Job vacancy statistics (jvs)

National Reference Metadata in ESS Standard for Quality Reports Structure (ESQRS)

Compiling agency: Institute for Employment Research (IAB) of the Federal Employment Agency

Eurostat metadata

Reference metadata

1. Contact
2. Statistical presentation
3. Statistical processing
4. Quality management
5. Relevance
6. Accuracy and reliability
7. Timeliness and punctuality
8. Coherence and comparability
9. Accessibility and clarity
10. Cost and Burden
11. Confidentiality
12. Comment
Related Metadata
Annexes (including footnotes)

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

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1. Contact

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1.1. Contact organisation

Institute for Employment Research (IAB) of the Federal Employment Agency

1.2. Contact organisation unit

Department "Labour Market Processes and Institutions"

Institute for Employment Research (IAB) of the Federal Employment Agency

1.5. Contact mail address

Institute for Employment Research (IAB)
Federal Employment Agency

Regensburger Strasse 100
D-90478 Nuremberg
Germany

2. Statistical presentation

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2.1. Data description

Job vacancy statistics (JVS) provide information on the level and structure of labour demand. The country transmits to Eurostat the quarterly data on the number of job vacancies and the number of occupied posts as well as provides the quality report under the JVS framework regulation and the two implementing regulations: the implementing regulation on the definition of a job vacancy, the reference dates for data collection, data transmission specifications and feasibility studies, as well as the implementing regulation on seasonal adjustment procedures and quality reports.

2.2. Classification system

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

A 'job vacancy' is defined as a paid post that is newly created, unoccupied, or about to become vacant:

(a) for which the employer is taking active steps and is prepared to take further steps to find a suitable candidate from outside the enterprise concerned; and

(b) which the employer intends to fill either immediately or within a specific period of time.

‘Active steps to find a suitable candidate’ include:

- notifying the job vacancy to the public employment services,

- contacting a private employment agency/head hunters,

- advertising the vacancy in the media (for example internet, newspapers, magazines),

- advertising the vacancy on a public notice board,

- approaching, interviewing or selecting possible candidates/potential recruits directly,

- approaching employees and/or personal contacts,

- using internships.

'Specific period of time’ refers to the maximum time the vacancy is open and intended to be filled. That period shall be unlimited; all vacancies for which active steps are continuing on the reference date shall be reported.

An 'occupied post’ means a paid post within the organisation to which an employee has been assigned.

2.5. Statistical unit

Local unit

2.6. Statistical population

All establishments with at least one or more employees

2.7. Reference area

All establishments located in the territory of Germany

2.8. Coverage - Time

Quarterly data from 2010Q4 onwards

2.9. Base period

Not applicable

3. Statistical processing

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3.1. Source data

Identification of the source of the data	IAB-Job Vacancy Survey
Coverage
- Geographical	The whole territory of the country
- NACE	NACE sections A-S
- Enterprise size	Establishments with one and more employees
Definition of the statistical unit	Local unit
Sampling design
Base used for the sample	For the postal survey in the fourth quarter of 2022, a sample of about 135,000 local units is drawn randomly from the official business register of the Federal Employment Agency. The sampling ratio is 6.2 % of the population of local units with registered employees in Germany (Table 1). The sample is stratified by: – 2 regions (East and West Germany) – 24 sectors (NACE Rev. 2 since IV/2010) – 7 size classes The number of local units in every cell of the sample matrix is chosen regarding the participation rates in previous surveys to ensure a sufficient number of responses. The probability of having an open vacancy is especially low in very small units. On the other hand, very small units account for about 30 per cent of all vacancies. For this reason, the absolute sample size is larger in smaller-sized classes (Table 1). The net sample size of the 2022 postal survey was 14,078, thereof 9,953 in the sample for West Germany and 4,209 in the sample for East Germany (Table 2). The telephone samples were around 12,000 local units in all three quarters of the year. These are subsamples of the previous year's postal survey (Tables 3 to 5). The net sample size was approximately 7,500 in the first three quarters of 2022. The four surveys from the 4^th quarter to the 3^rd quarter of the following year thus create a quasi-panel. In the observation period 2021/22, this allowed observing 36.9 % of the participants in all four surveys, 23.9 % in three of the surveys and 17.6 % in two of the surveys. 21.6 % participated only in the postal survey. The response rate in the postal survey was about 10 % and about 59 % in the telephone surveys.
Sampling design	The number of local units in every cell of the sample matrix is chosen regarding the participation rates in previous surveys to ensure a sufficient number of responses. The probability to have an open vacancy is especially low in very small units. On the other hand, very small units’ account for about 30 percent of all vacancies. For this reason, the sample size is larger in small size classes (Table 1).
Retention/renewal of sampling units	The sample is renewed once a year in the fourth quarter.
Sample size	Gross sample size: Q1 2022: 12,814 local units Q2 2022: 12,664 local units Q3 2022: 12,538 local units Q4 2022: 134,991 local units Net sample size: Q1 2022: 7,586 local units Q2 2022: 7,539 local units Q3 2022: 7,454 local units Q4 2022: 14,078 local units
Stratification	The samples for Eastern and Western Germany are stratified by - 24 sectors - 7 size classes
Other sources
Maintenance agency	The survey is conducted under the responsibility of the Institute for Employment Research (IAB) at the German Federal Employment Agency. On behalf of the IAB, the 2021 survey was conducted by Economix Research and Consulting in Munich.
Updating frequency	Not applicable
Rules for clearance (of outdated information)	Not applicable
Voluntary/compulsory reporting and sanctions	Voluntary reporting

Annexes:
Table 1 - Sampling ratio by NACE Rev. 2 and size of local units (4th quarter 2022)
Table 2 - Gross and net sampling structure, response rate by NACE Rev. 2 (4th quarter 2022)
Table 3 - Gross and net sampling structure, response rate by NACE Rev. 2 (1st quarter 2022)
Table 4 - Gross and net sampling structure, response rate by NACE Rev. 2 (2nd quarter 2022)
Table 5 - Gross and net sampling structure, response rate by NACE Rev. 2 (3rd quarter 2022)

3.2. Frequency of data collection

Reference dates

Quarterly average over all buiness days of the respective quarter.

3.3. Data collection

Brief description of the data collection method(s)

Remarks

Two methods are used for data collection:

1. Postal survey in the 4^th quarter of each year

2. Telephone survey in the first three quarters of the year [1]

Both surveys use standardized questionnaires which contain the same core questions for measuring job vacancies and use the same definitions.

Questionnaires of the postal survey are sent out twice to the firms. The first mailing is undertaken in October, the second in November each year. The second mailing addresses non-respondents only. Alternatively, addressees the postal survey can respond online. This option is used by 48 % of the firms.

Telephone surveys are equally distributed over the quarter in order to fully include fluctuations of job vacancies. Interviews are undertaken with a short questionnaire and take around 5 minutes on average. Interviewers are regularly trained in conducting statistical surveys and addressing company representatives.

[1] In the fourth quarter 2022, an additional cycle of interviews took place with a shortened questionnaire and questions focussing on the impact of the war in Ukraine. The regular reporting to Eurostat was based on the normal 4th quarter sample of 2022.

Annexes:
Table 6 - Participation in the four surveys IV-2021-III-2022

3.4. Data validation

Optional

3.5. Data compilation

Brief description of the weighting method

Weighting dimensions

In 2015, a new extrapolation procedure based on the Generalized regression estimator (GREG) was developed in close collaboration between the IAB, the Economix Research and Consulting survey research institute and the Regensburg University of Applied Sciences. This estimator is widely used in modern survey research (cf. Särndal et al. 1992; Deville/Särndal 1992) and is also recommended by the European Commission (cf. European Commission 2002).

The GREG procedure continues the basic ideas of the extrapolation method that has been used in the past. However, the adjustment to registered vacancies as an anchoring variable has been discontinued. Now, the number of employee subject to social security contributions and the number of establishments are used as anchor variables. Note that we base these numbers on the most recent available data, which is usually lagging behind by 2-3 quarters. A forecast of the employment development is used to adjust the anchor variable to the current employment levels in the German economy.

The method allows the implementation of different kinds of weights. It allows considering non-response corrections and the direct analytical calculation of key statistics to assess the quality of the extrapolation and the validity of results which allow statements regarding the statistic validity of the survey. The GREG procedure is more efficient in terms of methodology than the previously used procedure. It significantly improves the quality of the extrapolation.

GREG Implementation:

After the non-response correction (see 3.6), the GREG estimator is a calibration procedure applied to adjust the for non-response corrected design weights such that certain benchmark figures of the anchor variables are exactly achieved. The population of establishments and employees according to the BA's employment statistics is used as benchmark figure. For the matrix by size classes and economic sectors the number of size classes is limited to six and 24 economic sectors are considered. Separate extrapolations are made for Eastern and Western Germany.

The GREG estimator basically transforms input weights to output weights. Without any further restriction, the output weights can be of any small (also negative) or large size. However, negative weights are useless and a weight below 1 is hard to interpret with regard to content. An upper limit is also reasonable, depending on the sample size. In the extrapolation procedure applied here, the weights are restricted to the range [1, 10,000]. Within the scope of future extrapolations, this arrangement can be adjusted, for example, to account for different sample sizes.

A full description and the background to its development and implications is given in Brenzel, Hanna; Czepek, Judith; Kiesl, Hans; Kriechel, Ben; Kubis, Alexander; Moczall, Andreas; Rebien, Martina; Röttger, Christof; Szameitat, Jörg; Warning, Anja; Weber, Enzo (2016): Revision of the IAB job vacancy survey * backgrounds, methods and results. (IAB-Forschungsbericht, 04/2016 (en)), Nürnberg.

Main dimensions:

Number of local units and number of employees subject to social security contributions

3.6. Adjustment

Non-response adjustment

Initially, in the written survey (in each fourth quarter), a non-response estimation is made with the added auxiliary variables based on register data. An adjustment weight is calculated for the non-response behaviour. The auxiliary variables (vectors) originate from the Federal Employment Agency's administrative data (cf. Section 4.3). The affiliation to an economic sector and the affiliation to an establishment size class are included in the estimation in addition to the added average daily wage and the average age of staff. A binary choice model (logit estimator) is used to calculate the response probability for the given auxiliary variables. The inverse of this response probability of an establishment is the non-response weight (NR) for the written survey in the fourth quarter.

Since the telephone surveys in the following first, second and third quarter depend on the response behaviour in the main survey, a second-stage non-response adjustment is applied: The first component is determined by the non-response weights of the main survey. The second component is a non-response analysis conducted separately for each following quarter on the basis of the information from the auxiliary variables and the response behaviour from the main survey. So, on the one hand, a check is made first for non-responses compared to the gross sample (or the total number of establishments with one employee subject to social insurance contributions from the Federal Employment Agency) and, on the other hand, on the basis of the written survey for non-participations in the quarterly telephone surveys. Although the willingness to participate is with 80 to 90 per cent significantly higher than in the written survey, specific response behaviour can also lead to systematic distortions in the telephone survey. Here, another auxiliary variable is used as an indicator of the rapidness of the response behaviour. It became apparent that establishments that can be allocated to the first half of respondents with regard to time also have a significantly higher probability of participating in the telephone surveys in statistical terms.

4. Quality management

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4.1. Quality assurance

To check data quality, the quarterly subset of job vacancies that are reported to be registered at the Federal Employment Agency are compared with official register data.

4.2. Quality management - assessment

In the survey of Q2 2021, we detected a significant deviation between the number of survey-reported registered vacancies and the number of registered vacancies at the Federal Employment Agency. This divergence led us to an analysis of interviewer effects in the telephone interviews of the JVS survey. The analysis of interviewer effects was possible by merging a unique interviewer identifier to the micro data. Since the interviewed establishments are randomly allocated to the interviewers by the telephone institute, there should be no systematic interviewer effects. However, we detected that a specific interviewer significantly less likely (statistical precision 99.9%) inserted vacancies. We also reviewed voice files of the interviews of the respective interviewer. Our qualitative conclusion is that the respective interviewer, unfortunately, provided an unacceptable quality of interviewing. The respective interviewer was confronted with our accusation, and he/she admitted fraudulent behaviour.

As a consequence, we excluded the respective interviewer's observations from the micro data. Since the interviewer conducted interviews for JVS not only in Q2 2021 but also in Q1 2020, Q2 2020, and Q3 2020, we excluded interviews from all these quarters and revised the JVS data, respectively.

In the course of our rigorous investigation of fraudulent behaviour in the JVS data, we detected a second interviewer with significant interviewer effects. This second interviewer only conducted interviews in Q1 2020. Consequently, we also excluded the respective interviews of this second interviewer.

5. Relevance

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5.1. Relevance - User Needs

Description of the national users and their main needs

Remarks

National users:

The public via the media (TV, radio, newspapers, magazines): quarterly press release on the development of job vacancies in East and West Germany by sectors
Federal Employment Agency, Federal and State Ministries (esp. labour market and social policy, immigration policy): short term labour demand, labour and skill shortages, strategies against shortages

International users:

European Commission: publication of data by Eurostat, European Job Vacancy Monitor
European Central Bank and OECD: short term labour demand

Use by national and international scientific researchers:

economic research: matching and mismatch, recruitment processes
sociological research: the effect of labour market reforms, the role of networks in the recruitment process
survey methodology: survey design, non-response-analysis, multiple imputation methods, small area estimation

5.2. Relevance - User Satisfaction

Extent to which the needs of national users are satisfied (voluntary)

Remarks

The German job vacancy survey measures the volume of unfilled jobs in the surveyed quarter. It covers the German economy with all private enterprises, associations and public institutions as far as they employ at least one registered employee[2]. Private households and exterritorial institutions are excluded.

Job vacancies include all posts for which the company actively searches qualified staff at external labour markets. They include all types of labour contracts for a dependent job, irrespective of social security registration, duration of employment or occupational status. Job vacancies include posts for immediate recruitment and later recruitment, as long as the company is actively searching.

The survey measures the number of occupied posts including all types of employment, such as dependent employment, self-employment, civil service and marginal employment.

The 4^th quarter survey 2010 is the first survey which fully applies NACE Rev. 2 and is therefore able to provide data in the 19 sector breakdown.

As the sample for the 4^th quarter 2009 was established on the basis of NACE Rev. 1.1, the representation of NACE Rev. 2 is not available. The reclassification of micro-data according to NACE Rev. 2 was tested. The results were insufficient as particular sectors, such as information and communication or real estate activities, were not adequately represented in the former sample.

[2] Registered by public social insurance.

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

Regulation is fulfilled.

5.3.1. Data completeness - rate

Optional

6. Accuracy and reliability

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6.1. Accuracy - overall

Optional

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). See also Table 11.

Coefficient of variation for the whole economy (%)

Year	Quarter	CoV full sample	CoV 10+ employees
2022	1	3%	3%
2022	2	3%	3%
2022	3	3%	3%
2022	4	2%	2%

For coeffients of variation for each NACE by quarter, see Tables 7-10.

Annexes:
Table 7 - Estimated sampling errors for vacancies by NACE Rev. 2 (1st quarter 2022)
Table 8 - Estimated sampling errors for vacancies by NACE Rev. 2 (2nd quarter 2022)
Table 9 - Estimated sampling errors for vacancies by NACE Rev. 2 (3rd quarter 2022)
Table 10 - Estimated sampling errors for vacancies by NACE Rev. 2 (4th quarter 2022)
Table 11 - Estimated sampling errors for vacancies by quarter (2022)

6.3. Non-sampling error

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
The strong diversity in the number of vacancies creates a serious sensitivity of the calibration method to extreme values. This is due to the fact that vacancy information shows a high degree of variation at the micro-level. One third of the business units offer not more than one vacancy at the time of observation, and not more than 5 % offer 25 vacancies or more. The new weighting procedure is constructed without an adjustment to registered vacancies. The number of employees subject to social security contributions and the number of establishments are used as anchor variables. This method allows considering non-response corrections and the direct deduction of key figures to assess the quality of the extrapolation and the validity of results which allow statements regarding the statistic validity of the survey. The GREG procedure is more efficient in terms of methodology than the previously used procedure. It significantly improves the quality of the extrapolation.	see 3.5	see 3.6

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
The sampling frame (the business register maintained by the German Federal Employment Agency) consists of all business units that have at least one employee covered by the public social insurance system. Any other business units are not part of the sampling frame, and therefore the estimates might slightly be biased downwards as they exclude companies with non-registered employees only. A similar bias might occur, because the sampling frame is updated with a time lag of several months. Very new business units are thus excluded from the sampling frame; however, the frame might contain units that ceased to exist after the latest frame update. As the estimates are calibrated to the (estimated) current number of business units in the population during the period of observation, the effects of such biases are largely corrected.	See first column	The survey is conducted as quarterly average.	See first column

6.3.1.1. Over-coverage - rate

Optional

6.3.1.2. Common units - proportion

Optional

6.3.2. Measurement error

see 6.3

6.3.3. Non response error

see 3.6

6.3.3.1. Unit non-response - rate

Unit non-response rate (see also Tables 2 - 5)

1^st quarter 2022	2^nd quarter 2022	3^rd quarter 2022	4^th quarter 2022
40.8 %	40.4 %	40.5 %	89.5 %

To cope with the low response rates and to minimize non-response bias as far as possible, the calibration procedure described in the section on Data compilation (weighting procedure) is used for estimation.

6.3.3.2. Item non-response - rate

Optional

6.3.4. Processing error

See 6.3. Non-sampling error.

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

No imputation procedures for item non-response concerning the number of job vacancies were applied.

The occupied posts are included in the survey each quarter. However, in very few cases this variable is missing due to item non-response of the respective establishments. In such cases we impute the number of employees from the previous quarter. If it is again not available in the previous quarter, we go back up to the previous Q4 wave, where we have the number of employees for each firm in the data.

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.

A new extrapolation procedure based on the Generalized regression estimator (GREG) was developed in close collaboration between the IAB, the Economix Research and Consulting survey research institute and the Regensburg University of Applied Sciences. This estimator is widely used in modern survey research (cf. Särndal et al. 1992; Deville/Särndal 1992) and is also recommended by the European Commission, for instance (cf. European Commission 2002). See points 3.5 and 3.6

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.

Since the fourth quarter of 2014, the time series collected is sufficiently long to allow for seasonal adjustment. The seasonally adjusted time series is calculated using the jDemetra+ Software provided by Eurostat. The preferred adjustment follows the TRAMO/SEATS procedure and is calculated over the entire series for each quarter. It is done on the level of aggregated series provided to Eurostat[3] for all local units and local units with at least ten employees.

From 2016q4 onwards, there are regular revisions of past observations and their seasonal adjustment. This adjustment will be based on updates of the administrative data.

[3] Given that Eurostat has aggregated the individual series for EU-wide statistics, the earlier method to provide series by 19 sectors with seasonal adjustment has not been continued. Eurostat requested to provide the aggregated series with seasonal adjustment.

Annexes:
Quality reporting on SA of JVS 2022

6.5. Data revision - policy

Optional

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.

In 2024, the vacancies und posts of 2022 will be (regularly) revised according to the final administrative employment figures of the Federal Employment Agency.

6.6.1. Data revision - average size

Optional

7. Timeliness and punctuality

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7.1. Timeliness

See below.

7.1.1. Time lag - first result

Information on the time span between the release of data at national level and the reference period of the data.

Data are sent to Eurostat within 45 days after the end of the reference quarter.

7.1.2. Time lag - final result

Optional

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

	1^st quarter 2022	2^nd quarter 2022	3^rd quarter 2022	4^th quarter 2022
Fieldwork	07.01. - 31.03.2022	01.04. - 30.06.2022	01.07. - 30.09.2022	27.09.2022 - 10.01.2023
Assembly of data and quality control	08.04. - 15.04.2022	07.07. - 13.07.2022	07.10. - 14.10.2022	01.02. - 13.02.2023
Calibration	22.04.2022	20.07.2022	21.10.2022	13.02.2023
Reporting, delivery of data	06.05.2022	05.08.2022	28.10.2022	31.03.2023

See table in the first column

Data are available within six weeks after the end of the quarter.

Annexes:
Table 12 - Schedule for the job-vacancy surveys in I-2022-IV-2022

8. Coherence and comparability

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8.1. Comparability - geographical

Information on differences between national and European concepts, and — to the extent possible — their effects on the estimation.

The revised data are fully consistent with Eurostat standards.

8.1.1. Asymmetry for mirror flow statistics - coefficient

Optional

8.2. Comparability - over time

Information on changes in definitions, coverage and methods in any two consecutive quarters, and their effects on the estimation.

The time series has been weighted using the new weighting method for provided data. This produces a consistent series concerning the weighting procedure since 2010.

The weighting procedure is described in Brenzel et al. (2016).[1]

[1] Brenzel, Hanna; Czepek, Judith; Kiesl, Hans; Kriechel, Ben; Kubis, Alexander; Moczall, Andreas; Rebien, Martina; Röttger, Christof; Szameitat, Jörg; Warning, Anja; Weber, Enzo (2016): Revision of the IAB job vacancy survey * backgrounds, methods and results. (IAB-Forschungsbericht, 04/2016 (en)), Nürnberg.

8.2.1. Length of comparable time series

Optional

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.

There are no other administrative sources or other representative surveys on the population of job vacancies in Germany. The administrative data from the Federal Employment Agency only cover the number of registered vacancies, which covers about half of the total number of vacancies.

Attached you can find a comparison of occupied posts between data of the JVS and the LFS.

Annexes:
DE Beveridge curve 2022
DE Comparison of JVS with LFS data 2022

8.4. Coherence - sub annual and annual statistics

Optional

8.5. Coherence - National Accounts

Optional

8.6. Coherence - internal

Optional

9. Accessibility and clarity

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9.1. Dissemination format - News release

Optional

9.2. Dissemination format - Publications

Dissemination scheme, including to whom the results are sent	Periodicity of national publication	References for publications of core results, including those with commentary in the form of text, graphs, maps, etc.	Information on what results, if any, are sent to reporting units included in the sample
JVS data are disseminated online by the IAB in German language: https://iab.de/das-iab/befragungen/iab-stellenerhebung	Aggregated data are published online	Publications that apply the IAB-Job Vacancy Survey can be accessed through: https://iab.de/dossier/?id=265002	Not applicable

9.3. Dissemination format - online database

Optional

9.3.1. Data tables - consultations

Optional

9.4. Dissemination format - microdata access

Optional

9.5. Dissemination format - other

Optional

9.6. Documentation on methodology

Optional

9.7. Quality management - documentation

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

No specific metadata are provided. The quarterly press release contains all important information regarding meta data changes.

Kettner, Anja, Vogler-Ludwig, Kurt (2010): The German job vacancy survey. An overview. In: European Commission, Eurostat (Ed.): First and second International Workshops on Methodologies for Job Vacancy Statistics. Proceedings, Eurostat Methodologies and working papers, Luxemburg, S. 7-17.

Brenzel, Hanna; Czepek, Judith; Kiesl, Hans; Kriechel, Ben; Kubis, Alexander; Moczall, Andreas; Rebien, Martina; Röttger, Christof; Szameitat, Jörg; Warning, Anja; Weber, Enzo (2016): Revision of the IAB job vacancy survey * backgrounds, methods and results. (IAB-Forschungsbericht, 04/2016 (en)), Nürnberg.

Bossler, Mario; Gürtzgen, Nicole; Kubis, Alexander; Küfner, Benjamin; Lochner, Benjamin (2020): The IAB Job Vacancy Survey: design and research potential. In: Journal for labour market research, Vol. 54, No. 1, Art. 13.

Bossler, Mario; Kubis, Alexander; Küfner, Benjamin; Popp, Martin (2021): The IAB Job Vacancy Survey: Establishment survey on labour demand and recruitment processes, waves 2000 to 2018 and subsequent quarters 2006 to 2019. (FDZ-Datenreport, 09/2021 (en)), Nürnberg, 19 S.

Data are provided with a quarterly press release. New results and visible trends are intensively discussed by the national media on base of this release.

9.7.1. Metadata completeness - rate

Optional

9.7.2. Metadata - consultations

Optional

10. Cost and Burden

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Optional

11. Confidentiality

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11.1. Confidentiality - policy

Optional

11.2. Confidentiality - data treatment