1.1. Contact organisation
Statistics Estonia
1.2. Contact organisation unit
Economic and Environmental Statistics Department
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
Tatari 51, 10134 Tallinn, Estonia
1.6. Contact email address
Confidential because of GDPR
1.7. Contact phone number
Confidential because of GDPR
1.8. Contact fax number
Confidential because of GDPR
2.1. Metadata last certified
17 May 2024
2.2. Metadata last posted
12 June 2024
2.3. Metadata last update
12 June 2024
3.1. Data description
The Community Innovation Survey (CIS) is a survey about innovation activities in enterprises. The survey is designed to collect the information on types of innovation, processes of development of innovation like cooperation patterns, financing and expenditure, objectives of innovation activities or barriers for initiating or implementing innovation.
The CIS provides statistics by type of innovators, economic activity and size class of enterprises. The survey is currently carried out every two years across the EU Member States, EFTA countries and EU candidate countries.
In order to ensure comparability across countries, Eurostat together with the countries develops a Harmonised Data Collection (HDC) questionnaire and drafts the methodological recommendations for implementation of each survey round.
The CIS 2022 implements the concepts and methodology of the Oslo Manual 4th Edition revised in 2018. The changes that the CIS has undergone due to the revision of the manual and their impact on the indicators collected are described in the Statistics Explained article: Community Innovation Survey – new features.
The legal framework for CIS 2022 is the Commission Implementing Regulation (EU) 2022/1092, which sets out the quality conditions and identifies the obligatory cross-coverage of economic sectors, size class of enterprises and innovation indicators. The target population is enterprises with at least 10 employed persons (sum of employees and self-employed persons) classified in the core NACE economic sectors (see 3.3). Further activities may be covered on a voluntary basis in national datasets. Most statistics are based on the 3-year reference period (t, t-1, t-2), but some use only one calendar year (t or t-2).
3.2. Classification system
Indicators related to the enterprises are classified by country, economic activity (NACE Rev. 2), size class of enterprises and type of innovation.
The main typology of classification of enterprises in reference to innovation is the distinction between innovation-active enterprises (INN) and not innovation-active enterprises (NINN).
The enterprise is considered as innovative (INN) if during the reference period it successfully introduced a a) product or a) business process innovation, c) completed but not yet implemented the innovation, d) had ongoing innovation activities, e) abandoned innovation activities or was f) engaged in in-house R&D or R&D contracted out. Non-innovative (NINN) enterprises had no innovation activity mentioned above whatsoever during the reference period.
3.3. Coverage - sector
CIS covers main economic sectors according to NACE Rev.2 broken down by size class of enterprises and type of
innovation activity.
3.3.1. Main economic sectors covered - NACE Rev.2
In accordance with the Commission Implementing Regulation (EU) 2022/1092 on innovation statistics, the following sectors of the economic activity are included in the core target population: NACE Sections B, C, D, E, H, J, K, and Divisions 46, 71, 72 and 73.
3.3.1.1. Main economic sectors covered - NACE Rev.2 - national particularities
All core activities were covered.
No non-core activities were covered.
3.3.2. Sector coverage - size class
In accordance with Commission Implementing Regulation (EU) 2022/1092 on innovation statistics, only the enterprises with 10 or more employed persons (sum of employees and self-employed persons) are included in the core target population.
3.3.2.1. Sector coverage - size class - national particularities
In sampling the following size classes of enterprises according to number person employed are included:
- 10–49
- 50–99
- 100–249
- 250+
The same size classes are used for nationally published results.
3.4. Statistical concepts and definitions
The description of concepts, definitions and main statistical variables will be available in CIS 2022 European metadata file (ESMS) Results of the community innovation survey 2022 (CIS2022) (inn_cis13) in Eurostat database.
3.5. Statistical unit
Statistical unit is enterprise.
The observation unit is the enterprise.
3.6. Statistical population
Core target population is all enterprises in CORE NACE activities (see 3.3.1) with 10 or more employed persons (sum of employees and self-employed persons).
3.7. Reference area
All territory of Estonia is covered.
Estonia is at NUTS 2 level.
3.8. Coverage - Time
Several rounds of Community Innovation Survey have been conducted so far at two-year interval since the end of the 90’s.
3.8.1. Participation in the CIS waves
| CIS wave | Reference period | Participation (Yes/No) | Comment (deviation from reference period) |
|---|---|---|---|
| CIS2 | 1994-1996 | No | |
| CIS3 | 1998-2000 | Yes | |
| CIS light | 2002-2003* | No | |
| CIS4 | 2002-2004 | Yes |
|
| CIS2006 | 2004-2006 | Yes | |
| CIS2008 | 2006-2008 | Yes | |
| CIS2010 | 2008-2010 | Yes | |
| CIS2012 | 2010-2012 | Yes | |
| CIS2014 | 2012-2014 | Yes | |
| CIS2016 | 2014-2016 | Yes | |
| CIS2018 | 2016-2018 | Yes | |
| CIS2020 | 2018-2020 | Yes | |
| CIS2022 | 2020-2022 | Yes |
*two reference periods can be distinguished for CIS light: 2000-2002 and 2001-2003
3.9. Base period
Not relevant.
CIS indicators are available according to 3 units of measure:
NR: Number for number of enterprises and number of persons employed.
THS_EUR: Thousands of euros. All financial variables are provided in thousands of euros, i.e. Turnover or Innovation expenditure.
PC: Percentage. The percentage is the ratio between the selected combinations of indicators.
For CIS 2022, the time covered by the survey is the 3-year period from the beginning of 2020 to the end of 2022.
Some questions and indicators refer to one year — 2022.
The list of indicators specifying whether they cover the 3-year period or refer to one year according to the HDC will be available in the Annex section of the European metadata (ESMS).
6.1. Institutional Mandate - legal acts and other agreements
The CIS is based on the Commission Implementing Regulation (EU) 2022/1092, implementing Regulation (EU) 2019/2152 of the European Parliament and of the Council on the production and development of Community statistics on science and technology.
This Regulation establishes innovation statistics on a statutory basis and makes the delivery of certain variables compulsory e.g. innovation activities, cooperation, development, expenditures and turnover (see the Regulation). Each survey wave may additionally include further variables.
In addition, the Regulation defines the obligatory cross-coverage of economic sectors and size class of enterprises.
6.1.1. National legislation
No national legislations.
6.2. Institutional Mandate - data sharing
Not requested.
7.1. Confidentiality - policy
The dissemination of data collected for the purpose of producing official statistics is guided by the requirements
provided for in § 32, § 34, § 35, § 38 of the Official Statistics Act.
The treatment of confidential data is regulated by the Procedure for Protection of Data Collected and Processed by
Annexes:
Official Statistics Act
7.2. Confidentiality - data treatment
Primary cell suppression were used for financial indicators if there were less than 3 enterprises in the respective
NACE activity and size group or if the share of one enterprise was more than 90%.
In addition to primary cell suppression, secondary cell suppression was applied to protect primary cell suppressionl
values from calculation.
8.1. Release calendar
Notifications about the dissemination of statistics are published in the release calendar, which is available on the website. Every year on 1 October, the release times of the statistical database, news releases, main indicators by IMF SDDS and publications for the following year are announced in the release calendar (in the case of publications – the release month).
8.2. Release calendar access
Release Calendar.
Annexes:
Release Calendar
8.3. Release policy - user access
All users have been granted equal access to official statistics: dissemination dates of official statistics are announced in advance and no user category (incl. Eurostat, state authorities and mass media) is provided access to official statistics before other users. Official statistics are first published in the statistical database. If there is also a news release, it is published simultaneously with data in the statistical database. Official statistics are available on the website at 8:00 a.m. on the date announced in the release calendar.
CIS is conducted and disseminated at two-year interval in pair years.
Accessibility and clarity refer to the simplicity and ease for users to access statistics using simple and user-friendly procedure, obtaining them in an expected form and within an acceptable time period, with the appropriate user information and assistance: a global context which finally enables them to make optimum use of the statistics.
10.1. Dissemination format - News release
See below.
10.1.1. Availability of the releases
| Dissemination and access | Availability | Comments, links, ... |
|---|---|---|
| Press release | Yes | |
| Access to public free of charge | Yes | |
| Access to public restricted (membership/password/part of data provided, etc) | No |
Annexes:
National innovation statistics news (in Estonian)
Database
10.2. Dissemination format - Publications
- Online database (containing all/most results): containing all.
- Analytical publication (referring to all/most results): most results.
- Analytical publication (referring to specific results, e.g. only for one sector or one specific aspect): some graphs and key drawings and all information have been published on the Statistics by Theme.
10.3. Dissemination format - online database
Online database is available.
Annexes:
Database
10.3.1. Data tables - consultations
Not requested.
10.4. Dissemination format - microdata access
.
10.4.1. Dissemination of microdata
| Mean of dissemination | Availability of microdata | Comments, links, ... |
|---|---|---|
| Eurostat SAFE centre | Yes | |
| National SAFE centre | Yes | |
| Eurostat: partially anonymised data (SUF) | ||
| National: partially anonymised data |
10.5. Dissemination format - other
No other means of dissemination.
10.5.1. Metadata - consultations
Not requested.
10.6. Documentation on methodology
ESMS Matadata information is available.
Annexes:
ESMS metadata
10.6.1. Metadata completeness - rate
Not requested.
10.7. Quality management - documentation
There is no special quality documents available.
11.1. Quality assurance
To assure the quality of processes and products, Statistics Estonia applies the EFQM Excellence Model, the European Statistics Code of Practice and the Quality Assurance Framework of the European Statistical System (ESS QAF). Statistics Estonia is also guided by the requirements in § 7. “Principles and quality criteria of producing official statistics” of the Official Statistics Act.
11.2. Quality management - assessment
Statistics Estonia performs all statistical activities according to an international model (Generic Statistical Business Process Model – GSBPM). According to the GSBPM, the final phase of statistical activities is overall evaluationmusing information gathered in each phase or sub-process; this information can take many forms, including feedback from users, process metadata, system metrics and suggestions from employees. This information is used to prepare the evaluation report which outlines all the quality problems related to the specific statistical activity and serves as input for improvement actions.
12.1. Relevance - User Needs
Since 1996 the Statistical Office conducts reputation surveys and user surveys. The survey is conducted at least once a year, the existing as well as potential consumers are interviewed.
- to find out the reputation of the Statistical Office among consumers,
- to find out the need for statistical information,
- to study the consumers’ preferences in using various statistical products,
- to get the necessary information for production development.
The results of the surveys are applied for better serving the consumers, as well as in improvement of products. Information on the user surveys results can be found on the website.
user-surveys.
Proposals from stakeholders and users are negotiated to specify the need for data and the possibility their inclusion inthe survey. When additional questions are included in the survey, a contract is concluded with the stakeholders, which determines the needs, feasibility and publication of the results.
12.1.1. Needs at national level
| User group | Short description of user group | Main needs for CIS data of the user group Users’ needs |
|---|---|---|
| Institutions - Europeanlevel |
The European
Commission (DG
ENTR)
|
Innovation Union
Scoreboard
|
| Institutions - Europeanlevel | Eurostat |
To produce innovation STI
statistics and make
microdata available for
researchers
|
| Institutions - Nationallevel |
Ministry of
Ecconomuic Affairs
and Communications
|
To work out STI strategy
and politics
|
| Institutions - Nationallevel | Statistics Estonia |
To produce STI statistics
and make micro-data
available for researchers
|
| Social actors |
Governmental
Foundations connected
with STI
|
To take decisions when
financing STI
|
| Institutions - Regional level | Local goverrnments | To evaluate local situation in innovation |
| Institutions - International Organisations | OECD, IMF | To evaluate Estonian position and trends in respect to STI |
| Social actors | Employers’ associations | For sector and international comparisons |
| Media | Newspapers, TV and radio channels | To comment the situation to general public |
| Enterprises or businesses | Enterprises | Market analysis, investment analysis, possibility to create subsidiaries |
| Researchers and students | Researches | To analyse the field of S&T&I and have access to the micro-data to make specific research |
12.2. Relevance - User Satisfaction
Since 1996, Statistics Estonia has conducted reputation and user satisfaction surveys.
Annexes:
User satisfactory surveys
12.3. Completeness
All mandatory indicators were included to survey questionnaire and all data was sent to Eurostat.
12.3.1. Data completeness - rate
Not requested.
13.1. Accuracy - overall
Accuracy in the statistical sense denotes the closeness of computations or estimates to the exact or true values. Statistics are not equal with the true values because of variability (the statistics change from implementation to implementation of the survey due to random effects) and bias (the average of the possible values of the statistics from implementation to implementation is not equal to the true value due to systematic effects).
13.2. Sampling error
Restricted from publication
13.2.1. Sampling error - indicators
The main indicator used to measure sampling errors for CIS data is the coefficient of variation (CV).
CV= Coefficient of variation (%) = 100 * (Square root of the estimate of the sampling variance) / (Estimated value)
Formula:
where
and
13.2.1.1. Coefficient of variations for key variables
Coefficient of variation (%) for key variables by NACE categories and for enterprises with 10 or more employed persons
| NACE |
Size class |
(1) |
(2) |
(3) |
| Core NACE (B-C-D-E-46-H-J-K-71-72-73) |
Total |
2.04 |
4.03 |
2.75 |
| Core industry (B_C_D_E - excluding construction) |
Total |
2.78 |
6.95 |
3.62 |
| Core Services (46-H-J-K-71-72-73) |
Total |
3.01 |
3.33 |
4.19 |
(1) = Coefficient of variation for the percentage of innovative enterprises (INN) in the total population of enterprises (ENT)
(2) = Coefficient of variation for the turnover of product innovative enterprises with new or improved products (TUR_PRD_NEW_MKT), as a percentage of total turnover of product innovative enterprises [TOVT,INNO_PRD].
(3) = Coefficient of variation for percentage of product and/or process innovative enterprises (incl. enterprises with abandoned and or on-going activities) involved in any innovation co-operation arrangement [COOP_ALL,INN], as a percentage of innovative enterprises (INN).
13.2.1.2. Variance estimation method
For variance estimation the Taylor series linearization method is used.
13.3. Non-sampling error
Non-sampling errors occur in all phases of a survey. They add to the sampling errors (if present) and contribute to decreasing overall accuracy. It is important to assess their relative weight in the total error and devote appropriate resources for their control and assessment.
13.3.1. Coverage error
Coverage errors (or frame errors) are due to divergences between the target population and the frame population. The frame population is the set of target population members that have a chance to be selected into the survey sample. It is a listing of all items in the population from which the sample is drawn that contains contact details as well as sufficient information to perform stratification and sampling.
13.3.1.1. Over-coverage - rate
Not requested.
13.3.1.2. Common units - proportion
Not requested.
13.3.1.3. Under covered groups of the target population
Updated business register of Estonian economic units do not allow undercoverage
13.3.1.4. Coverage errors in coefficient variation
Not applicable
13.3.2. Measurement error
Measurement errors occur during data collection and generate bias by recording values different than the true ones. The survey questionnaire used for data collection may have led to the recording of wrong values, or there may be respondent or interviewer bias.
13.3.2.1. Measures for reducing measurement errors
More complex questions in CIS 2022 questionnaire were tested on selected enterprises before the questionnaire was opened for filling. The wording was improved on the basis of the information provided. An on-line questionnaire in eSTAT was used to collect the data. Questions were displayed as question blocks or tabs. If a question was not answered, a warning message appeared immediately and the respondent could not allowed to proceed to the next question. The questionnaire cannot be approved until the questions have been answered. Unfortunately, there were still some questionnaires that were not approved. These enterprises were contacted by telephone and additional information was provided as far as possible.
13.3.3. Non response error
Non response occurs when a survey fails to collect data on all survey variables from all the population units designated for data collection in a sample or complete enumeration.
There are two types of non-response:
1) Unit non-response, which occurs when no data (or so little as to be unusable) are collected about a population unit designated for data collection.
a) Un-weighted unit non-response rate (%) = 100*(Number of units with no response or not usable response) / (Total number of in-scope (eligible) units in the sample)
b) Weighted unit non-response rate (%) = 100*(Number of weighted units with no response or not usable response) / (Total number of in-scope (eligible) units in the sample)
2) Item non-response, which occurs when only data on some, but not all survey data items are collected about a population unit designated for data collection.
a) Un-weighted item non-response rate (%) = 100*(Number of units with no response at all for the item) / (Total number of eligible, for the item, units in the sample i.e. filters have to be taken into account)
The unweighted non-response rate was
13.3.3.1. Unit non-response - rate
See below.
13.3.3.1.1. Un-weighted and weighted unit non-response rate by NACE categories and for enterprises with 10 or more employed persons
Un-weighted and weighted unit non-response rate by NACE categories and for enterprises with 10 or more employed persons
| NACE | Number of eligible units with no response | Total number of eligible units in the sample | Un-weighted unit non-response rate (%) | Weighted unit non-response rate (%) |
| Core NACE (B-C-D-E-46-H-J-K-71-72-73) | 318 | 2100 | 15.14 | 19.24 |
| Core industry (B_C_D_E - excluding construction) | 148 | 1047 | 14.14 | 18.93 |
| Core Services (46-H-J-K-71-72-73) | 170 | 1053 | 16.14 | 19.56 |
The number of eligible units is the number of sample units, that ultimately indeed belong to the target population.
13.3.3.1.2. Maximum number of recalls/reminders before coding
The first information letter was sent to sampled enterprises at the beginning of 2023. The second letter was sent just before the deadline of the survey on August 2023. During the collection period, five reminder letters were sent to non-responded units.
13.3.3.2. Item non-response - rate
See below.
13.3.3.2.1. Item non-response rate for Turnover (in Core NACE: B-C-D-E-46-H-J-K-71-72-73 enterprises with 10 or more employed persons)
Item non-response rate for Turnover (in Core NACE: B-C-D-E-46-H-J-K-71-72-73 enterprises with 10 or more employed persons).
| Item non-response rate (un-weighted) (%) |
Imputation (Yes/No) |
If imputed, describe method used, mentioning which auxiliary information or stratification is used | |
| Turnover | 0% | No |
13.3.3.2.2. Item non response rate for new questions
Item non-response rate for new questions in CIS t (in Core NACE: B-C-D-E-46-H-J-K-71-72-73 enterprises with 10 or more employed persons)
| NEW QUESTIONS IN CIS 2022 | Inclusion in national questionnaire (Yes/No) | Item non response rate (un-weighted) (%) | Comments |
| 3.9 -- Reasons for not having more innovation activities | Yes | 0% | Mandatory question, no imputation |
| 3.10 -- Reasons for having no innovation activities | Yes | 0% | Mandatory question, no imputation |
13.3.4. Processing error
Research and development expenditures were compared the data with the RD survey, if there were differences in the data, the respondent was contacted. The differences may have been due to the fact that the respondents were different persons.
13.3.5. Model assumption error
Not requested.
Timeliness and punctuality refer to time and dates, but in a different manner.
14.1. Timeliness
The timeliness of statistics reflects the length of time between data availability and the event or phenomenon they describe.
14.1.1. Time lag - first result
Timeliness of national data – date of first release of national level: 20 May 2024
14.1.2. Time lag - final result
Not requested.
14.2. Punctuality
Punctuality refers to the time lag between the release date of data and the target date on which they were scheduled for release as announced officially.
14.2.1. Punctuality - delivery and publication
Date of transmission of complete and validated data to Eurostat (Number of days between that date and 30 June 2024) : 42
Comparability aims at measuring the impact of differences in applied statistical concepts and definitions on the comparison of statistics between geographical areas, non-geographical domains, or over time.
The coherence of statistical outputs refers to the degree to which the statistical processes by which they were generated used the same concepts (classifications, definitions, and target populations) and harmonised methods. Coherent statistical outputs have the potential to be validly combined and used jointly.
15.1. Comparability - geographical
The data is comparable with countries which collect data based on the common OECD methodology, which is also used by Eurostat. Calculation of enterprise innovation indicators is based on OECD methodology (Oslo Manual), which ensures coherence, comparability over time and across countries. OECD methodology is also used by Eurostat.
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not requested.
15.1.2. National questionnaire – compliance with Eurostat model questionnaire
Methodological deviations from the CIS Harmonised Data Collection (HDC)
| Questions not included in national questionnaire compared to HDC | Comment |
|---|---|
| question 7.1 'Number of persons employed' | The number of persons |
| question 7.2 'Number of persons employed |
There was used used linking of |
| question 7.3 'Total turnover' | The total turnover was taken |
| question 7.5 'Age of enterprise' | The age of the enterprise was |
| question 4.3 'Tax incentives' | There were no innovation related tax incentives available in Estonia. |
| question 5.2 'Purchase of machinery, equipment orsoftware' | |
| question 5.3 'Goods or services to meet users requirements' | |
| question 5.4 'Fundamental changes to business model' | |
| question 7.4 'Percentage of turnover' | |
| question 7.6 'Spendings' | |
| question 7.7 'Enterprise group' | Data was taken from Statistical Business Register (SPI). |
| question 7.8 'Activities in enterprise group' | |
| question 7.9 'Intra-group loans' |
| Changes in the filtering compared to HDC | Comment |
|---|---|
| question 3.1 'Introduction of innovative |
The question was split in two |
15.1.3. National questionnaire – additional questions
Methodological deviations from the CIS Harmonised Data Collection (HDC)
| Additional questions in national questionnaire (not included in HDC) | Comment |
| no additional questions | |
15.2. Comparability - over time
Due to important methodological changes introduced by Oslo Manual 2018, the data from 2018 onwards cannot be directly compared with CIS waves prior to 2018.
15.2.1. Length of comparable time series
Not requested.
15.3. Coherence - cross domain
See the comparison between SBS and CIS data in the section 15.3.3 below.
15.3.1. Coherence - sub annual and annual statistics
Not requested.
15.3.2. Coherence - National Accounts
Not requested.
15.3.3. Coherence – Structural Business Statistics (SBS)
This part compares key variables for aggregated CIS data with SBS data
Definition of relative difference between CIS and SBS data: DIFF = (SBS/CIS)*100
Comparison between SBS and CIS data (relative difference) by NACE categories and for enterprises with 10 or more employed persons
| NACE | Size class | Number of enterprises (SBS/CIS)* | Number of employed persons (SBS/CIS)* | Total Turnover (SBS/CIS)* |
| Core NACE (B-C-D-E-46-H-J-K-71-72-73) | Total | 95.75 | 90.27 | 89.56 |
| Core industry (B_C_D_E - excluding construction) | Total | 96.86 | 94.64 | 89.56 |
| Core Services (46-H-J-K-71-72-73) | Total | 94.63 | 84.64 | 89.56 |
* Numbers are to be provided for the last year of the reference period (t)
15.4. Coherence - internal
Not requested.
17.1. Data revision - policy
Not requested.
17.2. Data revision - practice
Not requested.
17.2.1. Data revision - average size
Not requested.
18.1. Source data
See below.
18.1.1. Sampling frame (or census frame)
Stratified simple random sampling by economic activity and size class of the enterprise was used.
Updated business register of Estonian economic units was used as a sampling frame.
18.1.2. Sampling design
The stratified simple random sampling method was used. The frame was stratified by economic activity (NACE Rev2.
2-digit level) and number of persons employed. By number of persons employed enterprises were divided into following size groups: 10-49, 50-249 and 250+.
The Neyman optimal allocation was used for sample allocation and determination of sample size in strata.
Sampling was used for enterprises 10 to 49 persons employed, enterprises with 50 and more persons employed were suveyed totally.
18.1.3. Target population and sample size
| Sample/census indicator | Number of enterprises |
| Target population (A) (*) | 3859 |
| Sample (B = C+D) | 2100 |
| In case of combination sample/census: | |
| Sampled units (C) | 1434 |
| Enumerated units/census (D) | 666 |
| Overall sample rate (E = 100*B/A) | 54.4% |
(*) CIS core population, i.e. NACE Rev.2 B-C-D-E-46-H-J-K-71-72-73 enterprises with 10 or more employed persons.
18.1.4. Data source for pre-filled variables
Variables and indicators filled or prefilled from other sources.
| Variables/Indicators | Source | Reference year |
|---|---|---|
| R&D expenditure | R&D survey | 2022 |
| Patent / industrial design right / trademark | Patent Office | 2020-2022 |
18.1.5. Data source and variables used for derivation and weighting
| Item | Response |
| Data source used for deriving population totals | register of economically active enterprises maintained in Statistics Estonia. |
| Variables used for weighting | population totals counted from the register and broken down by strata and number of reported units in the strata |
18.2. Frequency of data collection
According to the Commission Implementing Regulation (EU) 2022/1092, the innovation statistics shall be provided to Eurostat every two years in each even year. The data collection takes place every second year in year t-2 preceding the data provision.
18.3. Data collection
Data is collected and the submission of questionnaires is monitored through the web channel for electronic data submission. The questionnaires have been designed for independent completion and include instructions and controls.
The questionnaires and information about data submission are available on Statistics Estonia’s website in Estonian language.
Data is collected with the statistical questionnaire “Enterprises innovation survey”.
18.3.1. Survey participation
The survey is mandatory.
18.3.2. Survey type
Combination of sample and census.
The part of the target population containing units with less than 50 employees was stratified into staratas with respect to the main activity and number of employees.
Enterprises with number of employees more than 50 were investigated totally.
18.3.3. Combination of sample survey and census data
The part of the target population containing units with less than 50 employees was stratified into staratas with respect to the main activity and number of employees.
18.3.4. Census criteria
All enterprises with number of employees more than 50 were investigated.
18.3.5. Data collection method
Data collection method
| Survey method | Yes/No | Comment |
|---|---|---|
| Face-to-face interview | No | |
| Telephone interview | Yes | to a small extent |
| Postal questionnaire | No | |
| Electronic questionnaire (format Word or PDF to send back by email) | Yes | to a small extent |
| Web survey (online survey available on the platform via URL) | Yes | most common |
| Other | No |
18.4. Data validation
Not requested.
18.5. Data compilation
Operations performed on data to derive new information according to a given set of rules.
18.5.1. Imputation - rate
Imputation is the method of creating plausible (but artificial) substitute values for all those missing.
Definition of imputation rate:
Imputation rate (for the variable x) (%) = 100 * (Number of replaced values) / (Total number of values for a given variable)
Definition of weighted imputation rate:
Weighted imputation rate= 100 * (Number of total weighted replaced values) / (Total number of weighted values for a given variable)
18.5.1.1. Imputation rate for metric variables
Imputation rate (%) for metric variables by NACE categories and for enterprises with 10 or more employed persons: Imputation was not carried on for these variables.
| NACE | Size class | Total Turnover (1) | Turnover from products new to the market (2) | R&D expenditure in-house (3) | |||
| Unweighted | Weighted | Unweighted | Weighted | Unweighted | Weighted | ||
| Core NACE (B-C-D-E-46-H-J-K-71-72-73) | Total | 0% | 0% | 0% | 0% | 0% | 0% |
| Core industry (B_C_D_E - excluding construction) | Total | 0% | 0% | 0% | 0% | 0% | 0% |
| Core Services (46-H-J-K-71-72-73) | Total | 0% | 0% | 0% | 0% | 0% | 0% |
(1) = Imputation rate (%) for the total turnover in the last year of the reference period (t) (TUR)
(2) = Imputation rate (%) for the share of the turnover in the last year of the reference period (t) due to new or improved product new to the market in the total turnover for product innovative enterprises TUR_PRD_NEW_MKT/TOVT(INNO_PRD)
(3) = Imputation rate (%) for the R&D expenditure performed in-house (EXP_INNO_RND_IH)
18.5.2. Weights calculation
Weights calculation method for sample surveys
| Method | Selected applied method | Comments |
|---|---|---|
| Inverse sampling fraction | ||
| Non-respondent adjustments | ||
| Other |
x
|
For calculation weights population totals counted from the register and broken down by strata and number of reported units in the strata are used. |
18.6. Adjustment
Not applicable.
18.6.1. Seasonal adjustment
Not requested.
The Community Innovation Survey (CIS) is a survey about innovation activities in enterprises. The survey is designed to collect the information on types of innovation, processes of development of innovation like cooperation patterns, financing and expenditure, objectives of innovation activities or barriers for initiating or implementing innovation.
The CIS provides statistics by type of innovators, economic activity and size class of enterprises. The survey is currently carried out every two years across the EU Member States, EFTA countries and EU candidate countries.
In order to ensure comparability across countries, Eurostat together with the countries develops a Harmonised Data Collection (HDC) questionnaire and drafts the methodological recommendations for implementation of each survey round.
The CIS 2022 implements the concepts and methodology of the Oslo Manual 4th Edition revised in 2018. The changes that the CIS has undergone due to the revision of the manual and their impact on the indicators collected are described in the Statistics Explained article: Community Innovation Survey – new features.
The legal framework for CIS 2022 is the Commission Implementing Regulation (EU) 2022/1092, which sets out the quality conditions and identifies the obligatory cross-coverage of economic sectors, size class of enterprises and innovation indicators. The target population is enterprises with at least 10 employed persons (sum of employees and self-employed persons) classified in the core NACE economic sectors (see 3.3). Further activities may be covered on a voluntary basis in national datasets. Most statistics are based on the 3-year reference period (t, t-1, t-2), but some use only one calendar year (t or t-2).
12 June 2024
The description of concepts, definitions and main statistical variables will be available in CIS 2022 European metadata file (ESMS) Results of the community innovation survey 2022 (CIS2022) (inn_cis13) in Eurostat database.
Statistical unit is enterprise.
The observation unit is the enterprise.
Core target population is all enterprises in CORE NACE activities (see 3.3.1) with 10 or more employed persons (sum of employees and self-employed persons).
All territory of Estonia is covered.
Estonia is at NUTS 2 level.
For CIS 2022, the time covered by the survey is the 3-year period from the beginning of 2020 to the end of 2022.
Some questions and indicators refer to one year — 2022.
The list of indicators specifying whether they cover the 3-year period or refer to one year according to the HDC will be available in the Annex section of the European metadata (ESMS).
Accuracy in the statistical sense denotes the closeness of computations or estimates to the exact or true values. Statistics are not equal with the true values because of variability (the statistics change from implementation to implementation of the survey due to random effects) and bias (the average of the possible values of the statistics from implementation to implementation is not equal to the true value due to systematic effects).
CIS indicators are available according to 3 units of measure:
NR: Number for number of enterprises and number of persons employed.
THS_EUR: Thousands of euros. All financial variables are provided in thousands of euros, i.e. Turnover or Innovation expenditure.
PC: Percentage. The percentage is the ratio between the selected combinations of indicators.
Operations performed on data to derive new information according to a given set of rules.
See below.
CIS is conducted and disseminated at two-year interval in pair years.
The timeliness of statistics reflects the length of time between data availability and the event or phenomenon they describe.
The data is comparable with countries which collect data based on the common OECD methodology, which is also used by Eurostat. Calculation of enterprise innovation indicators is based on OECD methodology (Oslo Manual), which ensures coherence, comparability over time and across countries. OECD methodology is also used by Eurostat.
Due to important methodological changes introduced by Oslo Manual 2018, the data from 2018 onwards cannot be directly compared with CIS waves prior to 2018.
