.

Not available.

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.

https://www.csp.gov.lv/en/quality-assurance-framework

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.

It is available on CSB website under the following link: https://www.csp.gov.lv/en/quality-assurance-framework

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.

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.

No actions to measure user satisfaction were made.

All mandatory variables requested from Eurostat were included in Transmission format. Variables were recoded following the descriptions that were in the Transmission format in accordance with the technical standards established by Eurostat.

Mandatory variables have been transmitted.

Described in further sub-concepts.

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 https://cran.rproject.org/web/packages/vardpoor/index.html) 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 (8507 individuals) is reduced provided the unit response rate keeps stable at the 0.65 level.

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 question D1 of the 2022 model questionnaire):

Number of respondents (absolute value for ‘Yes’ answers): 3458

Estimated proportion (in %): 61.7

Standard error (in percentage points): 0.56

Details of the breakdowns are available in the Annex below. 

See more details on non-sampling error below.

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.

Unweighted over-coverage - rate: 0.0163433274544386.

Design weighted over-coverage - rate: 0.0161795503078695.

Not requested in the ICT survey.

1) Measurement errors:  No such errors ocured.

2) 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 by CSB employees from Trade and Services Statistics Section as well as employees from Data collection sections which were directly responsible for data collection.

3) 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.

4) Proxy interview rates:  Not applicable.

Information about non-respondents:  Most common nonresponce reason was refusal to take part in survey, followed by unavailability to contact respondents, mainly due to a part that telephone number that was provided for respondents was unusable (belonged to another person, was no longer in use, was not reachable etc.) and simply not encoutering the person.

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).

Unit non-response rate for

• Households:   
  
• Individuals (aged 16-74):   30.6% 

Comments, if any:

1) Methods used for dealing with unit non-response:  Re-weighting by identified response homogeneity groups (created using sample-level information).

2) Methods used for minimizing unit non-response:  Comparing with survey 2021 the response rate increased by 3 percentage points (2021 response rate – 65.3%, 2022 – 68.4%). For start of the survey CAWI data collection was used. Before it started, letters and e-mails were sent to respondents to inform them that they are included in the sample, they were asked to (if possible) fill out questionnaire using CAWI and informed that if it wouldn’t be done than the interviewer will contact them. After that CATI data collection was done, 18 respondents were interviewed via CAPI because there were no telephone number available for them. The telephone numbers and e-mails acquired from Road Traffic Safety Directorate of the Republic of Latvia, Office of Citizenship and Migration Affairs, State Revenue Service as well as mobile operator “Tele 2” gave a wide database of which were used for data collection via CATI and CAWI. The extra telephone numbers were the main way to minimize unit non-response, since it gave more precise contact information. Rise of the response rate led to believe that for respondents this is more convenient way to answer questions (interview can be done in time that is more suitable for respondents) also interviews cost less, since there are no transport costs.

3) Substitution permitted:  No

4) Substitution rate (in %):  Not applicable.

Items with low response rates (observed rates in %): No methodology to calculate "Item non-response - rate" have been developed in CSB.

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

Not requested for ICT Survey

The data was dissemination on national level was done on 2 November 2022.

If the calculation is done from the day the fieldwork ended, then it is 146 days. Such time lag is because after the fieldwork is ended data is checked, weighted and aggregated tables are made. After all that, data as validated by Eurostat and only after confirmation that data are correct, they are published in Official statistical portal.

1 day.

Final dataset which was accepted by Eurostat was sent on 4 October 2022. The deadline for this delivery was 5 October 2022, so the delivery was done 1 day before the deadline.

No such problems were encountered. All the regions of Latvia can be compared by collected data.

Not relevant

Possible limitations in the use of data for comparisons over time: Not relevant.

The length of comparable time series depends on the module and variable considered within each of the modules of the survey.

Not applicable

Not applicable

Not applicable

All statistics are coherent within the dataset.

MANDATORY questions in the Eurostat model questionnaire 2022: All the mandatory questions were included in model questionnaire with no deviations from Eurostat’s version of model questionnaire.

The table in the annex "INFOSOC_HHNSI_A_2022_an1_LV" lists the questions that do not reflect the coverage of subjects and characteristics of Annex 2 of the Commission Delegated Regulation (EU) 2021/1898 of the 20 July 2021. 

Adoption of OPTIONAL questions and items in the Eurostat model questionnaire 2022:

The optional questions included in model questionnaire are: B3n, C7d, C8c, C8d, F2, G8, G9, G13 (all the territory of Latvia is considered NUTS2 region). 

The table in the annex lists the optional questions from the annual Eurostat model questionnaire 2022 included in the national questionnaire and their coverage for age groups beyond the standard scope. 

Additional questions introduced in the national questionnaire: No additional questions were included in model questionnaire.

Effects of deviations from the routing used in the Eurostat model questionnaire: No deviations from the routing used in the Eurostat model questionnaire.

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.

No data revision to report.

Not relevant

The source of the raw data is described with more details in the paragraphs below.

The sampling frame covered all persons aged 16-74 inclusive, who were permanent residents in private households of the Republic of Latvia at the start of the sample making process. The sampling frame was made using automate tool, created by the CSB, which combines information according to the definition of target population from various registers (i.e. Register of Natural Persons, National address register, short-term residence permits),  and additional sources.

For sampling frame used the information of October, which was the newest available information during sampling. The sample was independent and survey was voluntary.

2022 ICT survey was “stand alone survey” and was not embedded in any other social surveys.

The sampling design for the ICT 2022 survey was a stratified two stage sampling with territorial variable (Riga {capital city}, 9 largest cities, other cities and rural areas) in combination with statistical regions (NUTS3 level) used as a stratification variable (16 strata in total) For respondents with unknown territorial variable, another 6 stratas were added (combination of statistical regions). To reduce the costs of the fieldwork and to facilitate the data collection process, the first stage of selection involved selection of survey polygon areas with probabilities proportional to size. A systematic random sampling was used at the first stage and was also used an implicit stratification by serpentine order.

The second stage of selection involved selection of individuals, aged 16-74, using systematic random sampling. Before selection, the units were sorted by age, thus providing implicit stratification by age in the second stage.

For the allocation of units in strata, well-known Neyman optimal allocation approach was used.

Annual

1) Methods used to gather data:

Data was gathered using CAWI, CATI and CAPI methods.

2) Short description of the survey method:

Overall 5815 interviews were collected, using two data gathering methods:

• a) Web survey (CAWI) from which 488 interviews (8,4% of achieved interviews) were collected.
• b) Telephone interviews (CATI) from which 5309 interviews (91,3 % of achieved interviews) were collected.
• c) Face to face interviews (CAPI) from which 18 interviews (0,3% 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.

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 can’t 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.

Information about imputation and grossing procedures are described in paragraphs below.

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 question D1 of the 2022 model questionnaire):

Imputation rate (% of observations): 0%

Imputation rate (share of estimate): 0%

Methods used to impute item non-response: Hot-deck.

Grossing up procedures have been applied to: 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 municipality (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).

Not relevant

Not relevant

No other comments.