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For any question on data and metadata, please contact: Eurostat user support |
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1.1. Contact organisation | ROMANIA NATIONAL INSTITUTE OF STATISTICS |
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1.2. Contact organisation unit | DEPARTMENT OF SHORT TERM ECONOMIC INDICATORS STATISTICS |
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1.5. Contact mail address | 16 Libertatii Bvd, Bucharest 5, Romania |
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2.1. Metadata last certified | 31/07/2024 | ||
2.2. Metadata last posted | 30/05/2024 | ||
2.3. Metadata last update | 30/05/2024 |
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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 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.
CIS 2020 is a second in a row to implement concepts and methodology of the Oslo Manual 4th Edition revised in 2018. The changes in the CIS driven by the revision of the manual and their impact on collected indicators are described in the Statistics Explained article: Community Innovation Survey – new features.
The legal framework for CIS since 2012 is the Commission Regulation No 995/2012 that establishes the quality conditions for the data collection and transmission and identifies the obligatory cross-coverage of economic sectors, size class of enterprises and innovation indicators. The target population are enterprises with at least 10 employees 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). Please refer to the Annex section of the European metadata (ESMS) for details of the time coverage of collected indicators. |
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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 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. |
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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 | ||||||||||||||||||||||||||||||||||||||||||||||||||||
No, national particularities; the core NACE activities only |
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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 | ||||||||||||||||||||||||||||||||||||||||||||||||||||
No national particularities |
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3.4. Statistical concepts and definitions | ||||||||||||||||||||||||||||||||||||||||||||||||||||
The description of concepts, definitions and main statistical variables is available in CIS 2020 European metadata file (ESMS) Results of the community innovation survey 2020 (CIS2020) (inn_cis12) in Eurostat database. |
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3.5. Statistical unit | ||||||||||||||||||||||||||||||||||||||||||||||||||||
Statistical unit is an enterprise. The enterprise is a group of legal units constituted as an organizational entity of goods production, trade services or social interest services, which benefits of a decisional autonomy, especially in view to ensure its current resources. An enterprise is carrying out one or several activities, on one or several places (headquarters - local units of enterprises). |
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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. |
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3.7. Reference area | ||||||||||||||||||||||||||||||||||||||||||||||||||||
According NUTS 2016 classification, CIS collect and disseminate regional information at NUTS 2 level (Romanian 8 basic regions for the application of regional policies). |
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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. |
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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 2020, the time covered by the survey is the 3-year period from the beginning of 2018 to the end of 2020. Some questions and indicators refer to one year — 2020. 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 | |||
Law on the organization and functioning of official statistics in Romania no. 226/2009 https://insse.ro/cms/ro/content/cadru-legal-ins
Government Decision no. 586/2020 on the approval of the National Annual Statistical Program 2020; https://insse.ro/cms/ro/content/cadru-legal-ins |
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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 | |||
No deviations from secure procedure Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of individuals with regard to the processing of personal data and on the free movement of such data and repealing Directive 95/46 / EC (General Regulation on data protection) https://insse.ro/cms/ro/content/norme-de-confiden%C8%9Bialitate Law no. 190 of 18 July 2018 on measures to implement Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of individuals with regard to the processing of personal data and on the free movement of these data and repealing Directive 95/46 / EC (General Data Protection Regulation) https://insse.ro/cms/ro/content/norme-de-confiden%C8%9Bialitate European Commission Regulation no. 995/2012, which implements Decision no. 1608/2003 / EC of the European Parliament and of the EU Council on the production and development of Community statistics in the field of science and technology LAW no. 363 of December 28, 2018 on protection natural persons regarding the processing of personal data by the competent authorities for the purpose of preventing, detecting, investigating, prosecuting and combating crime or the execution of punishments, educational and security measures, and regarding the free movement of such data Law no. 102/2005 on the establishment, organization and functioning of the National Authority for the Supervision of Personal Data Processing, with subsequent amendments and completions. |
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7.2. Confidentiality - data treatment | |||
The rules that have been applied for aggretate tables were the following: the rule of three, the dominance and the precision. |
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8.1. Release calendar | |||
On the NIS website there are two calendars one for the press releases and the other for publications; both of them are accessible to the general public. |
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8.2. Release calendar access | |||
https://insse.ro/cms/files/catalog/Catalogul_publicatiilor_INS_2022.pdf - for publications https://insse.ro/cms/ro/comunicate-de-presa-view for press release |
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8.3. Release policy - user access | |||
The NIS has on the web page a section “Calendar of press releases”, with links to the monthly lists of publications planned for the current year. Each monthly list is sorted by date of publication and contains a brief description of the statistics to be provided. The monthly calendar is established for the following year in December of the previous year. NIS publishes annually on the site the calendar of press releases, calendar based on the terms of the Annual National Statistical Program and contains: title of the press release, reference period, date of issue. The monthly calendar is established and posted on the NIS website from December of the previous year. The calendar of press releases on the NIS website covers only the statistics published by the NIS In the event of a change in the broadcast date, this is announced 24 hours before the calendar date, specifying the new broadcast date. |
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CIS is disseminated at two-year interval in even 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 publication(containing all/most results) : "Innovation in business enterprises” - Analytical publication (referring to all/most results) : General paper publication -Availlable only for national users. - Analytical publication (referring to specific results, e.g. only for one sector or one specific aspect) : |
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10.3. Dissemination format - online database | |||||||||||||||
http://statistici.insse.ro:8077/tempo-online/#/pages/tables/insse-table Available also in Romanian language format. |
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10.3.1. Data tables - consultations | |||||||||||||||
Not requested. |
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10.4. Dissemination format - microdata access | |||||||||||||||
See below |
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10.4.1. Dissemination of microdata | |||||||||||||||
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10.5. Dissemination format - other | |||||||||||||||
Sectoral indicators, more detailed NACE activities, SMEs regional data, high-tech innovative enterprises, competitiveness indicators, sustenable indicators, logistics indicators. |
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10.5.1. Metadata - consultations | |||||||||||||||
Not requested. |
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10.6. Documentation on methodology | |||||||||||||||
Data are accompanied of metadata describing the indicators and the calculation thereof. To all other questions regarding the methodology or the manner of designing the tables and the data we respond whenever necessary. In the TEMPO online database, each indicator is accompanied by the related metadata. |
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10.6.1. Metadata completeness - rate | |||||||||||||||
Not requested. |
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10.7. Quality management - documentation | |||||||||||||||
Romanian NIS has a special department for dissemination of data. All requirements of the users are solved by this department in cooperation with the production and methodological departments. CIS data quality reports are prepared at the end of each survey wave, once every 2 years, in even years. They are transmitted to Eurostat and posted on the NIS website at: https://insse.ro/cms/ro/content/rapoarte-de-calitate-anchete-statistice |
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11.1. Quality assurance | |||||||
The quality quantifies how well the statistics are fit for their purpose. The criteria to judge statistical quality correspond to: relevance, accuracy and reliability, timeliness and punctuality, accessibility and clarity, comparability, coherence and cost and burden. The aim is to reduce the errors of coverage, the non-response, the measurements errors, the processing errors. Sampling errors occur when the survey results are obtained from a sample rather than the population as a whole. They may also include estimation errors due to estimators that, by design or otherwise, create bias. Sampling errors are measured by the values of the coefficients of variation.
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11.2. Quality management - assessment | |||||||
The CIS survey is conducted to provide knowledge about innovation on business enterprises and to allow comparisons with other European countries. The national methodology is based on the Eurostat methodology prepared for CIS 2020 survey and meets the requirements of the six quality dimensions according with European Statistical System and other important characteristics. Weaknesses - Absence of a common IT program in order to process CIS data at micro-level in a harmonised fashion for all Member States. - A detailed methodology for computing the weighting coefficients. |
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Relevance is the degree to which statistics meet current and potential user needs. It includes the production of all needed statistics and the extent to which concepts used (definitions, classifications etc.) reflect user needs. The aim is to describe the extent to which the statistics are useful to, and used by, the broadest array of users. For this purpose, statisticians need to compile information, firstly about their users and their needs. The CIS is based on a common questionnaire and a common survey methodology, as laid down in the 4rd edition of Oslo Manual (2018 edition), in order to achieve comparable, harmonised and high quality results for EU Member States, EFTA countries, Candidates and Associated countries |
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12.1. Relevance - User Needs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
At every CIS wave, before the finalisation of the national questionnaire, the main national users and the representatives of regional NIS departments are invited to a discussion, by Romanian NIS, to express their opinions and suggestions about the final national questionnaire (clarity, difficulties, understanding and perception of the questions and about other national statistical needs). |
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12.1.1. Needs at national level | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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12.2. Relevance - User Satisfaction | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
NIS Romania conducted a general user satisfaction survey on every 3 years, where CIS and R&D domain is mention. The users request more detailed data for SMEs, regional data, new ad-hoc module and also accessibility to micro data. |
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12.3. Completeness | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
National survey includes all indicators of European questionnaire, CIS 2020. We have no missingness issues. |
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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 (ENT20) |
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13.2.1.2. Variance estimation method | ||||||||||||||||||||
Varianceh = (Ph*(1-Ph)*(Nh-mh))/( Nh *( mh -1)) |
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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 | ||||||||||||||||||||
Estimation of coverage was computed with the initial coefficient of extraction using the turnover Under covered groups (<100%) – section B (99.2%), section C (99.9%), section D (99.7%), section H (97.8%), in Core NACE 46 (97.9%), in Core NACE 58 (96.9%), in Core NACE 60,61 (99.7%), in Core NACE 63 (96.3%), in Core NACE 72 (98.8%), in Core NACE 73 (98.1%). Over covered groups (>100%) – section E(101.4%), section K (100.1%), in Core NACE 62 (100.9%), in Core NACE 71 (101.2%)
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13.3.1.4. Coverage errors in coefficient variation | ||||||||||||||||||||
CVs incorporate the effects of coverage errors. |
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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 | ||||||||||||||||||||
The measures for reducing errors consisted in selection of staff with knowledge in CIS methodology and experience in data entry and validation checks for online questionnaires. Also, we developed detailed methodological notes regarding the new terms and their definition. We recontact the respondents for supplementary clarifications |
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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:
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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. A number of 785 units were removed from the sample because they don't belong to target population after inspection of their characteristics. |
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13.3.3.1.2. Maximum number of recalls/reminders before coding | ||||||||||||||||||||
3 recalls |
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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 | ||||||||||||||||||||
The methods used for data entry were data keying and responses through online questionnaires To check variables, correlations between chapters and items were applied. |
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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 : February 25, 2022 |
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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 2022) : 0 |
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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 | ||||||||||||||||||||
In Romania, there are no problems of comparability between the regions of the country, because all regions are subject to the same assessment and the same questions from the CIS questionnaire, without other additional questions. |
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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)
Annexes: RO_Harmonised Data Collection 2020 |
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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 driven by Oslo Manual 2018, CIS 2018 and CIS 2020 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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Confidential information on the production cost of the CIS. |
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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) | ||||||||||||||||||||||||||||||||||||||
The national business register, named REGIS was used. |
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18.1.2. Sampling design | ||||||||||||||||||||||||||||||||||||||
The sampling design used was the stratified sampling with simple random sampling within the strata. The strata were defined according to the activity, enterprise size by the number of employees and the geographical region. For the sample allocation, Neymann allocation method was used. Sampled units: all enterprises with <250 persons employed; Census : all enterprises with 250 or more persons employed. |
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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 t+18. |
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18.3. Data collection | ||||||||||||||||||||||||||||||||||||||
See below |
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18.3.1. Survey participation | ||||||||||||||||||||||||||||||||||||||
The survey is mandatory. |
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18.3.2. Survey type | ||||||||||||||||||||||||||||||||||||||
Data are collected through a combination of a census and a sample survey. |
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18.3.3. Combination of sample survey and census data | ||||||||||||||||||||||||||||||||||||||
The population classes covered by sampling are the following: 10-49; 50-249. |
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18.3.4. Census criteria | ||||||||||||||||||||||||||||||||||||||
The criterion for census was the size class: all units with 250 and more employees were surveyed. |
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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: No imputation performed.
(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 | ||||||||||||||||||||||||||||||||||||||
In order to get the calibrated weights we used CLAN software. The level was: NACE 2 digits, size class according to average number of employees. |
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18.6.1. Seasonal adjustment | ||||||||||||||||||||||||||||||||||||||
Not requested. |
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