Reference metadata describe statistical concepts and methodologies used for the collection and generation of data. They provide information on data quality and, since they are strongly content-oriented, assist users in interpreting the data. Reference metadata, unlike structural metadata, can be decoupled from the data.
The quarterly data are broken down by economic activity (at section level) in accordance with NACE Rev. 2 - Statistical classification of economic activities in the European Community.
2.3. Coverage - sector
All economic activities defined by NACE Rev. 2, except the activities of households as employers and the activities of extraterritorial organisations and bodies.
2.4. Statistical concepts and definitions
Job vacancy
In accordance with the CSB methodology, job vacancy is defined as a new or existing salaried post which is vacant or will be vacant in the nearest time and employer is taking active steps to find a suitable employee outside own enterprise and the post may be filled immediately or within the nearest time.
Occupied post
Occupied post is a paid post to which the employee has been assigned. The number of occupied posts comprises both full time and part time employees, for which accounts of working time must be kept according to the Labour Law, as well as those employees who do not have a working time record.
Job vacancy rate
Share of job vacancies in the total number of jobs. The total number of jobs is the sum of occupied jobs and job vacancies.
2.5. Statistical unit
Enterprise
2.6. Statistical population
Enterprises with one and more employees
2.7. Reference area
The whole territory of the country
2.8. Coverage - Time
Data for the aggregated NACE sections B-S is available from 2005; data for the other individual and aggregated NACE sections from 2008.
At the end of 2015 the improvements in job vacancies data collection process were introduced resulting the break in time series. In order to ensure comparability of data over time, the time series at the level of sections (letters) of Statistical Classification of Economic Activities NACE rev. 2 have been recalculated up to the 4th quarter of 2015. Data by NACE divisions (2-digits), sector, region and major occupational group was not recalculated and is not comparable prior the 1st quarter of 2016.
2.9. Base period
Not applicable
3.1. Source data
Identification of the source of the data
Data is collected from the quarterly labour survey.
Coverage
Geographical
Whole country (Latvia)
NACE
NACE Rev. 2 by kind of activity A - S
Enterprise size
Enterprises with one and more employees
Definition of the statistical unit
All active businesses, budgetary institutions, foundations, associations and funds. Peasant and fishermen’s farms, religious organisations, rural craftsmen’s businesses, family-owned enterprises, natural person are not included.
Remarks
Sampling design
Base used for the sample
The sampling frame was made at the start of november 2023 from Statistical Business Register.
Sampling design
Sampling design is one stage stratified simple random sampling. 108 different NACE domains divided into 6 different size classes and 3 different classes of sector (108 x 6 x 3 sampling cells).
Group of sector
Size group by employees
0-9
10-13
14-19
20-49
50-99
100+
1
C/N
C/S
C/S
C/S
C/S
C
2
C
C
C
C
C
C
3
N
S
S
S
S
C
C – census
S – sample
N – not sampled.
Classes of sector:
1 – Public;
2 – General government;
3 – Private.
Retention/renewal of sampling units
During the year “large” statistical units (with 100 and more employees) are included in the sample. No statistical units are excluded of the sample.
Last day of the quarter (for 1st – 31 March, 2nd – 30 June, 3rd – 30 September, 4th – 31 December)
3.3. Data collection
Brief description of the data collection method(s)
Remarks
Data is collected from the quarterly labour survey using three questionnaires:
for local municipalities budget authorities (group 2): 2-Labour-Local Municipalities (Pārskats par darbu 2-darbs-pašvaldības),
for state budget authorities, state and municipal companies and foundations, private companies with 100 and more employees (groups 1,2,3): 2-Labour (Pārskats par darbu 2–darbs),
for the rest enterprises of the sample (group 3): 2-Labour short (Pārskats par darbu 2-darbs (īsā)).
Since 2022 for occupied posts administrative data of the State Revenue Service is directly used without applying imputation. Data on occupied posts for municipalities is obtained via the quarterly labour survey questionnaire.
Data on labour of the most municipal institutions are compiled by the central accounting offices. To ensure distribution by economical activities NSI requests those to submit data divided by KAU by NACE divisions. Otherwise, all data would be included in the main activity NACE O.
Questionnaires are available (in Latvian) on the site of CSB CSP katalogs.
Respondents submit data in Electronic Data Collection (EDC) System (in Latvian) CSP Account where data are also validated. Additional validations are used in the internal data collection system. Pre-printed data on job vacancies of the State Employment Agency is also used for validations.
3.4. Data validation
Not applicable.
3.5. Data compilation
Brief description of the weighting method
Weighting dimensions
Sampling design is one stage stratified simple random sampling. 108 different NACE domains divided into 6 different size classes and 3 different classes of sector (108 x 6 x3 sampling cells).
Group of sector
Size group by employees
0-9
10-13
14-19
20-49
50-99
100+
1
1/N
1/3
1/2
1/2
1/2
1
2
1
1
1
1
1
1
3
N
3
2
2
2
1
1=Method 1; 2=Method 2; 3=Method 3; N=Method 4
In the first sector (Public sector) in size group 0-9 state and municipal government foundations and companies have 1 method
Method 1
All respondent units have weight equal to 1.
Method 2
The weights are calculated by formula:
wh=Nh*/nRh
where wh is unit weight in stratum h, Nh is population size (number of economically active units) in stratum h and nRh is number of respondents in stratum h.
Method 3
The weights are calculated by formula: wh10:13=(Nh10:13+Nh1:9)/nRh10:13
where
wh10:13 is unit weight in stratum h for size class 10-13 employees,
Nh10:13 is population size in stratum h for size class 10-13 employees,
Nh1:9 is population size in stratum h for size class 1-9 employees,
nRh10:13 is number of respondents in stratum h for size class 10-13 employees.
Quality of statistics is assessed in accordance with the existing requirements of external and internal regulatory enactments and in accordance with the established quality criteria.
Regulation (EC) no 223/2009 of the European Parliament and of the Council on European statistics states that European Statistics European statistics shall be developed, produced and disseminated on the basis of uniform standards and of harmonised methods. In this respect, the following quality criteria shall apply: relevance, accuracy, timeliness, punctuality, accessibility, clarity, comparability and coherence.
CSB has introduced Quality Management System (QMS). The system is directed towards providing high user satisfaction and ensuring compliance with regulatory enactments. Based on the structure of Generic Statistical Business Process Model (GSBPM), QMS defines and at the level of procedures describes processes of statistical production as well as sets the persons responsible for the monitoring of processes at all stages of the statistical production. QMS defines the sequence how processes are implemented (i.e., activities to be performed (incl. verifications of processes and statistics, sequence and implementation requirements thereof, as well as persons responsible for the implementation)), procedures used in the evaluation of processes and statistics, as well as any improvements needed.
Since 2018, QMS of the CSB has been certified by the standard ISO 9001:2015 “Quality Management Systems. Requirements” (certified scope: Production of official statistics – planning, development, data acquisition, processing, analysis and dissemination).
5.1. Relevance - User Needs
Description of the national users and their main needs
Remarks
Main users:
Government (Ministry of Economics, Ministry of Welfare);
Banks (Bank of Latvia, commercial banks);
Research centers, scientists;
Students;
Mass media.
Data on job vacancies are mainly used to obtain information in country by kind of activity to evaluate economical situation and its development.
5.2. Relevance - User Satisfaction
Extent to which the needs of national users are satisfied (voluntary)
Remarks
CSB collects quarterly data by main occupational groups, but users are also interested in more detailed occupational level.
5.3. Completeness
Description of missing variables and missing breakdowns of the variables
Report progress on the implementation measures regarding quarterly job vacancies statistics of Regulation (EC) No 453/2008, including :
a detailed plan and timetable for completing implementation
a summary of the remaining deviations from EU concepts
There are no missing variables or breakdowns.
All required measures are implemented.
5.3.1. Data completeness - rate
100%
6.1. Accuracy - overall
Not applicable.
6.2. Sampling error
See below
6.2.1. Sampling error - indicators
Coefficient of variation (taking into account the sampling design) or estimated sampling error for the number of job vacancies (see guidelines).
Information on variables with non-negligible measurement and processing errors
Information on main sources of (non-negligible) measurement and processing errors and, if available, on methods applied for correction
Estimation bias: An assessment of the non-sampling errors, in terms of the absolute number of vacant posts, for the total number of job vacancies and, where possible, for aggregation level of NACE Rev. 2 specified in Annex 1 to this Regulation and size classes (1-9, 10 + employees).
Remarks
Not relevant
Not relevant
Bias is not estimated.
6.3.1. Coverage error
Description of any difference between the reference population and the study population
Description of classification errors
Description of any difference between the reference dates and the reference quarter
Any other relevant information
Not available
For some enterprises in the sample the main economic activity can be changed during the time.
Not available
6.3.1.1. Over-coverage - rate
Overcoverage in 2023:
1st quarter – 1.0%.
2nd quarter – 1.0%.
3rd quarter – 1.6%.
4th quarter – 2.3%.
6.3.1.2. Common units - proportion
Not applicable.
6.3.2. Measurement error
The definition of job vacancy is not always clear for respondents.
6.3.3. Non response error
See below
6.3.3.1. Unit non-response - rate
Unit unweighted response rate
1st quarter – 91%;
2nd quarter – 91%;
3rd quarter – 90%;
4th quarter – 91%.
6.3.3.2. Item non-response - rate
Not applicable.
6.3.4. Processing error
See below
6.3.4.1. Imputation - rate
Item imputation rate and methods and, where possible, the effect of imputation on the estimates for the variables transmitted
Imputation is not conducted.
6.3.5. Model assumption error
If modelling is used, include a description of the models used. Particular emphasis should be given to models for imputation or grossing-up to correct for unit non-response.
The assumption is made, that the units with 1-9 employees in average have the same number of job vacancies as the units with 10-13 employees.
6.4. Seasonal adjustment
Brief description of seasonal adjustment procedures, in particular with regard to the European Statistical System guidelines on seasonal adjustment which have been endorsed and supported by the SPC.
Data on job vacancies are seasonally adjusted.
The Central Statistical Bureau of Latvia performs seasonal adjustment in accordance with the European Statistical System (ESS) seasonal adjustment guidelines.
Software used: JDemetra+ Method used: TRAMO/SEATS
A time series is a sequence of observations collected at regular time intervals, for example, a monthly /quarterly time series. It characterises indicator changes or development thereof. Seasonality and calendar effects are present in a large number of economic time series.
Seasonality or seasonal fluctuations of time series are those movements, which recur with similar intensity in the same season each year. Seasonally adjusted data do not include seasonal fluctuations and calendar effects, so it is possible to compare, for example, current quarterly data with previous quarterly data.
Calendar effects cover influence of calendar on time series. It is the number of different working days in months /quarters; distribution of days of the week; the impact of the leap year on changes of the indicator. The Central Statistical Bureau of Latvia uses Latvian specific calendar regressors1, which are calculated in accordance with the Law on Holidays, Remembrance and Celebration Days2 and JDemetra+ documentation3. Calendar adjustment is performed only for those time series for which the calendar effect is statistically significant and economically explainable. Calendar adjusted data do not include calendar effects and are used to compare, for example, data for the current quarter with data for the corresponding quarter of the previous year.
Revisions are expected when new data are added to the time series, as the whole seasonally adjusted time series is recalculated. Once a year, the time series models are reviewed - that is, the models are checked for compliance with the time series and the time series models are improved if necessary. Larger data revisions are potentially expected for the next month or quarter after the model review.
Revision Policy is an important component of good governance practice addressed more and more often in the international statistical society. The objective of the Revision Policy is to lay down the order of review or revision of the prepared and published data. The first chapter of the present document explains the terms applied in the Revision Policy, the second chapter shortly characterises the CSB Revision Policy, whereas the third chapter stipulates the revision cycle of the statistical data produced by the CSB.
Revision Policy is now being updated.
6.6. Data revision - practice
Provide a revision history, including the revisions in the published number of job vacancies and a summary of the reasons for the revisions.
During the reference year revision is made once – at the end of reference year for the 1st, 2nd and 3rd quarter.
Data is revised in line with the routine data revisions defined in the CSB Revision Policy guidelines, as new active enterprises and institutions are added to the population of the statistical units surveyed, kinds and sectors of economic activities of enterprises are specified, additional or specified information from respondents or updated data on occupied posts from administrative data sources are received.
The data revisions for the previous quarters are allowed, obligatory and accepted by the CSB if the data delivered by the enterprises and institutions in the current quarter do not correspond to the data of the previous quarter due to mistakes.
Information on the time span between the release of data at national level and the reference period of the data.
Final data for every quarter are available 75 days after the reference period.
7.1.2. Time lag - final result
Not applicable.
7.2. Punctuality
See below.
7.2.1. Punctuality - delivery and publication
Deadlines for the respondents to reply, also covering recalls and follow-ups
Period of the fieldwork
Period of data processing
Dates of publication of first results
Remarks
Deadline is 15 days after the end of each quarter + 25 days for recalls and follow-ups.
1 month
60 days after the reference period.
75 days after the reference period.
Data are always published according to release date.
8.1. Comparability - geographical
Information on differences between national and European concepts, and — to the extent possible — their effects on the estimation.
Common methodology is used as it is defined in regulations (EC) No 1062/2008 and Commission Regulation (EC) No 19/2009 of 13 January 2009 implementing Regulation (EC) No 453/2008.
8.1.1. Asymmetry for mirror flow statistics - coefficient
Not applicable.
8.2. Comparability - over time
Information on changes in definitions, coverage and methods in any two consecutive quarters, and their effects on the estimation.
Remarks
See below
8.2.1. Length of comparable time series
Data on job vacancies, job vacancy rate and occupied posts are available since 2005.
At the end of 2015 the improvements in job vacancies data collection process were introduced resulting the break in time series. In order to ensure comparability of data over time, the time series at the level of sections (letters) of Statistical Classification of Economic Activities NACE rev. 2 have been recalculated up to the 4th quarter of 2015. Data by NACE divisions (2-digits), sector, region and major occupational group was not recalculated and is not comparable prior the 1st quarter of 2016.
8.3. Coherence - cross domain
Comparisons of data on the number of vacant jobs from other relevant sources when available, in total and broken down by NACE at section level when relevant, and reasons if the values differ considerably.
Another source which collects information on job vacancies in Latvia is the State Employment Agency (SEA). There is no obligation for employers to register vacancies at SEA, and only part of the enterprises does it on voluntary basis. The only exceptions defined in national regulations are cases when employers want to hire employees from countries out of EU, registration of such vacancies are mandatory. Enterprises do not inform SEA on filling or annulment of the vacancy, as well as informs SEA only on the part of jobs vacant in the enterprise, whereas labour survey of CSB obtain actual information on job vacancies at the end of the quarter.
Since January 1 2016 the information about vacancies of enterprises in which the state or municipality share in the capital individually or in total exceeds 50 percent have to be published on the vacancy portal of the State Employment Agency, but vacancies of municipality institutions - since January 1, 2019.
Description of and references for metadata provided
References for core methodological documents relating to the statistics provided
Description of main actions carried out by the national statistical services to inform users about the data
Remarks
CSB has introduced Quality Management System (QMS). The system is directed towards providing high user satisfaction and ensuring compliance with regulatory enactments. Based on the structure of Generic Statistical Business Process Model (GSBPM), QMS defines and at the level of procedures describes processes of statistical production as well as sets the persons responsible for the monitoring of processes at all stages of the statistical production. QMS defines the sequence how processes are implemented (i.e., activities to be performed (incl. verifications of processes and statistics, sequence and implementation requirements thereof, as well as persons responsible for the implementation)), procedures used in the evaluation of processes and statistics, as well as any improvements needed.
Since 2018, QMS of the CSB has been certified by the standard ISO 9001:2015 “Quality Management Systems. Requirements” (certified scope: Production of official statistics – planning, development, data acquisition, processing, analysis and dissemination).
Information on definitions and methodology can be found at Official statistics portal Labour market/Reference metadata/Labour market/Occupied posts and job vacancies
The Projects Documentation system (only in Latvian).
Prepared information on website about the newest data in databases, published press release calendar on website for the year, publication in the website on the day when data are available, message in twitter about latest news, news by e-mail (need to subscribe on website).
9.7.1. Metadata completeness - rate
Not applicable.
9.7.2. Metadata - consultations
Not applicable.
Not applicable.
11.1. Confidentiality - policy
Confidentiality of individual data is protected by Statistics Law:
Section 7. Competence of the Statistical Institution in Production of Official Statistics
(2) The statistical institution shall:
8) ensure statistical confidentiality in accordance with the procedures laid down in this Law;
Section 17. Data Processing and Statistical Confidentiality
Section 19. Dissemination of Official Statistics
(1) The statistical institution shall disseminate official statistics in a way that does not allow either directly or indirectly identify a private individual or a State institution in cases other than those laid down in Section 25 of this Law.
(2) The statistical institution shall publish the official statistics which have been produced within the framework of the Official Statistics Programme in a publicly available form and by a predetermined deadline on the portal of official statistics. Until the moment of publication of official statistics this statistics shall not be published.
11.2. Confidentiality - data treatment
Disclosure rules: Brief description of when data have to be deleted for reasons of confidentiality
Data are published at the aggregate level at which it is not confidential.
CSB has introduced Quality Management System (QMS). The system is directed towards providing high user satisfaction and ensuring compliance with regulatory enactments. Based on the structure of Generic Statistical Business Process Model (GSBPM), QMS defines and at the level of procedures describes processes of statistical production as well as sets the persons responsible for the monitoring of processes at all stages of the statistical production. QMS defines the sequence how processes are implemented (i.e., activities to be performed (incl. verifications of processes and statistics, sequence and implementation requirements thereof, as well as persons responsible for the implementation)), procedures used in the evaluation of processes and statistics, as well as any improvements needed.
Since 2018, QMS of the CSB has been certified by the standard ISO 9001:2015 “Quality Management Systems. Requirements” (certified scope: Production of official statistics – planning, development, data acquisition, processing, analysis and dissemination).
In accordance with the CSB methodology, job vacancy is defined as a new or existing salaried post which is vacant or will be vacant in the nearest time and employer is taking active steps to find a suitable employee outside own enterprise and the post may be filled immediately or within the nearest time.
Occupied post
Occupied post is a paid post to which the employee has been assigned. The number of occupied posts comprises both full time and part time employees, for which accounts of working time must be kept according to the Labour Law, as well as those employees who do not have a working time record.
Job vacancy rate
Share of job vacancies in the total number of jobs. The total number of jobs is the sum of occupied jobs and job vacancies.
Enterprise
Enterprises with one and more employees
The whole territory of the country
Not Applicable
Not applicable.
Not Applicable
Brief description of the weighting method
Weighting dimensions
Sampling design is one stage stratified simple random sampling. 108 different NACE domains divided into 6 different size classes and 3 different classes of sector (108 x 6 x3 sampling cells).
Group of sector
Size group by employees
0-9
10-13
14-19
20-49
50-99
100+
1
1/N
1/3
1/2
1/2
1/2
1
2
1
1
1
1
1
1
3
N
3
2
2
2
1
1=Method 1; 2=Method 2; 3=Method 3; N=Method 4
In the first sector (Public sector) in size group 0-9 state and municipal government foundations and companies have 1 method
Method 1
All respondent units have weight equal to 1.
Method 2
The weights are calculated by formula:
wh=Nh*/nRh
where wh is unit weight in stratum h, Nh is population size (number of economically active units) in stratum h and nRh is number of respondents in stratum h.
Method 3
The weights are calculated by formula: wh10:13=(Nh10:13+Nh1:9)/nRh10:13
where
wh10:13 is unit weight in stratum h for size class 10-13 employees,
Nh10:13 is population size in stratum h for size class 10-13 employees,
Nh1:9 is population size in stratum h for size class 1-9 employees,
nRh10:13 is number of respondents in stratum h for size class 10-13 employees.
Data is collected from the quarterly labour survey.
Coverage
Geographical
Whole country (Latvia)
NACE
NACE Rev. 2 by kind of activity A - S
Enterprise size
Enterprises with one and more employees
Definition of the statistical unit
All active businesses, budgetary institutions, foundations, associations and funds. Peasant and fishermen’s farms, religious organisations, rural craftsmen’s businesses, family-owned enterprises, natural person are not included.
Remarks
Sampling design
Base used for the sample
The sampling frame was made at the start of november 2023 from Statistical Business Register.
Sampling design
Sampling design is one stage stratified simple random sampling. 108 different NACE domains divided into 6 different size classes and 3 different classes of sector (108 x 6 x 3 sampling cells).
Group of sector
Size group by employees
0-9
10-13
14-19
20-49
50-99
100+
1
C/N
C/S
C/S
C/S
C/S
C
2
C
C
C
C
C
C
3
N
S
S
S
S
C
C – census
S – sample
N – not sampled.
Classes of sector:
1 – Public;
2 – General government;
3 – Private.
Retention/renewal of sampling units
During the year “large” statistical units (with 100 and more employees) are included in the sample. No statistical units are excluded of the sample.
Information on differences between national and European concepts, and — to the extent possible — their effects on the estimation.
Common methodology is used as it is defined in regulations (EC) No 1062/2008 and Commission Regulation (EC) No 19/2009 of 13 January 2009 implementing Regulation (EC) No 453/2008.
Information on changes in definitions, coverage and methods in any two consecutive quarters, and their effects on the estimation.
