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For any question on data and metadata, please contact: Eurostat user support |
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1.1. Contact organisation | Statistics Estonia |
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1.2. Contact organisation unit | Enterprise and Agricultural Statistics Department |
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1.5. Contact mail address | Tatari 51, 10134 Tallinn, Estonia |
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2.1. Metadata last certified | 01/07/2021 | ||
2.2. Metadata last posted | 01/07/2021 | ||
2.3. Metadata last update | 01/07/2021 |
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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 different types of innovation, various aspects of the development of an innovation, objectives of innovation activities, sources of information, public funding or expenditure on innovation. It is aim is to measure the innovativeness of sectors and enable the analysis of the factors of innovation. The CIS provides statistics by type of innovators, economic activities 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 developed a Harmonised Data Collection (HDC) questionnaire accompanied by a set of definitions and methodological recommendations.
CIS 2018 concepts and its underlying methodology are based on the Oslo Manual (2018) 4th Edition.
New review of the CIS2018 aims to meet several objectives : 1: Reduce subjectivity and biases in the main CIS indicators 2: Improve reporting about innovation activities and capabilities in the firm 3: Ensure international comparability (including compliance with the OM4) 4: Broaden the basis CIS information on enterprise management 5: Take better account the diversity of enterprises in the EU 6: Improve reporting about external drivers and enablers of innovation 7: Improve timeliness 8: Ensure the feasibility of data collection 9: Ensure continuity with the CIS 2016 10: Improve reporting about the output and impact of innovation
CIS2018 is conducted under Commission Regulation No 995/2012. This Regulation defines the mandatory target population of the survey referring to enterprises in the Core NACE economic sectors (see section 3.3.) with at least 10 employees. 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).
Please consider CIS t to be the survey that refers to the same year of the quality report and CIS t-2 to be the previous survey e.g.: CIS 2018= CIS t then, CIS t-2=CIS 2016 |
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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 product or business process innovation, had ongoing innovation activities, abandoned innovation activities or was 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. |
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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. |
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3.3.1. Main economic sectors covered - NACE Rev.2 | ||||||||||||||||||||||||||||||||||||||||||||||||
In accordance with Commission Regulation 995/2012 on innovation statistics, the following industries and services are included in the core target population. Results are made available with these following breakdowns : All NACE – Core NACE (NACE Rev. 2 sections & divisions B-C-D-E-46-H-J-K-71-72-73 )
CORE INDUSTRY (excluding construction) (NACE Rev. 2 SECTIONS B_C_D_E) 10-12: Manufacture of food products, beverages and tobacco 13-15: Manufacture of textiles, wearing apparel, leather and related products 16-18: Manufacture of wood, paper, printing and reproduction 20: Manufacture of chemicals and chemical products 21: Manufacture of basic pharmaceutical products and pharmaceutical preparations 19-22: Manufacture of petroleum, chemical, pharmaceutical, rubber and plastic products 23: Manufacture of other non-metallic mineral products 24: Manufacture of basic metals 25: Manufacture of fabricated metal products, except machinery and equipment 26: Manufacture of computer, electronic and optical products 25-30: Manufacture of fabricated metal products (except machinery and equipment), computer, electronic and optical products, electrical equipment, motor vehicles and other transport equipment 31-33: Manufacture of furniture; jewellery, musical instruments, toys; repair and installation of machinery and equipment
D: ELECTRICITY, GAS, STEAM AND AIR CONDITIONING SUPPLY
E: WATER SUPPLY; SEWERAGE, WASTE MANAGEMENT AND REMEDIATION ACTIVITIES 36: Water collection, treatment and supply 37-39: Sewerage, waste management, remediation activities
CORE SERVICES (NACE Rev. 2 sections & divisions 46-H-J-K-71-72-73)(NACE code in the tables = G46-M73_INN) 46: Wholesale trade, except of motor vehicles and motorcycles
H: TRANSPORTATION AND STORAGE 49-51: Land transport and transport via pipelines, water transport and air transport 52-53: Warehousing and support activities for transportation and postal and courier activities
J: INFORMATION AND COMMUNICATION 58: Publishing activities 61: Telecommunications 62: Computer programming, consultancy and related activities 63: Information service activities
K: FINANCIAL AND INSURANCE ACTIVITIES 64: Financial service activities, except insurance and pension funding 65: Insurance, reinsurance and pension funding, except compulsory social security 66: Activities auxiliary to financial services and insurance activities
M: PROFESSIONAL, SCIENTIFIC AND TECHNICAL ACTIVITIES 71: Architectural and engineering activities; technical testing and analysis 72: Scientific research and development 73: Advertising and market research 71-73: Architectural and engineering activities; technical testing and analysis; Scientific research and development; Advertising and market research
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3.3.1.1. Main economic sectors covered - NACE Rev.2 - national particularities | ||||||||||||||||||||||||||||||||||||||||||||||||
All core activities were covered. No non-core activities were covered. |
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3.3.2. Sector coverage - size class | ||||||||||||||||||||||||||||||||||||||||||||||||
In accordance with Commission Regulation 995/2012 on innovation statistics, the following size classes of enterprises according to number of employees are included in the core target population of the CIS:
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3.3.2.1. Sector coverage - size class - national particularities | ||||||||||||||||||||||||||||||||||||||||||||||||
In sampling the following size classes of enterprises according to number of employees are included
The same size classes are used for nationally published results. |
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3.4. Statistical concepts and definitions | ||||||||||||||||||||||||||||||||||||||||||||||||
The description of concepts, definitions and main statistical variables is available in CIS 2018 European metadata file (ESMS) Results of the community innovation survey 2018 (CIS2018) (inn_cis11) in Eurostat database. |
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3.5. Statistical unit | ||||||||||||||||||||||||||||||||||||||||||||||||
Statistical unit is enterprise |
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3.6. Statistical population | ||||||||||||||||||||||||||||||||||||||||||||||||
Core target population are all enterprises in CORE NACE activities (see 3.3.1) with 10 or more employees. Core target population CIS2018 is 3838 |
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3.7. Reference area | ||||||||||||||||||||||||||||||||||||||||||||||||
All territory of Estonia is covered. Estonia is at NUTS 2 level. |
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3.8. Coverage - Time | ||||||||||||||||||||||||||||||||||||||||||||||||
Several rounds of Community Innovation Survey have been conducted so far at two-year interval since end of 90’s. Timeseries are available since 2000 |
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3.8.1. Participation in the CIS waves | ||||||||||||||||||||||||||||||||||||||||||||||||
*two reference periods can be distinguished for CIS light: 2000-2002 and 2001-2003 |
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3.9. Base period | ||||||||||||||||||||||||||||||||||||||||||||||||
Not relevant. |
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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. |
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For CIS 2018, the time covered by the survey is the 3-year period from the beginning of 2016 to the end of 2018. Some questions and indicators refer to one year — 2018. The list of indicators covering the 3-year period and referring to one year according to the HDC is available in the Annex section of the European metadata (ESMS). |
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6.1. Institutional Mandate - legal acts and other agreements | |||
CIS surveys are based on the Commission Regulation No 995/2012, implementing Decision No 1608/2003/EC 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. |
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6.1.1. National legislation | |||
DIRECTLY APPLICABLE LEGAL ACTS Decision No 1608/2003/EC of the European Parliament and of the Council of 22 July 2003 concerning the production and development of Community statistics on science and technology (Text with EEA relevance) Commission Regulation (EC) No 1450/2004 of 13 August 2004 implementing Decision No 1608/2003/EC of the European Parliament and of the Council concerning the production and development of Community statistics on innovation Commission Implementing Regulation (EU) No 995/2012 of 26 October 2012 laying down detailed rules for the implementation of Decision No 1608/2003/EC of the European Parliament and of the Council concerning the production and development of Community statistics on science and technology |
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6.2. Institutional Mandate - data sharing | |||
Not requested. |
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CIS data are transmitted to Eurostat via EDAMIS using the secured transmission system. |
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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 Statistics Estonia: http://www.stat.ee/66485. |
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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. |
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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).
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8.2. Release calendar access | |||
http://www.stat.ee/release-calendar |
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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. |
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CIS is conducted and disseminated at two-year interval in pair years. |
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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. |
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10.1. Dissemination format - News release | |||||||||||||||
See below. |
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10.1.1. Availability of the releases | |||||||||||||||
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10.2. Dissemination format - Publications | |||||||||||||||
- Online database (containing all/most results) : all the data are published in the online database https://andmed.stat.ee/en/stat - Analytical publication (referring to all/most results) : analytical review is available https://www.stat.ee/et/avasta-statistikat/valdkonnad/infotehnoloogia-innovatsioon- ja-teadus-arendustegevus/innovatsioon - 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 https://www.stat.ee/et/avasta-statistikat/valdkonnad/infotehnoloogia-innovatsioon-ja-teadus-arendustegevus/innovatsioon |
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10.3. Dissemination format - online database | |||||||||||||||
Yes, the online database is available https://andmed.stat.ee/en/stat |
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10.3.1. Data tables - consultations | |||||||||||||||
Not requested. |
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10.4. Dissemination format - microdata access | |||||||||||||||
Microdata was transmitted to Eurostat on 01.07.2020. |
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10.4.1. Dissemination of microdata | |||||||||||||||
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10.5. Dissemination format - other | |||||||||||||||
No other means of dissemination. |
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10.5.1. Metadata - consultations | |||||||||||||||
Not requested. |
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10.6. Documentation on methodology | |||||||||||||||
ESMS Matadata information is available https://www.stat.ee/en/find-statistics/methodology-and-quality/esms-metadata/21702 |
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10.6.1. Metadata completeness - rate | |||||||||||||||
Not requested. |
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10.7. Quality management - documentation | |||||||||||||||
There is no special quality documents available. ESMS Metadata information is available https://www.stat.ee/en/find-statistics/methodology-and-quality/esms-metadata/21702 |
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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. |
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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 evaluation using 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. |
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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. The aims of user surveys are:
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 https://www.stat.ee/en/statistics-estonia/about-us/user-surveys Proposals from stakeholders and users are negotiated to specify the need for data and the possibility their inclusion in the 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.
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12.1.1. Needs at national level | ||||||||||||||||||||||||||||||||||||
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12.2. Relevance - User Satisfaction | ||||||||||||||||||||||||||||||||||||
Since 1996, Statistics Estonia has conducted reputation and user satisfaction surveys. All results are available on the website at http://www.stat.ee/user-surveys. |
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12.3. Completeness | ||||||||||||||||||||||||||||||||||||
No missing cells among mandatory ones. Only 2 not mandatory indicators tax credits or allowances for RD or other innovation activities and tax credits or allowances for all other types of activities were excluded because there are no tax allowances in Estonia. |
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12.3.1. Data completeness - rate | ||||||||||||||||||||||||||||||||||||
Not requested. |
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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). |
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13.2. Sampling error | ||||||||||||||||||||||||||||||||||||||||||||||||||||
That part of the difference between a population value and an estimate thereof, derived from a random sample, which is due to the fact that only a subset of the population is enumerated. |
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13.2.1. Sampling error - indicators | ||||||||||||||||||||||||||||||||||||||||||||||||||||
The main indicator used to measure sampling errors for CIS data is the coefficient of variation (CV).
Coefficient of Variation= (Square root of the estimate of the sampling variance) / (Estimated value) Formula:
where |
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13.2.1.1. Coefficient of variations for key variables | ||||||||||||||||||||||||||||||||||||||||||||||||||||
Coefficient of variation (%) for key variables by NACE categories and for enterprises with 10 and more employees
[1] = Coefficient of variation for the percentage of innovative enterprises (INN) in the total population of enterprises (ENT18) |
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13.2.1.2. Variance estimation method | ||||||||||||||||||||||||||||||||||||||||||||||||||||
For variance estimation the Taylor series linearization method is used. Annexes: Standard errors formula |
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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. |
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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 has 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. |
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13.3.1.1. Over-coverage - rate | ||||||||||||||||||||||||||||||||||||||||||||||||||||
Not requested. |
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13.3.1.2. Common units - proportion | ||||||||||||||||||||||||||||||||||||||||||||||||||||
Not requested. |
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13.3.1.3. Under covered groups of the target population | ||||||||||||||||||||||||||||||||||||||||||||||||||||
Updated business register of Estonian economic units do not allow undercoverage. |
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13.3.1.4. Coverage errors in coefficient variation | ||||||||||||||||||||||||||||||||||||||||||||||||||||
Not applicable |
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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. |
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13.3.2.1. Measures for reducing measurement errors | ||||||||||||||||||||||||||||||||||||||||||||||||||||
More complex questions in CIS 2018 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 VVIS was used to collect the data which is more user-friendly from the point of view of the respondent. 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. |
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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 47.09 |
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13.3.3.1. Unit non-response - rate | ||||||||||||||||||||||||||||||||||||||||||||||||||||
See below. |
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13.3.3.1.1. Un-weighted and weighted unit non-response rate by NACE categories and for enterprises with 10 or more employees | ||||||||||||||||||||||||||||||||||||||||||||||||||||
Un-weighted and weighted unit non-response rate by NACE categories and for enterprises with 10 or more employees
The number of eligible units is the number of sample units, which indeed belong to the target population. |
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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 January 2019. The second letter was sent just before the start of the survey on 15 August.During the collection period, five reminder letters were sent to non-responded units |
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13.3.3.2. Item non-response - rate | ||||||||||||||||||||||||||||||||||||||||||||||||||||
See below. |
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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 employees) | ||||||||||||||||||||||||||||||||||||||||||||||||||||
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 employees).
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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 employees)
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13.3.4. Processing error | ||||||||||||||||||||||||||||||||||||||||||||||||||||
There were few processing errors. There were problems with 2 indicators, the enterprise group membership indicator and research and development expenses. In the case of group membership, there were differences in the country of location of the group's parent company compared to the statistical profile data. In these cases, enterprises were contacted by phone and specified membership. In general, the problem was in the respondent's understanding and interpretation. Regarding research and development expenditures, we 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. |
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13.3.5. Model assumption error | ||||||||||||||||||||||||||||||||||||||||||||||||||||
Not requested. |
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Timeliness and punctuality refer to time and dates, but in a different manner. |
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14.1. Timeliness | |||
The timeliness of statistics reflects the length of time between data availability and the event or phenomenon they describe. |
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14.1.1. Time lag - first result | |||
Timeliness of national data – date of first release of national level : Data was published in national database on 25.05.2020 |
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14.1.2. Time lag - final result | |||
Not requested. |
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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. |
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14.2.1. Punctuality - delivery and publication | |||
Date of transmission of complete and validated data to Eurostat (Number of days between that data and 30 June 2020) : data were transmitted to Eurostat on 01.07. 2020, also microdata were transmitted on 01.07.2020 |
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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. |
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15.1. Comparability - geographical | ||||||||||||||||||||
The data are 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. |
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15.1.1. Asymmetry for mirror flow statistics - coefficient | ||||||||||||||||||||
Not requested. |
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15.1.2. National questionnaire – compliance with Eurostat model questionnaire | ||||||||||||||||||||
Methodological deviations from the CIS Harmonised Data Collection (HDC)
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15.1.3. National questionnaire – additional questions | ||||||||||||||||||||
Methodological deviations from the CIS Harmonised Data Collection (HDC)
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15.2. Comparability - over time | ||||||||||||||||||||
Due to important methodological changes in CIS 2018 driven by Oslo Manual 2018, the data 2018 cannot be directly compared with previous CIS waves. |
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15.2.1. Length of comparable time series | ||||||||||||||||||||
Not requested. |
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15.3. Coherence - cross domain | ||||||||||||||||||||
See the comparison between SBS and CIS data in the section 15.3.3 below. |
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15.3.1. Coherence - sub annual and annual statistics | ||||||||||||||||||||
Not requested. |
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15.3.2. Coherence - National Accounts | ||||||||||||||||||||
Not requested. |
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15.3.3. Coherence – Structural Business Statistics (SBS) | ||||||||||||||||||||
This part compares key variables for aggregated CIS data with SBS data
* Numbers are to be provided for the last year of the reference period (t) |
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15.4. Coherence - internal | ||||||||||||||||||||
Not requested. |
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17.1. Data revision - policy | |||
Not requested. |
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17.2. Data revision - practice | |||
Not requested. |
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17.2.1. Data revision - average size | |||
Not requested. |
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18.1. Source data | ||||||||||||||||||||||||||||||||||||||
See below: |
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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. |
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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. |
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18.1.3. Target population and sample size | ||||||||||||||||||||||||||||||||||||||
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18.1.4. Data source for pre-filled variables | ||||||||||||||||||||||||||||||||||||||
Variables and indicators filled or prefilled from other sources.
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18.1.5. Data source and variables used for derivation and weighting | ||||||||||||||||||||||||||||||||||||||
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18.2. Frequency of data collection | ||||||||||||||||||||||||||||||||||||||
According to the Commission Regulation (UE) 995/2012, 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. |
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18.3. Data collection | ||||||||||||||||||||||||||||||||||||||
Data are 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 at https://www.stat.ee/en/submit-data/questionnaires/12932019 (in Estonian). Data are collected with the annual statistical questionnaire “Enterprises innovation survey”. |
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18.3.1. Survey participation | ||||||||||||||||||||||||||||||||||||||
The survey is mandatory |
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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. |
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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. |
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18.3.4. Census criteria | ||||||||||||||||||||||||||||||||||||||
Enterprises with number of employees more than 50 were investigated totally |
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18.3.5. Data collection method | ||||||||||||||||||||||||||||||||||||||
Data collection method
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18.4. Data validation | ||||||||||||||||||||||||||||||||||||||
Not requested. |
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18.5. Data compilation | ||||||||||||||||||||||||||||||||||||||
Operations performed on data to derive new information according to a given set of rules. |
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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) |
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18.5.1.1. Imputation rate for metric variables | ||||||||||||||||||||||||||||||||||||||
Imputation rate for metric variables by NACE categories and for enterprises with 10 or more employees:
(1) = Total turnover in the last year of the reference period (t) (TUR) (2) = 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/TUR(INNO_PRD) (3) = R&D expenditure performed in-house (EXP_INNO_RND_IH) |
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18.5.2. Weights calculation | ||||||||||||||||||||||||||||||||||||||
Weights calculation method for sample surveys
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18.6. Adjustment | ||||||||||||||||||||||||||||||||||||||
Not applicable |
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18.6.1. Seasonal adjustment | ||||||||||||||||||||||||||||||||||||||
Not requested. |
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