Croatian Bureau of Statistics (CBS)

Innovations, Science and Technologies Unit

Ilica 3, 10 000 Zagreb, Croatia

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

The purpose of statistical survey on innovation activities in enterprises is to determine the share and characteristics of innovative enterprises in Croatia in the period 2016 - 2018. Community Innovation Survey (CIS) is carried out based on harmonized EU methodology and questionnaire and definitions and concepts laid down in the Oslo Manual (2018) 4^th Edition.

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.

CIS covers main economic sectors according to NACE Rev.2 broken down by size class of enterprises and type of innovation activity.

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

Due to its significance in the economy of Croatia, we have additionally surveyed NACE 41-43, 55-56 and 68 apart from the core industries. Furthermore we also surveyed NACE 59 and 60.

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

No deviations.

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.

In accordance with Commission Regulation 995/2012 on innovation statistics, it is required that Member States set up and maintain a register of enterprises, as well as associated legal units and local units.

The basic units of statistical characteristics (observations) to which data refer are legal units - legal entities and natural persons. In national context, until recently it was considered that one legal unit in the statistical business register equals to one enterprise. A legal unit has a complete set of records and autonomy in decision-making. The ongoing process of enterprise profiling will enable us to use the statistical unit enterprise in the future in order to be aligned with the EBS Regulation (and if decided so by the WG STI). For reasons of simplifying further text, we shall use the term enterprise.

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

The survey was conducted in both NUTS2 regions (Continental and Adriatic Croatia). No country parts were excluded from the survey. We also sent regional data according to NUTS 2021 (Panonska Hrvatska, Jadranska Hrvatska, Grad Zagreb and Sjeverna Hrvatska) by recalculating NUTS 2016 data.

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

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

Not relevant.

CIS indicators are available according to 3 units of measure:

NR: Number for number of enterprises and number of persons employed.

THS_EUR: Thousands of euros. All financial variables are provided in thousands of euros, i.e. Turnover or Innovation expenditure.

PC: Percentage. The percentage is the ratio between the selected combinations of indicators.

For CIS 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). 

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.

Legal acts that define the responsibilities and authority of the Croatian Bureau of Statistics for collecting, processing and disseminating statistics are the following:

Official Statistics Act (NN, Nos. 103/03, 75/09, 59/12 and 12/2013 ‒ consolidated text)

Programme of Statistical Activities of the Republic of Croatia (NN, No. 69/13) https://www.dzs.hr/Hrv/about_us/Legals/Program%20statistickih%20aktivnosti%202018%20-%202020.pdf

Annual Implementation Plan of Statistical Activities of the Republic of Croatia 2019 (NN, No 19/2019) https://narodne-novine.nn.hr/clanci/sluzbeni/2019_02_19_405.html

Not requested.

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

Statistical data collected in this survey, according to the National Statistics Act (NN, 25/20.) is confidential and its purpose is restricted exclusively to statistical usage (with exception of registered researchers under specified conditions). Authorized interviewers are obligated to respect these restrictions. The results will be published in a cumulative form which prevents displaying data on individuals.

The following rules are used to identify sensitive cells in tabular data:

• Threshold rule: The cell is considered sensitive if the cell frequency is less than a pre-specified threshold value. In practice this means if data in certain cell in the table relates to less than a pre-specified number of reporting units, the cell is primary sensitive.
• Dominance rule: The cell is considered sensitive if the value of 1 largest contributor in the cell exceeds a pre-specified percentage of total value for that cell.

When a data cell in a table is suppressed by dropping its value based on a primary cell suppression rule, the value of that cell can still be calculated if the table provides totals. Secondary cell suppression is therefore needed to avoid such disclosures. Those values under primary and secondary protection are therefore suppressed for use.

There is a release policy and release calendar which is publicly accessible on CBS website (www.dzs.hr) 

Released data – by Publishing Programme – Publication Programme 2019 (pdf.)

According to the Release Date announced in the Publishing Programme and in the Calendar of Statistical Data Issues, publications of the Croatian Bureau of Statistics are released at 11:00 a.m. precisely thus abiding by the Principle of Timeliness of the European Statistics Code of Practice, i.e. standard daily time set for the release.

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

Accessibility and clarity refer to the simplicity and ease for users to access statistics using simple and user-friendly procedure, obtaining them in an expected form and within an acceptable time period, with the appropriate user information and assistance: a global context which finally enables them to make optimum use of the statistics.

See below.

-              Online database (containing all/most results) : not available

-              Analytical publication (referring to all/most results) : https://www.dzs.hr/Hrv_Eng/publication/2020/08-02-05_01_2020.htm

-              Analytical publication (referring to specific results, e.g. only for one sector or one specific aspect) : not available

Not available

Not requested.

Micro-data are not disseminated.

No other means of dissemination.

Not requested.

Methodological documents are published in First Release in paper form and in electronic version available on the website of the Croatian Bureau of Statistics.

The meta-information available together with the data published in official First Release – part “Notes on methodology” are information about Data sources, Coverage and comparability and short interpretation and analysis of results.

Not requested.

On the website of CBS there is a Quality chapter with QRs for different areas. One of them is CIS with QRs for CIS2014 and CIS2016

https://www.dzs.hr/Eng/international/Quality_Report/Quality_Report_Results/Quality_report_CIS%202012-2014.pdf

https://www.dzs.hr/Eng/international/Quality_Report/Quality_Report_Results/Quality_report_CIS%202014-2016.pdf

https://www.dzs.hr/Hrv/international/Quality_Report/Quality_Report_Results/Izvjestaj_kvalitete_CIS%202012-2014.pdf

https://www.dzs.hr/Hrv/international/Quality_Report/Quality_Report_Results/Izvjestaj_kvalitete_CIS%202014-2016.pdf

The survey is conducted by Croatian Bureau of Statistics which means that all data collected are confidential and will be used strictly for statistical purposes and will not be published as individual.

National questionnaire was prepared based on the harmonized survey questionnaire and other relevant documents. National CIS questionnaire includes all obligatory and optional questions, instruction and skips. It is basically translation of the harmonized survey questionnaire and it was changed minimally (we have added a subquestion on the legislation on GDPR affected enterprise’s innovation activities within Q. 3.17. and a question on the short description of the most important innovation).

After receiving a filled-in questionnaire, it was checked for logical and mathematical inconsistencies and missing data. In case of some illogical answers or missing data, the enterprises were contacted by telephone or e-mail.

Since the data collection mode was electronic (on-line) questionnaire, the data were automatically transferred into database. Web questionnaire includes some routines, skips and checks, but not too many. Some of the data collected by enterprises were crosschecked with data from existing administrative sources (data on turnover, size-class, age of enterprise).

The questionnaire was understood by respondents slightly worse than the previous one. As in previous waves, some enterprises had problems understanding concepts while answering couple of questions. The main remark concerned the length of the questionnaire and its complexity. Some enterprises have stated that the questionnaire requires more time to complete and a larger number of people involved in completing it from different departments. We also had a remark that the questionnaire covers the period from 2016 to 2018. It would make more sense if it was at the level of the business year. Several enterprises consider financial information a trade secret. Some variables do not correspond to those in the annual financial report, so it is very difficult to decide what it refers to.

The most problematic question was 3.10. as some enterprises cannot separate expenditures on innovation and R&D. Furthermore for some enterprises it was complicate to separate turnover of new or improved products into products that were not previously offered by any of enterprise’s competitors from identical or very similar products already offered by enterprise’s competitors.

The most confusing question was 4.6 training own staff because enterprises mostly include whole salary of staff trained.

Overall quality of the CIS methodology is satisfactory. There are however some weakness e.g. question about enterprise being part of group of enterprises. We have noticed that some reporting units do not understand this issue correctly. On the other hand, our colleagues from the Statistical Business Register (SBR) need to update HR data according to Eurostat and we believe that they have up-to-date data. For the next CIS wave we will take this data from SBR. 

One postal reminder was sent, and the other reminders were conducted by telephone or e-mail which resulted in response rate of 73.5%.

There are several users at national and international level with different needs with respect to the statistiacal data.

At the international level main user is the European Commissin with their DG's - DG GROW, DG RTD, Eurostat, as well as Innovation Union Scoreboard and Regional Innovation Scoreboard . They use data for systematic and user-oriented presentation of internationally comparable indicators on the Community Innovation Survey (for all Member States of the European Union) furthermore to provide a comparative assessment of the innovation performance of EU Member States (Innovation Union Scoreboard) and assessing the innovation performance of European regions on a limited number of indicators (Regional Innovation Scoreboard). 

The users at national level will be listed under 12.1.1.

A targeted measurement of user satisfaction specifically with the data from the survey on innovation activities of enterprises is not conducted.

The survey was conducted by the Croatian Bureau of Statistics and was completely in accordance with the survey entitled "Community Innovation Survey", which is conducted in the European Union every two years. The survey covers all mandatory and optional variables laid down in Commission Regulation (EC) No 995/2012 of 26 October 2012 implementing 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. All mandatory and voluntary variables were collected. All statistics produced on innovation are available.

Not requested.

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).

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.

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

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)
[2] = Coefficient of variation for the turnover of product innovative enterprises with new or improved products (TUR_PRD_NEW_MKT), as a percentage of total turnover of product innovative enterprises [TUR18,INNO_PRD].
[3] = Coefficient of variation for percentage of product and/or process innovative enterprises (incl. enterprises with abandoned and or on-going activities) involved in any innovation co-operation arrangement [COOP_ALL,INN], as a percentage of innovative enterprises (INN).

Taylor linearization was used for variance estimation by applying SAS procedure Surveymeans for calculating variance estimation. Sample design and weighting has been taken into account because it is required by mentioned SAS procedure.

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.

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.

Not requested.

Not requested.

Companies that were liquidated during the period are deleted from the sample and target population, unless it was decided that their liquidation was so late in the survey period that they should be included in the target population.

Effects of coverage errors are incorporated in the variance estimation, in a way that in non-response adjustment procedure small, medium and large enterprises are treated in different manner. Non-response weights for small enterprises are calculated as the ratio of the number of selected units and the number of units that participated in the survey, while the non-response weights for medium and large enterprises are calculated as the ratio of the eligible units and the number of units that participated in the survey. The reason for this is that we assume that small enterprises that no longer exist are easily replaced with new small enterpise, while medium and large enterprises could not be easily replaced. In that way we imputed the response for small enterprises, altough they no longer exist.

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.

Measures which were taken to reduce measurements errors started with designing the national questionnaire. We have put a lot of efforts to translate, as good as it was possible, some terms and concepts to Croatian (e.g. pooling, cross-licensing, co-creation, crowd-sourcing, open business-to-business platforms, open-source software, cross-functional work groups) and we wrote clear methodological guidelines. The on-line questionnaire was tested by CBS employees and we have covered most of fore coming situation and to be ready to avoid possible errors. As well, we have tested all skips and controls in order to ensure better quality of collected data. Due to unexpected circumstances that influenced all activities of the project from (changes of project leader, new member of project team, new internal organizational structure of CBS and the relocation of the project team) before start of data collection, we organized a quick training to our new member of the project team and agreed common approach to all issues that could be confusing, questionable or unclear to reporting units.

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) 

See below.

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.

Not available.

See below.

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).

There were no missing values i.e. item non-response. The enterprises that provided answers were contacted as many times as needed to get answers to all questions, either by email or by phone. 

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)
 

There were no missing values i.e. item non-response. The enterprises that provided answers were contacted as many times as needed to get answers to all questions, either by email or by phone. 

 Not available.

Not requested.

Timeliness and punctuality refer to time and dates, but in a different manner.

The timeliness of statistics reflects the length of time between data availability and the event or phenomenon they describe.

Timeliness of national data – date of first release of national level : 

30/09/2020

Not requested.

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.

Date of transmission of complete and validated data to Eurostat (Number of days between that data and 30 June 2020) : 

15/10/2020 (45 days delayed due to difficult working conditions caused by the COVID-19 pandemic.)

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.

We did not have any problems of comparability between 2 regions of the country.

Not requested.

Methodological deviations from the CIS Harmonised Data Collection (HDC)

Methodological deviations from the CIS Harmonised Data Collection (HDC)

Due to important methodological changes in CIS 2018 driven by Oslo Manual 2018, the data 2018 cannot be directly compared with previous CIS waves.

Not requested.

See the comparison between SBS and CIS data in the section 15.3.3 below.

Not requested.

Not requested.

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 employees

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

Not requested.

Confidential information on the production cost of the CIS.

Not requested.

Not requested.

Not requested.

See below:

The official, up-to-date, statistical business register of Croatian Bureau of Statistics was used as a frame (situation at the end of 2018). The frame consisted of 11313 units with 10 or more employees and with main activity in core target population and additional target population (NACE 41-43, 55-56, 68) according to NACE Rev. 2.

There are 7610 units with 10 or more employees and with main activity in core target population in the sampling frame.

The target population was broken down into similar structured subgroups or strata, so, stratification is used. Appropriate stratification will normally give results with smaller sampling errors than a non-stratified sample of the same size and will make it possible to ensure that there are enough units in the respective domains to produce results of acceptable quality.

The stratification variables that are used for the CIS 2018, i.e. the characteristics used to break down the sample into similarly structured groups were:

• Regional sampling according to NUTS2 regions
• Enterprise size according to the number of employees
• The economic activities (in accordance with NACE)

In that way, 280 strata were formed.

The selection of the sample was based on random sampling techniques, with known selection probabilities, applied to strata.

So, the sampling frame was divided in 280 strata according to the 2 digit NACE, 3 size classes of number of employees and 2 regions at NUTS 2 level. All units with 50 or more employees were selected with certainty. The sample for units with 10 – 49 employees was stratified simple random sample with known selection probabilities for all units. The number of selected units in the stratum with enterprises with 10 - 49 employees was calculated in proportion to the number of units in the stratum in population. After that, we decreased calculated number of units in the sample for activities such as construction, accommodation and food service activities, manufacture of bread and real estate activities, due to too big proportion such units in the whole sample and as we wanted to increase number of sampling units from other strata. Optimal allocation was not used because of unreliable estimates of variance of strata from CIS 2010. Estimates of variance were unreliable as there was small number of units in some strata.

Variables and indicators filled or prefilled from other sources.

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.

Data collection method used was electronic (on-line) questionnaire which was computer-assisted in a minimum way. On-line version matched harmonised questionnaire visually and methodologically.

The survey is mandatory.

Survey type was combination of sample survey and census data.

Survey type was combination of sample survey and census data.

We have sample of small enterprise (10-49 employees) and enterprises with 50 - 249 employees and 250 or more employees  are covered by complete enumeration.

The sample for units with 10 – 49 employees was stratified simple random sample with known selection probabilities for all units. 

Enterprises with 50 - 249 employees  and 250 or more employees  are covered by complete enumeration.

Enterprises with 50 - 249 employees  and 250 or more employees  are covered by complete enumeration.

Data collection method

Not requested.

Operations performed on data to derive new information according to a given set of rules.

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)

Imputation rate for metric variables by NACE categories and for enterprises with 10 or more employees: there was no 'item no response' so no imputation was 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)

Weights calculation method for sample surveys

The survey results are weighted in order to adjust for the sampling design and for unit non-response to produce valid results for the target population.

The basic method for adjusting for different probabilities of selection used in the sampling process is to use the inverse of the sampling fraction, using the number of enterprises. This was based on the figure Nh/nh where Nh is the total number of enterprises in stratum h of the population and nh is the number of enterprises in the realised sample in stratum h of the population, assuming that each unit in the stratum had the same inclusion probability. This automatically adjusts the sample weights of the respondents to compensate for unit non-response. So, we have used the basic method for adjusting for the sampling design and for unit non-response. We calculated weights only by using module SAS-base.

At the end we have also calculated ratio estimator and its effect has been also incorporated in final weights. We have first divided population in 2 groups (2 regions and 2 groups according to number of employees - small enterprises with less than 50 employees and other group with 50 or more employees). Then, number of employees was calculated for each group and it was used in calculation. After that, we have included also its effect in final weights and exact number of employees which was obtained in the frame.

We did not use standard calibration methods and software. We have only calibrated data according to number of employees from sampling frame (business register). We have tried to calculate also ratio weights, but population was too overestimated with it. Reason for that is that we have used weighted number of employees according to design weights, but after that, we have used final weight (product of design weights and response weights) and in that way we have achieved number of employees as it is in the frame. In some way, we can say now that population is calibrated according to number of employees in each.

Not requested.

As already mention the survey covers all mandatory and optional variables and follows all Eurostat methodological recommendations (skips, logical and mathematical control etc. built into the on-line questionnaire). Beside target population which covers active enterprises ‒ legal entities and natural persons employing 10 or more persons that are, according to the main activity, classified in sections B, C, D, E, F, G, H, I, J, K, L, M of NACE Rev. 2 we added some more service activities in the survey because of their significance in the Croatian economy (we added Construction (41 – 43), Accommodation and food service activities (55 – 56) and Real estate activities (68)) and we also surveyed NACE 59 and 60. Futrhermore, within the question 3.17. we added the impact of GDPR law on enterprises’ innovation activities.

As recommended we extracted the enterprise identification from the Statistical Business Register as well some variables collected as part of Section 4 – average number of employees; total turnover; in which year was your enterprise established; in 2018, was your enterprise part of  - a) an enterprise group with the head office located in HR and if “yes” are all of the enterprises of the group located in HR, b) an enterprise group with the head office located abroad and if “yes” inserted country code according to ISO standard for country in which head office is located.

We have experienced that reporting units do not read instructions whether they are written with or after the question.