ROMANIA

NATIONAL INSTITUTE OF STATISTICS

DEPARTMENT OF SHORT TERM ECONOMIC INDICATORS STATISTICS

16 Libertatii Bvd, Bucharest 5, Romania

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

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

 No, national particularities; the core NACE activities only

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 national particularities

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.

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). 

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

According NUTS 2016 classification, CIS collect and disseminate regional information at NUTS 2 level (Romanian 8 basic regions for the application of regional policies).

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.

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

Not requested.

Fixed text modified: CIS data are transmitted to Eurostat via EDAMIS using the secured transmission system.

 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.

The rules that have been applied for aggretate tables were the following: the rule of three, the dominance and the precision.

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.

https://insse.ro/cms/files/catalog/Catalogul_publicatiilor_INS_2020.pdf - for  publications

https://insse.ro/cms/ro/comunicate-de-presa-view for  press  release

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.

CIS is disseminated at two-year interval in even 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 publication(containing all/most results) : 

                  "Innovation in business enterprises” 

                   https://insse.ro/cms/sites/default/files/field/publicatii/inovatia_in_intreprinderile_din_mediul_de_afaceri_2018.pdf

-              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) : 

http://statistici.insse.ro:8077/tempo-online/#/pages/tables/insse-table

Available also in Romanian language format.

Not requested.

See below

Sectoral indicators, more detailed NACE activities, SMEs regional data, high-tech innovative enterprises, competitiveness indicators, sustenable indicators, logistics indicators.

Not requested.

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.

http://statistici.insse.ro:8077/tempo-online/

Not requested.

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.
Data are accompanied by detailed metadata. To all other questions regarding the methodology or the manner of designing the tables and the data we respond whenever necessary.

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

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.

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 2018 survey and meets the requirements of the six quality dimensions according with European Statistical System and other important characteristics.
Strengths: - Use of a common questionnaire and a methodology for all countries;
- Experiences and knowledge got from the other waves of CIS survey;
- Compliance with user requirements and providing all necessary data;
- Data collection through online portal  questionnaires which decrease the number of errors in data;
- Comparability of data with other two important surveys: SBS survey and R&D survey.
- Punctuality of time schedule of effective publication

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 methodolgy for computing the weighting coefficients.

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, as laid down in the 3rd edition of Oslo Manual (2005 edition), in order to achieve comparable, harmonised and high quality results for EU Member States, EFTA countries, Candidates and Associated countries

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).

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.

National survey includes all indicators of European questionnaire, CIS 2018. We have no missingness issues.

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).

Varianceh = (Ph*(1-Ph)*(Nh-mh))/( Nh *( mh -1))
Varianceh= variance of the stratum h
Where: Nh = target population in stratum h
mh= number of responding units in the realised sample, in stratum h
Ph= proportion of stratum h, meaning the ratio between the sum of weightnr, for each
indicator, and the target population of the stratum (Nh).
Then we have computed the Sh (Standard Deviation for each stratum), the coefficient of
variance and the aggregates.

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.

Estimation of coverage was computed with the initial coefficient of extraction using the turnover

Under covered groups (<100%) – section B (99.3%), section C (99.5%), section D (99.1%), section E (98.9%), in Core NACE  46 (96.3%), section J (97.7%),  in Core NACE 73 (97.5%).

Over covered groups (>100%) – section H (101.8%), in Core NACE 71 (102.0%L),  in Core NACE  72 (104.1%)

100% covered groups section K (100.0%).

CVs incorporate the effects of coverage errors.

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.

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

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:

• 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.

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.

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.

A number of 527 units were removed from the sample because they don't belong to target population after inspection of their characteristics.

3 recalls

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).

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)
 

The methods used for data entry were data keying and responses through online questionnaires

To check variables, correlations between chapters and items were applied.
An edit rate is 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 :  February 24, 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) : 30 june 2020

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.

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.

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 national business register, named REGIS was used.

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.
Number of strata used was 945.

Sampled units: all enterprises with <250 persons employed;

Census :  all enterprises with 250 or more persons employed.

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.

See below

The survey is mandatory.

Data are collected trough a combination of  a census and a sample survey.

The population classes covered by sampling are the following: 10-49; 50-249.
The population class covered by census was: 250+

The criterion for census was the size class: all units with 250 and more employees were surveyed.

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: 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)

Weights calculation method for sample surveys

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.
There were computed 3 coefficients for turnover, number of enterprises and number of employees.

Not requested.