Community innovation survey 2020 (CIS2020) (inn_cis12)

National Reference Metadata in Single Integrated Metadata Structure (SIMS)

Compiling agency: CZECH STATISTICAL OFFICE


Eurostat metadata
Reference metadata
1. Contact
2. Metadata update
3. Statistical presentation
4. Unit of measure
5. Reference Period
6. Institutional Mandate
7. Confidentiality
8. Release policy
9. Frequency of dissemination
10. Accessibility and clarity
11. Quality management
12. Relevance
13. Accuracy
14. Timeliness and punctuality
15. Coherence and comparability
16. Cost and Burden
17. Data revision
18. Statistical processing
19. Comment
Related Metadata
Annexes (including footnotes)
 



For any question on data and metadata, please contact: Eurostat user support

Download


1. Contact Top
1.1. Contact organisation

CZECH STATISTICAL OFFICE

1.2. Contact organisation unit

Research, Development and Information Society Statistics Unit

1.5. Contact mail address

Czech Statistical Office

Society Development Statistics Department

Na padesatem 81

Praha 10

100 82


2. Metadata update Top
2.1. Metadata last certified 28/02/2024
2.2. Metadata last posted 28/02/2024
2.3. Metadata last update 28/02/2024


3. Statistical presentation Top
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

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 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

 

3.3.1.1. Main economic sectors covered - NACE Rev.2 - national particularities

No national particularities.

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:

  • 10 - 49 employees
  • 50 - 249 employees
  • 250 or more employees
3.3.2.1. Sector coverage - size class - national particularities

Person employed used instead of employee as classification unit for size class of enterprises.

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.

3.5. Statistical unit

The statistical unit is an enterprise which corresponds to the legal unit with the identification number given by the Business Register.

3.6. Statistical population

Core target population are all enterprises in CORE NACE activities (see 3.3.1) with 10 or more employed persons.

3.7. Reference area

The geographic area to which the measured statistical phenomenon relates is Czechia (NUTS1) for all variables (data) and NUTS2 for selected variables (data).

3.8. Coverage - Time

Several rounds of Community Innovation Survey have been conducted so far at two-year interval since end of 90’s.

3.8.1. Participation in the CIS waves
CIS wave Reference period Participation Comment (deviation from reference period)
CIS2 1994-1996  No  
CIS3 1998-2000  Yes   1999-2001
CIS light 2002-2003*  Yes  
CIS4 2002-2004  Yes   2003-2005
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  

*two reference periods can be distinguished for CIS light: 2000-2002 and 2001-2003

3.9. Base period

Not relevant.


4. Unit of measure Top

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.


5. Reference Period Top

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). 


6. Institutional Mandate Top
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.

6.1.1. National legislation

There is no specific Czech legislation for the production of CIS statistics. The European Legislation applies.

The Law on Statistics of the Czech Republic is the main national legal act regarding official statistics. Production of CIS statistics as well as other official statistics is included in the annual Official Statistics Work Programme.

6.2. Institutional Mandate - data sharing

Not requested.


7. Confidentiality Top

CIS data are transmitted to Eurostat via EDAMIS using the secured transmission system.

7.1. Confidentiality - policy

See the Framework Security Policy in tha annexed document.



Annexes:
the_czso_framework_security_policy
7.2. Confidentiality - data treatment

In producing the standard statistical outputs, a number of procedures were implemented to prevent the release of information that identified characteristics about an enterprise.

1) Restricting the number of output categories into which a variable may be classified.

2) Where the number of enterprises in a group fell below a minimum threshold, the statistical output is not published.

The rule concerning the confidentiality applied for treating the tabular data is following: less than 3 enterprises or at least 85% of turnover for one enterprise.


8. Release policy Top
8.1. Release calendar

The main indicators were released in a press release in June 2022.

All indicators (data) were published in the regular publication Innovation activities of enterprises during 2018-2020 in June 2022.

8.2. Release calendar access

https://www.czso.cz/csu/czso/catalogue-of-products

8.3. Release policy - user access

The CIS data are disseminated to all users through the Official Statistics Portal. The data are released simultaneously to all interested parties by issuing a news release. At the same time the news release is also e-mailed to the media. The news release is issued in Czech only. All published CIS data are available for users for free. Special datasets made ad hoc for researches/students are chargeable. Anonymized microdata are available at the Safe Centre of CZSO. The access to these microdata is paid.



Annexes:
diseminace csu_aj


9. Frequency of dissemination Top

CIS is conducted and disseminated at two-year interval in even years.


10. Accessibility and clarity Top

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  Only Czech version. https://www.czso.cz/csu/czso/investice-do-inovaci-byly-rekordni
Access to public free of charge   Yes  Only Czech version. https://www.czso.cz/csu/czso/inovacni-aktivity-podniku-20182020
Access to public restricted (membership/password/part of data provided, etc)  Yes  Only Czech version.
10.2. Dissemination format - Publications

-              Online database (containing all/most results) : No

-              Analytical publication (referring to all/most results) : Yes : https://www.czso.cz/csu/czso/inovacni-aktivity-podniku-20182020

-              Analytical publication (referring to specific results, e.g. only for one sector or one specific aspect) : No

10.3. Dissemination format - online database

Not available.

10.3.1. Data tables - consultations

Not requested.

10.4. Dissemination format - microdata access

Microdata are accessible only at the National SAFE centre and Eurostat SAFE centre.

10.4.1. Dissemination of microdata
Mean of dissemination Availability of microdata Comments, links, ...
Eurostat SAFE centre  Yes  
National SAFE centre  Yes  https://www.czso.cz/csu/czso/statistical_data_for_scientific_research_purposes
Eurostat: partially anonymised data (SUF)  Yes  
National : partially anonymised data  No  
10.5. Dissemination format - other

No other means of dissemination.

10.5.1. Metadata - consultations

Not requested.

10.6. Documentation on methodology

The complete meta-information (methodology of survey, definition of variables) on the CIS is available for users on the website of CZSO.

https://www.czso.cz/csu/czso/statistika_inovaci

10.6.1. Metadata completeness - rate

Not requested.

10.7. Quality management - documentation

Quality related documents (quality reports, studies, etc) are not publicly available. Only selected indicators are published (e.g. overall non-response rate).


11. Quality management Top
11.1. Quality assurance

See attached annex.



Annexes:
CZSO quality commitment
11.2. Quality management - assessment

Assessment of the quality uses the following components:

1) Standard STS (Simple, Transparent, and Standardised) compliance assessments carried out by Eurostat. This assessment is used internally as well.

2) Regular response rate measurement.

3) Regular methodological update and ad hoc methodological audit carried out every 10 years.

The overall quality of the national methodology is good. Improving of the national methodology regarding CIS and data quality is ongoing process in line with ICT development.


12. Relevance Top

Relevance is the degree to which statistics meet current and potential users’ 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 in order to achieve comparable, harmonised and high quality results for EU Member States, EFTA countries, Candidates and Associated countries.

12.1. Relevance - User Needs

The CZSO primarily fulfils its commitments towards the European Commission, which represents the high priority user. However, depending on the capacity available the CZSO treats all the users equally.

The relevance of an instrument has to be assessed in the light of the needs of its users. As for EU Statistics on innovations in enterprises (CIS) the main users are the following:

1) Institutional users having access to aggregative data for policy-making;

2) Statistical users in Eurostat or in National Statistical Institutes to feed sectorial or transversal publications;

3) Researchers having access to microdata;

4) End users – including the media - interested in innovations in the EU area.

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
The European Commission (DG ENTR) Data used for the European
Innovation Scoreboard and its
further development
OECD Data used for analyses
Ministry of Industry and Trade Data used for analyses (micro-data)
  R&D&I Council Data used for analyses and policy making

 1. Institutions – Regional level

Regional Innovation Agencies Data used for analyses and policy making (regional innovation strategies)
  Association of Innovative Entrepreneurship CR, Technology Center AS CR Data used for analyses and research (using micro-data)
National and regional media Data used for analyses
 4 Center for Economic Research and Graduate Education – Economics Institute, Charles University, students Data used for analyses and research
12.2. Relevance - User Satisfaction

No user satisfaction survey is carried out exclusively for CIS indicators on the national level. However, CZSO is constantly in contact with different groups of users, e.g. Ministry of Industry and Trade, Czech National Bank, different associations, internal users etc. Formal meeting with users is organized regularly by the General Methodology Department. Data users are asked for a potential feedback if they receive data, publications or special outputs.

Every 5 years, CZSO organises . Last one was carried out in 2020.

12.3. Completeness

All compulsory CIS 2020 variables according to the Commission Regulation No 995/2012 are implemented.

12.3.1. Data completeness - rate

Not requested.


13. Accuracy Top
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

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.

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

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

NACE

Size class

(1)

(2)

(3)

Core NACE (B-C-D-E-46-H-J-K-71-72-73)

Total

0.778282 0.758087 0.883682

Core industry (B_C_D_E - excluding construction)

Total

0.89336 1.017464 0.957058

Core Services (46-H-J-K-71-72-73)

Total

1.318817 0.59658 1.548815

 

     
     
     
13.2.1.2. Variance estimation method

See the annex 1.



Annexes:
Variance estimation method
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 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.

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

Because the corresponding list of units with the number social of insurance policyholders, is handed over with monthly periodicity with about a two-month delay after the end of the reference period, some coverage errors can occur at time of sampling.

13.3.1.4. Coverage errors in coefficient variation

The coefficient of variation reported under 13.2.1.1 incorporates the effects of coverage errors.

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

Regarding overvalued innovation expenditure the following ratio is calculated as innovation expenditures in the given year/ turnover in the given year which should be lower than 1. Innovation expenditures on in-house research and development is also compared with research and development expenditures in Annual Research and Development Survey. A special training is organized for staff that process the questionnaires and transfer data from printed questionnaires to databases (data entry).

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 overall unit non-response rate is very good with low values. The weighted unit non-response rate and un-weighted unit non-response rate are both around 11 %.

No imputation regarding a non-responding unit is applied.

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 employees

Un-weighted and weighted unit non-response rate by NACE categories and for enterprises with 10 or more persons employed

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) 564 5139 10.97 11.57
Core industry (B_C_D_E - excluding construction) 314 2915 10.77 10.40
Core Services (46-H-J-K-71-72-73) 878 8054 10.90 11.02

The number of eligible units is the number of sample units, which indeed belong to the target population.

13.3.3.1.2. Maximum number of recalls/reminders before coding

Two reminders are sent and also telephone follow-ups are carried out if it is needed.

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 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 persons employed).

  Item non-response rate (un-weighted)  Imputation If imputed, describe method used, mentioning which auxiliary information or stratification is used
Turnover  Not surveyed  Partially SBS and other yearly surveys turnovers used in item imputation for all unit. If there were no turnover values in these yearly surveys, they were imputed by use of administrative data.
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)
 

NEW QUESTIONS IN CIS 2020 Inclusion in national questionnaire  Item non response rate (un-weighted) Comments
2.2   Market conditions faced by enterprise  No  -  
2.8   Factors related to climate change  No  -  
3.16  Innovations with environmental benefits  Yes  0  
3.17  Factors driving environmental innovations  No  -  
13.3.4. Processing error

Main data entry methods are: data scanning or keying for the printed questionnaire (1/3 of all) and CASI/e-PDF for the electronic questionnaire (2/3 of all). The errors’ catching is maintained by programming tools which identify hard and soft errors. Programming tools find incomplete answers and warn of the given type of error. Errors which were found during this checking process are corrected manually.

Processing errors are not significant.

13.3.5. Model assumption error

Not requested.


14. Timeliness and punctuality Top

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 : 18 months after the reference year

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 data and 30 June 2022) : 1 day


15. Coherence and comparability Top

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

No significant problems of comparability between regions at the level NUTS 2 of Czechia. The stratification of the sample is set to eliminate possible problems regarding comparability between regions at the NUTS 2.

Data collected by this survey are internationally comparable because this survey respects standards described in Oslo manual (OECD, 2018) and 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.

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
 Q2.2, 2.3, 2.8, 3.9, 3.14, 3.17, 4.2, 4.6, 4.8, 4.9  
 Q3.10  Only options regarding public funds used for R&D or other innovation activities

 

Changes in the filtering compared to HDC Comment
   
   
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
 Geographic markets where an enterprise sells goods and/or services former question from CIS 2016
 Results/impacts of implemented product innovations Yes/No options
   
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.

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 persons employed

NACE Size class Number of enterprises (SBS/CIS)* Number of persons employed (SBS/CIS)* Total Turnover (SBS/CIS)*
Core NACE (B-C-D-E-46-H-J-K-71-72-73) Total 99.1 103.3 100.0
Core industry (B_C_D_E - excluding construction) Total 96.6 91.1 85.2
Core Services (46-H-J-K-71-72-73) Total 97.9 98.9 94.3

* Numbers are to be provided for the last year of the reference period (t)

15.4. Coherence - internal

Not requested.


16. Cost and Burden Top

Confidential information on the production cost of the CIS.


17. Data revision Top
17.1. Data revision - policy

Not requested.

17.2. Data revision - practice

Not requested.

17.2.1. Data revision - average size

Not requested.


18. Statistical processing Top
18.1. Source data

See below:

18.1.1. Sampling frame (or census frame)

The frame population is the same as the one for the Structural Business Survey (SBS). Following ESA 2010 sectors are included: S.11+S.12+S.141.

18.1.2. Sampling design

Sampling design is a combination of stratified random sampling (enterprises with 10-249 employees of selected two-digit NACE industries) and census (see 12.3.3). Two-digit NACE, NUTS2 and size-class according to the Business Register were used for stratification. The sample was designed with no reference to any other survey. Following ESA 2010 sectors are covered: S.11+S.12+S.141. The total number of strata is 1320 including special strata for units with unknown NACE.

18.1.3. Target population and sample size
Sample/census indicator Number of enterprises
Target population 25147
Sample 8320
In case of combination sample/census:
Sampled units 6920
Enumerated units/census 1400
Overall sample rate (overall sample/target population) 0.33
18.1.4. Data source for pre-filled variables

Variables and indicators filled or prefilled from other sources.

 

Variables/Indicators Source Reference year
 TAX_CRED_RNDINN General Financial Directorate (GFD) - data from Corporate Income Tax returns  2018-2020
     
18.1.5. Data source and variables used for derivation and weighting
Item Response
Data source used for deriving population totals Number of persons employed - SBS and other yearly business surveys
Total turnover - SBS and administrative tax data
Variables used for weighting Number of persons employed - SBS and other yearly business surveys
Total turnover - SBS and administrative tax data
Number of enterprises in the sampling frame
Number of social security policyholder - from social security administrative data
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.

18.3. Data collection

CZ-CIS survey in the Czech Republic is a combination of computer assisted filling in and paper questionnaires. There is a possibility for enterprises to fill in PDF format of questionnaire or online questionnaire.  Respondents receive instructions (via a message in their data mailbox) describing how to get the online questionnaire (computer assisted) or have an opportunity to download the online questionnaire from the CZSO website. We send paper questionnaires to enterprises that do not own data mailboxes (approximately 500 enterprises a year). Paper questionnaires are sent and returned by post. 

During the data collection, checking and processing period all received data are checked primarily by junior statisticians (secondary by the Project manager). Online questionnaires (computer assisted) includes all necessary consistency checks (controls). There are approximately 150 of them every year. Inconsistencies in controls notify junior statisticians of necessity to check answers. Phone calls are used for validation of the data (corrections) and quality improvement if necessary. The year-to-year checks in the aggregate data (before data delivery to Eurostat) are made.

No imputation for item non-response will be used except of imputation of some background information that will not be available in SBS database.

18.3.1. Survey participation

The survey is mandatory.

18.3.2. Survey type

Data are collected through the combination of a census and sample survey.

18.3.3. Combination of sample survey and census data

Covered by Census:
- Number of employees according to the Business Register >=250 of ALL CORE NACE
- Number of employees according to the Business Register =50-249 of NACE=5-9, 12, 19, 37, 39, 50-51, 53, 59-60

 

Covered by sample survey:

- Number of employees according to the Business Register =50-249 of NACE=10-11, 13-18, 20-36 , 38, 46, 49, 52, 58, 61-66, 71-73

- Number of employees according to the Business Register =10-49 of all NACE

18.3.4. Census criteria

Covered by Census:
- Number of employees according to the Business Register >=250 of ALL CORE NACE
- Number of employees according to the Business Register =50-249 of NACE=5-9, 12, 19, 37, 39, 50-51, 53, 59-60

 

18.3.5. Data collection method

Data collection method

Survey method Yes/No Comment
Face-to-face interview  No  
Telephone interview  Yes  The telephone interview and email were used for checking and editing primary data.
Postal questionnaire  Yes  
Electronic questionnaire (format Word or PDF to send back by email)  Yes  e-PDF
Web survey (online survey available on the platform via URL)  Yes  
Other  -  
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 persons employed:

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) = 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)

18.5.2. Weights calculation

Weights calculation method for sample surveys

Method Selected applied method  Comments
Inverse sampling fraction    
Non-respondent adjustments    
Other  GREG estimators (calibration method) The starting weights are calibrated in 3 stages to treat non-response and provide more accurate and coherent estimates:
+ stage 1: weight are adjusted to preserve estimated totals of units and number of social security policyholders in the strata.
+ stage 2: weight from the previous are adjusted to preserve estimated totals of units and number of employees in the strata.
+ stage 3: weight from the previous are adjusted to preserve estimated totals of units and turnover in the strata
18.6. Adjustment

No procedures employed to modify statistical data are applied.

18.6.1. Seasonal adjustment

Not relevant for yearly data.


19. Comment Top


Related metadata Top


Annexes Top